50 Reporting Tools for Data Scientists in 2019 From Experts

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In this blog, I will walk you through more than 50 reporting tools for data scientists that industry experts have recommended. This can be long, but you can see the complete list on the table below and you can go directly to the reporting tool’s details by clicking on it.

Alteryx Automatic Statistician KNIME Analytics Platform PythonReports
Amazon Lex BigML Logical Glue Qubole
Anaconda D3.js Lumen Data R
Apache Giraph Datapine MATLAB RapidMiner
Apache Hadoop DataRobot Matplotlib RStudio
Apache HBase Domo Microsoft Azure ML Studio Redis
Apache Hive Excel MLBase SAS
Apache Kafka Feature Labs MLJAR Scikit-learn
Apache Mahout Ggplot2 NLTK Tableau
Apache Mesos GraphLab Create NumPy TensorFlow
Apache Pig IBM Watson Studio Octave Trifacta
Apache Spark InetSoft OpenRefine Weka
Apache Storm Jupyter Pandas XLCubed
Anaconda Keras Paxata

The need for data science

If there’s anything common between startup companies, multinational corporations, political leaders, and other organizations, it’s the use of data in coming up with strategic decisions. 

Startups gather all the data they can about the market, including consumer behavior and details about their competitors to come up with a solid business plan.

SMEs, multinational corporations, and organizations that have been established in their respective industries, rely on statistical data such as market trends and past performances when deciding the fate of subsidiaries, departments, and even corporate leaders. 

Political parties spend millions of dollars just to conduct surveys that will allow them to determine which candidate to support.

Organizations in all sectors get insights from data and use these to make important decisions, from which suppliers to source their raw materials from, what countries to look into for expansion, to whether or not a product or service is worth investing in. 

Data has always been an important commodity, but in recent years, the industry has seen a huge increase in the number of companies adopting big data. 

In a study by Dresner Advisory Services, they found out that the number of companies adopting big data has significantly increased from 17% in 2015, to 41% in 2016, and 53% in 2017. 

adopting big data

This graph shows the year on year percentage of companies adopting big data, from 2015 to 2017.

The number of companies who were holding off on big data adoption has decreased to only 11% over the same three-year period.

In fact, experts had been actively comparing big data to crude oil, as evidenced by a tweet from Nick Bilodeau, a financial technology expert.

If data is the new oil, then data science is the machine that processes it to make it useful. Without it, data will be unreadable event to industry leaders, and insights can’t be derived from it. 

What is a data scientist?

Data science is the machine that processes big data, whereas data scientists are the people behind these machines. Data scientists are problem solvers with a high level of analytical and technical skills.

Among their inherent characteristics is curiosity. Curiosity on what the company needs in order to succeed, curiosity to explore tools and make them work for their purpose, and curiosity to know what they don’t know. 

As Cathy O’Neil, American mathematician and author of Weapons of Math Destruction, aptly said, “Sometimes the job of a data scientist is to know when you don’t know enough.”

Specific responsibilities of a data scientist include:

  • Gather unstructured data at scale and turning them into structured, readable data.
  • Use different programming languages such as Python, SQL, and R.
  • Keep up with the latest analytical methodologies such as deep learning and machine learning. 
  • Analyze data in such a way that they recognize patterns and see trends that can help the company achieve its goals.
  • Solve complex problems using data and statistics. 

A data scientist is also adept with handling and customizing different tools including reporting tools.

Reporting Tools vs Business Intelligence Tools

People have often used the terms business intelligence tools and reporting tools interchangeably, that the differences between them had somehow blurred. But if you are going to examine these two tools closely, you’ll see that they are used to fill different business purposes.

Most business intelligence suites already include a reporting tool, and rightly so because according to the Dresner study I previously cited, reporting is the number on the list of technologies and initiatives that are strategic to business intelligence.  

Dresner study

This graph from the Dresner Big Data Analytics Market Study shows the top 33 technologies and initiatives that are strategic to business intelligence. Reporting is at the top of the list.

Here’s how reporting tools differ from business intelligence tools:

  • Perspective: Reporting tools reflect the status of the company based on what had happened in the past, while business intelligence tools explain what has happened and how performance can be improved.
  • Scope: Reporting tools are used for a specific data set such as the daily report on the number of orders, and how many products were delivered. Business intelligence tools, however, pool several data sets and show the relationship between these data. 

For instance, through BI tools, you’ll discover why the number of deliveries has decreased by looking at data from the human resource department. You will then learn how to increase the performance of your delivery team so the number of deliveries per day will catch up with the number of orders received.

  • Format: Departments stick to a fixed reporting format to make it easier for workers. Delivery teams, for instance, will know in one glance what deliveries to make because they have become familiar with the format overtime.

When it comes to business intelligence tools, however, the format is dynamic which allows companies to view different sources of data quickly and see cause and effect relationships between them.

Factors to Consider When Choosing a Reporting Tool

Reporting tools help increase productivity and can contribute tremendously to the overall business performance of your company.

An important consideration though is the reporting tool you choose since not all reporting tools are created equal. The reporting tool you choose can define the performance of key departments, so it’s important to select the tool carefully.

The factors you should consider in the selection process are:

  • The number of users: The first thing to appraise is the number of people who will use the tool, not only at this point of your business but also in the future. Are you planning to expand? Then the number of users may increase too. Make sure that the reporting tool you choose allows this growth.
  • The size of data to be handled: You should have an idea about the size of data that the reporting tool is expected to handle. The reporting tool must scalable so it can face the growing size of data especially for SaaS and internet-based companies. 
  • Your budget: The amount of money you can invest in is also very important. Learn and compare the prices of different tools and see if they are within your budget for it.
  • Ease of use: The learning curve when using the tool must be short for it to effectively drive productivity. Select a tool that has an intuitive user interface so users can easily understand how to use it. 
  • After-sale support: There can be issues that require you to contact the vendor’s support team, so make sure that they provide a decent after-sale support. This can include resources such as videos and tutorials.
  • Reputation of the vendor: Lastly, you also need to look into the reputation and stability of the vendor. Has the company been in the industry long enough? If they are new, do their long term plans look good? Who are the people behind the company? You need to know these things since you will be entrusting your company data to the reporting tool.

 

Explore 50+ reporting tools for data scientist

50 reporting tools 2019

#1 SAS

SAS is an analytics powerhouse for more than 40 years, trusted by 92 of the top 100 companies on the Fortune Global 1000 in 2018. Its headquarter is in Cary, North Carolina and it has offices in other countries.

reporting tools_sas

Aside from Business Intelligence & Analytics, the SAS software suite also provides product solutions for the following business areas:

  • Advanced Analytics
  • AI Solutions
  • Cloud Computing
  • Customer Intelligence
  • Data Management
  • Decision Management
  • Fraud, Business Intelligence & Analytics
  • Hadoop
  • IoT Analytics
  • Performance Management
  • Personal Data Protection
  • Supply Chain Management

The whole SAS software suite has over 200 components, but what we are going to look at today is the SAS EBI or the Suite of Business Intelligence Applications which includes a reporting tool. 

Features 

These are the features of SAS Business Intelligence: 

  • Customizable dashboard
  • Drag and  drop functionality
  • Reports: Financial, Marketing, and Sales
  • Export 
  • Report automation and scheduling 
  • Data source connectors
  • Drill down
  • Forecasting

If we are going to define one strength of SAS, that would be the fact that it is a comprehensive tool. Clients don’t have to employ other tools for their business intelligence, data visualization, and statistical analysis.

Markets Supported

The SAS software has been used in a lot of markets including:

  • Banking
  • Capital Markets
  • Casinos
  • Communications
  • Consumer Goods
  • Defense & Security
  • Government
  • Health Care and Insurance
  • Higher Education
  • Hotels
  • Life Sciences
  • Manufacturing
  • Media
  • Midsize Business
  • Oil & Gas
  • P-12 Education
  • Retail
  • Sports
  • Travel & Transportation
  • Utilities

SAS is one of the major players in Business Intelligence, along with SAP, IBM, Salesforce, and other market leaders. Take a look at the Gartner Magic Quadrant for Business Intelligence  and Analytics Platform that Ronald von Loon tweeted:

Cost

SAS Business Intelligence plans start at $8,000 per user, per year. The company has partnered with Wells Fargo in the US and Canada for their payment options program that includes several payment methods. 

Clients can choose deferred payments and flat or ramped payments. They can also pay annually, semi-annually, quarterly, and monthly as long as they meet the following requirements:

  • Has been in business for two to three years
  • Has at least 10 employees.
  • Spends at least $10,000 in total.
  • Has been approved for credit.

 Ratings

SAS Business Intelligence is rated 4.5 out of 5 stars by 31 respondents in Capterra, and 4 out of 5 stars by 46 respondents in G2 Crowd.

#2 Alteryx 

Alteryx focuses on self-service, end-to-end data analytics. Among the solutions it supports are advanced analytics, business intelligence and visualization, data discovery and management, location intelligence, data preparation, and technology integrations.

reporting tools_alteryx

Alteryx is trusted by thousands of clients around the world, including McDonald’s, Audi, Unilever, and Experian.

Alteryx’ CEO, Dean Stoecker, made it to the news recently for hitting a personal net worth of $1 billion.

Features

The features of Alteryx are:

  • Repeatable Workflow
  • Code-free
  • Deployable analytics
  • Flexible
  • Scalable

Alteryx is popular for its code-free and code-friendly features, and they claim that their tool can turn anyone into a data scientist.

Markets Supported

Alteryx is being used in the following industries:

  • Financial services
  • Healthcare
  • Retail
  • Transportation and logistics
  • Oil and gas
  • Public sector

 Cost

The Alteryx Designer product is priced at $5,195 per user, per year. However, if you’re going to add more features and capabilities, the annual price goes up for each user:

  • $11,700 for Alteryx Designer plus Location Insights Dataset
  • $33,800 for Alteryx Designer plus Business Insight Dataset

Ratings

Alteryx is rated 5 out of 5 stars by 61 respondents in Capterra, and 4.5 out of 5 stars by 114 respondents in G2 Crowd

#3 Apache Giraph

Apache Giraph is an open-source graph processing tool which was primarily developed as a counterpart to Google’s Pregel. It is the system used by Facebook to process and analyze the social graph of users and their network connections.

reporting tools_giraph

As such, it’s a tool recommended by most experts in big data when it comes to establishing relationships between datasets. 

Features 

The features of this reporting tool are:

  • Out of core and master computation
  • Edge-oriented input
  • Sharded aggregators
  • Scalable
  • Fast
  • Customizable

Giraph is mostly used by social media platforms including Facebook and Twitter to analyze social media data. It’s strongest feature is its scalability which makes it suitable for huge amount of data.

Markets Supported

Giraph is popularly used in the social media industry, but it is also being used in the following industries:

  • Higher Education
  • Staffing and Recruitment
  • IT Services
  • Management Consulting Services
  • Internet / Social Media
  • Marketing & Advertising
  • Construction
  • Financial Services

Cost

The price of the software depends on several factors and it’s not disclosed. You need to contact Apache for a customized pricing computation. 

Ratings 

Apache Giraph is rated 4.3 out of 5 stars on G2 Crowd. This rating is only from two respondents.

#4 Datapine

Datapine is developed on the premise of building online reports without the need for advanced technical skills. The platform makes creating interactive dashboards easy and simple with its report builder which has the combined benefits of a centrally-managed reporting software, and a cloud-based application.

Features

Datapine enables users to explore, analyze, and generate report from their data with only a few clicks and without any coding required. The results can then be shared in a visualized dashboard where automated reports can be generated. Other key features are:

  • Fast & easy data connectors
  • Many interactive dashboard features
  • AI-based data alerts
  • Predictive Analytics & Forecasting
  • Multiple report sharing options (Email, URL, embedded dashboards etc.)
  • High German security standards

The best thing about Datapine is that all you need to do is connect it to your data source(s) and you can already generate reports and insights in less than 10 minutes.

Markets Supported

Datapine covers many different industries including for example Retail, Manufacturing, Logistics, Market Research, Digital Media and Healthcare.

Among the organizations that use the reporting tool are the University of Texas, Kreditech, Media Markt, Fog Creek Software, and Axel Springer.

Cost

Datapine is available for free for 14 days. After this, you can avail of any of their four pricing tiers as described below:

  • Basic
  • Professional
  • Premium
  • Branding & Embedded

Ratings 

Datapine is rated 4.5 out of 5 stars on Capterra.

#5 BigML

BigML is a platform that makes machine learning a lot easier for data scientists as it provides pre-engineered algorithms and framework. BigML can be used in the cloud or on-premises.

reporting tools_bigml

BigML comes highly recommended by data professionals. In the tweet below, it’s second on the list of tools you should know or use if you’re into Machine Learning and AI:

Features 

The features of BigML include:

  • Complete machine learning platform
  • Immediate access
  • Interpretable & exportable models
  • Collaboration
  • Programmable
  • Automated
  • Flexible

Among these features, the one that makes BigML popular is the fact that it provides a complete and comprehensive machine learning platform.

Markets Supported

BigML is used in the following industries:

  • Pharmaceutical
  • Aerospace
  • Food
  • Energy
  • Entertainment
  • Financial Services
  • IoT
  • Healthcare
  • Automotive
  • Telecommunications
  • Transportation

Cost

BigML offers two types of subscription plans: Free and Prime.

  • Free: With a free account, data scientists will have access to all functionality for personal and education purposes. Only one user is allowed under this plan, and he or she will have a maximum dataset size of 16 MB and two parallel tasks.
  • Prime: Prime account holders are given priority over free accounts. They can run parallel tasks ahead of free accounts. Prime accounts start at $30 with the Standard plan, $150 for the Boosted plan, $300 for the Pro plan, $2,500 for the Bronze plan, $5,000 for the Silver plan, $7,500 for the Gold plan, and $10,000 for the Platinum plan.

Ratings 

BigML is rate 4.7 out of 5 stars on G2 Crowd, from 25 respondents.

#6 D3.js

D3.js is a JavaScript library that enables data engineers to create interactive data visualizations in web browsers. It replaced the Protovis framework, making use of HTML5, CSS (Cascading Styles Sheets), and SVG (Scalable Vector Graphics).

reporting tools_d3js

Features 

Among the features of D3.js are:

  • Web standards
  • Built-in element inspector
  • Data-driven approach to DOM Manipulation
  • Can support huge datasets
  • Flexible, and easy to use
  • Codes are reusable

As a reporting tool, D3 provides a data visualization platform for your datasets. What’s great about D3.js is that it’s modular. This means that you can download only the codes you want to use, and not the entire D3.js libraries. 

Markets Supported

D3.js is used by different industries, from Computer Electronics, Data Science, Finance, and Consumer Services. Since the tool is web-based, some of the websites that use it are:

  • Urbandictionary.com
  • Grammarly.com
  • vodafone.com
  • Kin.naver.com
  • Lenta.ru
  • Baidu.com

D3 is also used in the Higher Education sector, with professors like Alex Wellerstein of Stevens Institute of Technology. Here’s an example of a project he worked on using D3:

Cost

Since D3.js is modular, the developer had employed a quote-based pricing approach. You need to get in touch with them and tell them your requirements so they can create a price quotation for you.

Ratings 

D3.js has a 4-star rating on Capterra, from 5 respondents and a 4.4-star rating on G2 Crowd, from 19 respondents.

#7 MATLAB

MATLAB or Matrix Laboratory,  is a computing environment and a programming language in itself. It enables data engineers to plot functions and data, manipulate matrices, create user interfaces, implement algorithms, and so much more.

reporting tools_matlab

MATLAB has several use cases including math and computation, modeling, prototyping, and simulation, algorithm development, data analysis, data exploration and visualization, and app development.

Features 

MATLAB features a wide library of mathematical functions for:

  • Linear algebra
  • Non-linear functions
  • Statistics
  • Fourier analysis
  • Numerical integration
  • Differential equations

Aside from this, MATLAB makes 2D and 3D plotting, data analysis, and app development easier with its interactive environment and programming interface. 

Markets Supported

MATLAB is used by more than 3 million people around the world in several industries including:

  • Medical Devices
  • Civil Engineering
  • Computer Software
  • Computer Hardware
  • Higher Education
  • Staffing and Recruiting
  • Aviation 
  • IT Services

Cost

MATLAB has four pricing plans that are based on where and how the license is going to be used. These are:

  • Standard: The Standard plan is for business organizations. Under this plan, you have three options depending on the number of users: Individual, Network Named User (a group of people will use the network one at a time), and Concurrent (multiple users can access the software simultaneously. 

The perpetual license of the Standard/Individual plan is $2,350, while the yearly license fee is $940.

  • Education: This plan is for schools or universities, and under this plan there are four choices based on how it’s going to be used: Academic, Campus-Wide, Academic, and Classroom. License fee starts at $550 for perpetual license and $275 for an annual license.
  • Home: If you’re planning to use MATLAB for personal use, then this is the plan you should select. It costs $95, and you can purchase add-ons.
  • Student: For students who want to use MATLAB to fulfill academic research and other course requirements, the license costs $29 and $55 for the student suite license. 

Ratings 

MATLAB is rated 4.5 stars on both Capterra and G2 Crowd, with 1,038 and 438 respondents respectively. 

#8 Ggplot2

This is primarily a data visualization tool developed primarily for the statistical programming R.

reporting tool_github

Ggplot2 is a complete data visualization tool, with automatic legends and colors, two-color gradient to differentiate between positive and negative values, smoothing overlays that are customizable, and elaborat, pleasant-looking graphs.

It can easily turn Cartesian graphs into polar graphs with just one statement. With ggplot2, you can use different data sets and create a single graph. 

Markets Supported

Ggplot2 has millions of downloads on Github, and most people who download it are data scientists from tech companies; journalists, and even the U.S. government. 

Ratings 

Financesonline Score on the User Satisfaction 96%

#9 Tableau

Tableau is a data visualization tool that simplifies large data sets and turn them into easy-to-understand format. Even non-technical persons can create dashboards in Tableau. 

reporting tool_tableau

Features 

The most important features of Tableau are:

  • Data blending
  • Real time collaboration
  • Real time analysis
  • Ad Hoc reports
  • KPIs
  • Dashboard
  • Predictive and profitability analysis
  • Visual analytics

Markets Supported

Thousands of companies all over the world uses Tableau, and most of them belong to the following industries:

  • Computer Software
  • Information Technology
  • Hospital
  • Human Resource
  • Financial Services
  • Higher Education
  • Management Consulting
  • Retail
  • Marketing and Advertising
  • Nonprofit Organization Management

Cost

There are three pricing options if you want to use Tableau. They have a plan for Individuals, for Teams & Organizations, and for Embedded Analytics.

  • Individuals: The Tableau Creator for individuals is priced at $70 per user, per month, billed annually.
  • Teams & Organizations: Tableau offers more product options for businesses. Aside from the Tableau Creator, there’s also the Tableau Explorer which allows users to explore and make changes at $35 per user, per month; and the Tableau Viewer which only allows users to view the dashboards, at $12 $35 per user, per month.

If you choose to have Tableau host the tool, the prices go up to $42 and $15 for Tableau Explorer and Tableau Viewer, respectively.

  • Embedded Analytics: This plan allows organizations to deliver analytics to their customers. Price for Tableau’s Embedded Analytics is quote-based. 

Ratings 

On Capterra, Tableau is rated 4.5 out of 5 stars by 1,091 respondents. On the other hand, it has a 4.4 star rating on G2 Crowd, from 691 respondents.

#10 Jupyter

Jupyter offers a platform for notebook environment reporting with Jupyter Notebook and Jupyter Lab. Project Jupyter is a  nonprofit organization which was initially a spin-off of IPython, but later on focused on developing several open-source software for “interactive computing across dozens of programming languages.” 

reporting tool_jupyter

Features 

The main features of Jupyter are:

  • Fast interface
  • Easy to use and easy to learn
  • Compatible with several programming languages
  • In-browser code and rich text editing 
  • Automatic syntax highlighting
  • Ability to display computation results using HTML, PNG, SVG, and other rich media 

With these features, Jupyter is easily dubbed as data scientists’ computational notebook of choice.

Markets Supported

Industries using Jupyter range from Computer Software and Insurance, to Communications and Data Science. Some of the companies that use the application are:

  • Intuit
  • SoFi
  • SendGrid
  • Checkr
  • AgFlow
  • Policygenius
  • MD Insider

Cost

Project Jupyter has ot provided pricing details, but you can get started with the application by installing it on your computer.

Ratings 

On G2 Crowd, Jupyter Notebook is rated 4.5 out of 5 stars by 80 respondents. 

#11 Matplotlib

Matplotlib is a plotting library that uses Python 2D. With Matplotlib, users can generate histograms, power spectra, bar charts, error charts, and other graphs using a few lines of code. The data visualization tool can be used in several environments like Python, IPython, Jupyter notebook, and other user interface programs. 

reporting tool_matplotlib

Features 

The greatest benefit you can get in using Matpotlib is that it is very user friendly and even new programmers can use it. Plotting in Matplotlib is made simple since there is a pylot, a module that assists users when plotting.

Markets Supported

Matplotlib is used in several industries including Information Technology, Computer Software, Human Resource, Financial Services, Retail, and Marketing and Advertising.

Cost

Matplotlib is free to use.

Ratings 

The application has a 4-star rating from six respondents on G2 Crowd

#12 NLTK (Natural Language Toolkit)

NLTK is a platform that offers simple interfaces to more than 100 corpora and lexical resources, and it also provides a suite for text processing libraries. It is used in building programs using Python 

reporting tool_nltk

Features 

The biggest advantage in using NLTK as a text analytics platform is that it includes a wide library of natural languages algorithms including part-of-speech, tokenizing, sentiment analysis, and topic segmentation.

Markets Supported

NLTK is under the category of Natural Language Processing, and among the industries that use it are:

  • Higher Education
  • Computer Software
  • Information Technology and Services
  • IoT
  • Human Resources
  • Aerospace
  • Consumer Electronics

Cost

NLTK is a free, open-source platform that relies on the contribution of its community. 

Ratings 

NLTK has a 4.5-star rating in G2 Crowd.

#13 Scikit-learn

Scikit-learn is a machine learning library for the Python programming language. It is built on SciPy, NumPy, and matplotlib, and is also open-source. It can be used and reused by companies under the BSD license. 

reporting tool_scikit

Features 

Several data scientists have named Scikit-learn as the best tool for machine learning as it has these features:

  • It has hyperparameter tuning tools like GridSearchCV and RandomSearchCV.
  • It provides preprocessing tools.
  • It allows regression.

Aside from regression, the tool also enables users to classify, cluster, perform dimensionality reduction, model selection, and preprocessing.

Markets Supported

Scikit-learn is used widely in different industries including in the stock market, hotel bookings, music streaming, market research, and any market that requires prediction of consumer behavior. 

Cost

Scikit-learn is free to use and is covered by the BSD license type.

Ratings 

Scikit-learn is rated 4.8 stars on G2 Crowd, based on 41 respondents.

#14 TensorFlow

TensorFlow was developed by the Google Brain team initially for internal use only, and was later on released under Apache License 2.0 in November 2015.

reporting tool_tensorflow

 It’s a free, open-source symbolic math library suitable for machine learning. TensorFlow can be used by researchers to run high-end machine learning applications. At the same time, developers can create machine learning apps using TensorFlow. 

Features 

The features of TensorFlow are:

  • Comprehensive tools and libraries for large-scale neural networks.
  • Simple and flexible architecture.
  • Ability to use high-level APIs like Keras.
  • Large community of developers and researchers behind it.

TensorFlow already has pre built models and subblocks that can be combined with the use of Python scripts.

Markets Supported

TensorFlow is used by multinational corporations such as LinkedIn, Coca Cola, Airbnd, GE Healthcare, Intel, PayPal and Twitter. Industries that use TensorFlow are:

  • Social networking 
  • Cloud data storage
  • Internet
  • Ecommerce
  • Computer hardware
  • Computer software

Cost

TensorFlow is free to use under the Apache License 2.0.

Ratings 

TensorFlow is rated 4.5 out of 5 stars in both G2 Crowd and Capterra, with 38 and 66 reviews, respectively.

#15 Weka

Weka or Waikato Environment for Knowledge Analysis is a machine learning suite written in Java, making it simple and customizable for any implementation.  

reporting tool_weka

Weka contains a wide selection of data visualization tools, making it an effective reporting tool. It also provides algorithms for data analysis which can easily be accessed because of graphical user interfaces that go along with the tool. 

Features 

The most attractive aspect of Weka is that it is available for free under the GNU General Public License. Its graphic user interfaces make Weka easy to use and understand and since it is written in Java, it can therefore run on any modern platform for computing.

Weka supports tasks that are basic to data mining such as data preprocessing, classification, regression, and visualization. 

Markets Supported

Among the industries that use Weka are Retail, Financial Services, and Biotech.

Cost

Weka is free to use under the GNU General Public License. 

Ratings 

With 8 and 12 respondents respectively, Weka received a 4.5 and 4.4 rating on Capterra and G2 Crowd.

#16 Apache Hadoop

Apache Hadoop is used as a distributed processing tool in big data. It is primarily a framework that can be used in processing large data sets in a distributed environment. Apache Hadoop has a powerful storage capacity that allows users to do large scale data processing. 

reporting tool_hadoop

Features 

The strongest features of Apache Hadoop lies in its major components which are:

  • Hadoop YARN: A scheduling and management system that appropriately schedules the distribution of resources to different cluster of machines.
  • Hadoop Distributed File System or HDFS: HDFS is a clustered file storage system that has high bandwidth. It can store any kind of data in their original format, regardless of its source. 
  • Hadoop MapReduce: This is a programming model for distributed processing of large data sets. The data are fed to mappers in small quantities where the targeted data are isolated. The data is then fed to reducers which collate it into something meanngful. 

 

 Markets Supported

Industries that use Apache Hadoop are:

  • Computer Software
  • Higher Education
  • Financial Services
  • Information Technology
  • Human Resources
  • Healthcare
  • Internet
  • Telecommunications

Some of the companies that use Apache Hadoop are Wipro, TouchCommerce, Zipcar, and Conversant Media.

Cost

Hadoop is free to download and use since it is an open source software. However, commercial versions or distros of Hadoop are also available.

Ratings 

Apache Hadoop received a 8.3 on Trust Radius and 8.4 on Predictive analysis Today.

There are no ratings available for Apache Hadoop on Capterra and G2 crowd although it is widely used by companies from different sectors. According to Enlyft, the software is used by more than 30,000 companies. 

#17 Apache HBase

Apache HBase can host huge tables of data with billions of rows and millions of columns. It is an open-source, versioned, and distributed non-relational database which is developed as a reproduction of Google’s Bigtable. With Apache HBase, you can access big data in real time, anytime and anywhere.

reporting tool_hbase

Features 

The features of Apache HBase according to its website are:

  • Linear and modular scalability.
  • Consistent reads and writes.
  • Automatic and configurable sharding of tables
  • Automatic failover support between RegionServers.
  • Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables.
  • Easy to use Java API for client access.
  • Block cache and Bloom Filters for real-time queries.
  • Query predicate push down via server side Filters
  • Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options
  • Extensible jruby-based (JIRB) shell
  • Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX

Markets Supported

Apache HBase is used in the following industries:

  • Computer Software
  • Computer Hardware
  • Information Technology 
  • Staffing/Recruitment
  • Financial Services
  • Management Consulting
  • Healthcare
  • Higher Education

Cost

You can download any version of Apache HBase from its website.

Ratings 

The tool is rated 4.2 out of 5 stars on G2 Crowd

#18 Apache Hive

Apache Hive provides data query and analysis support for software built or integrated on Apache Hadoop through an SQL-like interface.

reporting tool_hive

Features 

Below are the features of Apache Hive:

  • Supports analysis of large datasets.
  • Provides indexes to speed up queries.
  • Compatible with Amazon S3, Alluxio, and other file systems.
  • Supports different storage types such as plain text, ORC, and HBase.

Markets Supported

More than four thousand companies worldwide are using Apache Hive. These companies belong to the following industries:

  • Computer Software
  • Information Technology 
  • Staffing and Recruiting
  • Financial Services
  • Hospital and Health Care
  • Insurance
  • Higher Education

Cost

Apache Hive is free to use under Apache License 2.0.

Ratings 

Hive is rated 4.2 stars on G2 Crowd.

#19 Apache Kafka

At its core, Apache Kafka is a distributed streaming platform used primarily for building real time streaming data pipelines and streaming applications. With Kafka, you can publish, subscribe to, store, and process streams of records in real time.

reporting tool_kafka

Apache Kafka can be used in messaging, website activity tracking, log aggregation, metrics, stream processing, and a whole lot of use cases. 

Features

Apache Kafka is scalable, reliable, durable and stable. Aside from these, the other features of Kafka are:

  • Event replication
  • High speed
  • Guarantees zero downtime 
  • Guarantees zero loss of data
  • Has high throughput
  • Can handle failures 
  • Can handle high volume of data streams

Markets Supported

Apache Kafka is used in several industries including Computer Software, Information Technology, Human Resource, Financial Services, Management Consulting, Hospital and Health Care, Higher Education, and the Internet.

A few of the most notable companies that use it are JPMorgan Chase, Uber Technologies, HP Enterprise Company, and Walker Digital Table Systems.

Cost

No pricing is available for Apache Kafka, but it is open source and the code can be downloaded for free. There are also paid distros available.

Ratings 

Kafka is rated 4.3 out of 5 on G2 Crowd

#20 Apache Storm

Apache Storm is a distributed real time computation system which is available for free as it’s open source. With Apache Storm, you can process huge amount of data streams reliably. Among the use cases of Apache Storm are machine learning, real time analytics, and distributed RPC.

reporting tool_storm

Features

The advantage when using Apache Storm is that it is compatible with any programming language so it’s very simple and easy to use. Storm also integrates seamlessly with any database and queueing system, and it is very fast. In fact, its speed is at more than a million tuples processed per second per node.

Apache Storm is also scalable and fault-tolerant. You don’t have to worry about it skipping some data at it guarantees that all of your data will be processed.

Markets Supported

Apache Storm is widely used in several industries including Computer Software, Information Technology, Staffing and Recruitment, Education, Financial Services, and Health Care.

Twitter, Baidu, Wayfair, and Alibaba are just some popular companies that use the computation software.

Cost

Apache Storm is an open source and free application.

Ratings 

12 respondents have rated Apache storm with 3.8 stars on G2 Crowd.

#21 Apache Pig

Apache Pig s a platform that allows users to analyze large data sets. More than this, Apache Pig also has an infrastructure that evaluates data analysis programs with a compiler that produces sequences of MapReduce programs. 

reporting tool_pig

Features

Apache Pig expresses three main properties or features on their website, and these are:

  • Ease of programming: The main language that Apache Pig uses is Pig Latin, which is SQL-like so it’s familiar.
  • Optimization opportunities: Task execution are optimized automatically, so developers only need to focus on the language’s semantics.
  • Extensibility: Users can create their own functions that can read, process, and write data.

The best thing about Apache Pig is that it can analyze all kinds of data, whether they are structured or unstructured. 

Markets Supported

Apache Pig is used by Hortonworks Inc., Comscore Inc., SalesHandy, The MITRE Corporation, and other companies in the following industries:

  • Computer Software
  • Information Technology
  • Financial Services
  • Education
  • Human Resource
  • Telecommunication
  • Insurance
  • Hospital and Health Care
  • Retail

Cost

Apache Pig is an open source project under the Apache Software Foundation and developers are encouraged to contribute their expertise voluntarily.

Ratings 

The tool has a 3.9 star rating on G2 Crowd, based on the reviews from 17 respondents.

#22 Apache Mesos

Apache Mesos isa cluster manager that is able to handle different workloads in a distributed environment by using dynamic resource sharing and isolation. It uses the same principles as

the Linux Kernel but Apache Mesos runs on every machine and provides applications with API’s for resource management and scheduling, both in physical or virtual environments. 

reporting tool_mesos

Features

The features of Apache Mesos include the following:

  • Linear scalability
  • High availability
  • Native support for containers
  • Isolation support for CPU, disk, ports, GPU, and memory.
  • Two-level scheduling
  • HTTP APIs 
  • Built-in web user interface
  • Runs on Linux, OSX, and Windows

Markets Supported

Top companies using Mesos include HubSpot Inc., Twitter Inc., ISHI SYSTEMS INC., and Mesosphere, and many others. These companies belong to the Computer Software, Information Technology, Human Resource, Financial Services, Internet, Computer Hardware, Retail, Higher Education, and Telecommunications industries. There are some government agencies that use the tool too.

 Cost

The Mesos is open source and downloadable for free from their website.

Ratings 

Apache Mesos has a 4-star rating on G2 Crowd, coming from 16  review respondents.

#23 Apache Mahout

The goal of the Apache Software Foundation when they developed Apache Mahout is to provide a free implementation of distributed machine learning algorithms related to data clustering, classification and collaborative filtering.

reporting tool_mahout

Aside from this, Mahout also contains Java libraries for linear algebra and statistics. Most implementations use the Apache Hadoop platform although there are still algorithms that are not yet implemented.      

Features

The notable features of Mahout are as follows:

  • Since Mahout works on top of Apache Hadoop, it is able to scale efficiently even in the cloud. It also works perfectly well in different distributed environment.
  • Mahout allows for the fast and effective analysis of large datasets.
  • The developer already has a built-in framework for his or her large scale data mining tasks.
  • Mahout has k-means, Dirichlet, Canopy, fuzzy, and other MaReduce-enabled clustering implementations.
  • Mahout also has built-in matrices and libraries.

Markets Supported

Facebook, LinkedIn, Rang Technologies, Twitter, LucidWorks, Yahoo, and Foursquare are just somke of the companies that use Apache Mahout. Most companies that use Mahout belong in different industries such as the Computer Software and Computer Hardware industries, Human Resources, Financial Services, Health Care, and Management Consulting industries.

 Cost

Apache Mahout is free to use under the Apache License 2.0.

Ratings 

The tool received a 4.3 star rating on G2 Crowd, based on 11 respondents. 

#24 RapidMiner

RapidMiner is an end-to-end data science platform that allows collaboration and transparency in machine learning. It is formerly known as YALE or Yet Another Learning Environment. The software provides a holistic environment for data  scientists, ranging from data preparation, machine learning, deep learning, and predictive analysis.

reporting tool_rapidminer

Features 

The features of RapidMiner are rooted into three aspects that promote full transparency and governace for machine learning. These are:

    • Easy to trust: Its unified platform provides transparency from data lineage and transformation, model selection and validation, up to deployment and optimization.

 

  • Easy to tune: It has more than 1500 visual building bloc algorithms for machine learning that data scientists and developers can easily access and modify.
  • Easy to Explain: The RapidMiner platform is automated and it enables users to create visual analytics and workflows.

 

Markets Supported

Industries that use RapidMiner are the following:

  • Computer Software
  • Higher Education
  • IT and Services
  • Staffing and Recruiting
  • Hospital and Health Care
  • Financial Services
  • Management Consulting
  • Telecom
  • Marketing and Advertising

Cost

RapidMiner has five different pricing plans, and these are:

  • RapidMiner Studio which is a visual workflow designer. It is priced at $5,000 to $10,000 per user, per year.
  • RapidMiner Server (On-Premise) allows organizations to share and re-use predictive models, automate processes, and deploy models on premise. The annual plan price starts at $36,000.
  • RapidMiner Server (Cloud) provides a pre configured server environment on Microsoft Azure or AWS. Price starts at $7 per hour.
  • RapidMiner Real Time Scoring is an add-on to the RapindMiner Server, at $36,000 per year.
  • RapidMiner Radoop is an alternative to Hadoop and Spark which is priced at $5,000 per user, per year.

RapidMiner offers discounts for students and nonprofit organizations, and they also offer free trial of their core program.

Ratings 

RapidMiner has a 4.5 star rating both on G2 Crowd and Capterra, based on 320 and 16 respondents, respectively. 

#25 DataRobot

DataRobot is an automated Artificial Intelligence platform suitable for data scientists of all skill levels. The tool is also targeted for business analysts, business executives, software engineers, and IT professionals and it aims to make machine learning as simple as possible.

reporting tool_datarobot

DataRobot enables users to build and deploy predictive models in a fast and accurate method by automating most of the tasks. 

Features 

DataRobot stands out with its self-healing, distributed architecture, large ecosystem of algorithms, and wide array of visualization tools. Aside from these, DataRobot has the following features:

  • Hadoop cluster plug and play
  • Enterprise security integrations
  • Easy to use
  • High speed
  • Distributed architecture
  • Data accuracy
  • Data preparation

Markets Supported

Several industries use DataRobot in their machine learning and artificial intelligence processes. Here are some of these industries:

  • Banking
  • Health Care
  • Insurance
  • Finance Technology
  • Manufacturing
  • Retail
  • Marketing
  • Government
  • Sports

Cost

DataRobot has not released their pricing packages, but you can contact them to get a quote or schedule a demo,

Ratings 

DataRobot has a 5-star rating on Capterra and a 4.4 star on G2 Crowd.

#26 Qubole

Qubole is a self-service big data platform specifically for machine learning, data analytics and artificial intelligence. It’s built on Amazon, Google, Microsoft and Oracle Clouds by the team that also founded Apache Hive.

reporting tool_qubole

Features

With Qubole, data scientists can process large clusters of data on any public cloud and create queries within less than five minutes. It is built for anyone who uses data, and is therefore simplified. There are several ways to access data, including web interface, Notebooks, APIs, or even third party business intelligence tools. 

Qubole is optimized for the cloud, and it serves as a single platform for ETL and reporting, stream processing, machine learning, and other uses cases. You don’t need different platforms for different use cases. 

The tool runs on Microsoft Azure, AWS, and Oracle Cloud infrastructure so you can enjoy the scalability and elasticity of the Cloud. 

Markets Supported

Industries where Qubole is used in are as follows:

  • Technical
  • Business Services
  • Financial Services
  • Media and Internet
  • Retail
  • Telecommunication
  • Healthcare
  • Entertainment
  • Consumer Services

Cost

Qubole only has one pricing plan which is the Qubole Data Platform – Enterprise Edition which is priced at $0.14 per QCU (Qubole Compute Unit) per hour. The package includes premium support, and an adaptive serverless architecture.

You also have the option to try Qubole for free with any of these options:

  • Free Test Drive: Includes a test-featured environment for one user, up to two weeks. A sample data set is also provided.
  • Free Full-Featured Trial: You have to use your own cloud data infrastructure account and provide your own data with this plan. However, you can enjoy all Qubole features and up to five people can use the tool for one month and up to 5,000 QCU only.

Ratings 

Qubole has a 5-star rating on Capterra and a 4-star rating on G2 Crowd, based on a total of 234 reviews. 

#27 Paxata

Paxata is a self-service data preparation application and machine learning platform. It aims to remove the hardship involved in turning raw data into structured and useful information. As such, Paxata decreases the effort and time spent in data preparation, from gathering, exploring, up to cleaning and shaping. 

reporting tool_paxata

Features

Paxata’s features include the following:

  • Integration: Paxata can integrate with other BI tools. SSO and API integrations are also available.
  • Support: Paxata offers tutorials, online training, and on-site training classes.
  • Intelligent Automation
  • Intelligent Ingest
  • Rapid Data Profiling
  • Intelligent Join Detection
  • Auto-Governance & Embedded Catalog
  • VPN to Connect to On Premises Data

Markets Supported

A wide range of industries use Paxata, and below are some of them:

  • Financial Services
  • Retail
  • Pharmaceutical
  • Public Sector
  • Technology
  • Healthcare

Cost

Paxata offers a free trial of their software for 14 days. This free trial includes 500 thousand rows, and other basic features. Below are Paxata’s paid packages:

  • Paxata Professional: With a minimum of one million rows and up to five data sources, the price for this plan starts at $360 per month. The price goes up depending on the number of rows or gigabytes to process.
  • Paxata Enterprise: For this plan, users can get data from an unlimited number of sources, and any number of users are allowed. Processing capacity also starts at one million rows. You have to contact Paxata to get a quote.

 

Ratings 

Paxata has 7.7 ratings on Predictive Analysis Today. There are no ratings available for Paxata on Capterra and G2 Crowd.

#28 Trifacta

Trifacta is a platform that speeds up data wrangling, which is the process of transforming raw data into useful and meaningful output. It can be used on any cloud platform including AWS, Microsoft Azure, Snowflake, and Google Cloud.

reporting tool_trifacta

Features

Trifacta has these features:

  • Connectivity framework
  • Innovation-friendly
  • Interactive exploration
  • Predictive transformation
  • Intelligent execution
  • Collaborative data governance

Markets Supported

Trifacta is being used in different industries including Technical, Finance, Business Services, Manufacturing, Retail, Insurance, Hospital and Health Care, Education, Telecommunication, and Transportation. 

A few companies that use Trifacta are JPMorgan Chase, Bank of America, Advantage, IQVIA, and Mattel.

Cost

Trifacta has three pricing plans: Trifacta Wrangler, Trifacta Wrangler Pro, Trifacta Wrangler Enterprise. The first package is free with 100MB and core wrangling only. The Pro plan, on the other hand, starts at $419 per month, per user. It includes all the basic features.

The Enterprise package includes all features, including onsite training, and you have to contact them to get a quote.

Ratings 

Trifacta has a 4.5 star rating on G2 Crowd.

#29 Redis

Redis is an open source data structure storage that is used as a database cache and message broker. It can support different data structures including hashes, strings, lists, sets, bitmaps, and indexes.

reporting tool_redis

Features

The features of Redis include the following:

  • Reliable and large storage
  • Stable
  • Scalable
  • Secure
  • Allows data manipulation

Markets Supported

Redis is used by companies that belong to the Technical,Business Services, Finance, Media & Internet, Manufacturing, Retail, Telecommunications, Education, Entertainment, and Healthcare.

Cost

Redis is free to use under the BSD license.

Ratings 

Redis is rated 4.4 on G2 Crowd with 76 respondents; and 5 stars on Capterra with 39 respondents.

#30 Lumen Data

Lumen Data is an information management platform that takes a phased approach through their MDM-specific methodology. The company provides products as well as consulting services for:

  • Predictive analysis
  • Data Strategy
  • Data governance
  • Data quality
  • Data migration
  • Data integration

reporting tool_lumendata

Features

The key features of Lumen Data are:

  • Enterprise data management expertise
  • Data governance and data quality
  • Pre-built integrations
  • Cloud expertise

Markets Supported

Among the industries that use Lumen Data’s products and services are the Financial Services sector, Manufacturing, Education, Life Sciences, Retail, and Telecommunications.

Cost

Lumen Data’s pricing is quote-based so you need to get in touch with them. 

Ratings 

There are no reviews on both Capterra and G2 Crowd.

#31 Excel

Excel is the traditional way of reporting, although it’s very limited. While there have been independent tools that popped up over the years, there are also tons of tools that have been developed to work with Excel. 

Here are some tools that you can integrate into Excel:

#32 Domo

Domo helps you turn Excel into a powerful and visual analytics platform. It allows you to collaborate with other team members in real time too. 

reporting tool_domo

#33 XLCubed

XLCubed uses Excel’s presentation format and calculation engine but it also turns Excel into a database where companies can connect Excel directly to their data. It gives users more flexibility than the simple and plain Excel.

reporting tool_xlcubed

#34 InetSoft

Finally, there’s InetSoft’ Style Intelligence that can transform Excel into a Business INtelligence reporting tool. It makes Excel more flexible as it improves data exploration and allows you to collate data not only from Excel but also from Google Adwords and Analytics, Salesforce, and other databases. 

reporting tool_inetsoft

#35 MLBase

MLBase is a Julia package that provides different tools for machine learning. It is a very helpful library for data scientists and developers when they are writing their own machine learning codes.

reporting tool_mlbase

MLBase is part of the Berkeley Data Analytics Stack (BDAS), together with Apache Spark. The tool has three components namely:

  • ML Optimizer  which automates the Machine Learning pipeline construction.
  • MLI which is an API that develops algorithms. It also extracts features for high-level computations.
  • MLlib is Apache Sparks’ machine learning library and is also used by MLBase.

Features

Because of the three components briefly discussed above, MLBase is capable of these features:

  • Ability to test data on different learning algorithms and learn which model is the most appropriate in terms of accuracy.
  • Has a simple and intuitive GUI for machine learning development and coding.
  • Scalable and able to process huge data sets effectively.

Markets Supported

Like Apache Spark, MLBase is used in a wide range of industries such as Computer Software, IT and IT Services, Staffing and Recruiting, Higher Education, Financial Services, Hospital and Health Care, and Management Consulting.

Cost

MLBase is open source and no information is available as to whether it is being distributed commercially.

Ratings 

MLBase has a 4-star rating on G2 Crowd

#36 Microsoft Azure ML Studio

Microsoft Azure Machine Learning Studio allows for a collaborative and visual  machine learning environment where users can easily build, test, and iterate their predictive analysis model with no programming required.

reporting tool_azure

Users can simply drag-and-drop datasets and analysis modules to the Azure ML canvas. These datasets and modules are connected to form an experiment which is run in the Machine Learning Studio.

If you want to iterate on the model design, just edit the experiment and run it again. The training experiment can be converted into a predictive experiment which can be published as a web service accessible by other people.

Features

The strongest feature of the tool is its drag-and-drop functionality in building experiments. This requires no programming skills at all, so even new data scientists and non-developers can use the tool. Other features of Microsoft Azure ML Studio are:

  • Ability to process large datasets and solve large data projects.
  • No limit on the data to be imported.
  • Simple and easy to use tool with functionalities that are not restrictive.
  • Ability to publish experiments as a web service.
  • Experiments can be accomplished within a few minutes.
  • Your data is protected by Azure security measures.
  • Algorithms are fast, enabling you to get real time predictions.

Markets Supported

Top companies that use Azure Machine Learning Studio include Nigel Frank International Ltd, MAQ LLC, KiZan Technologies, and of course, Microsoft Corporation, among others. Most of the companies belong to these industries:

  • Computer Software
  • Information Technology
  • Human Resources
  • Management Consulting
  • Financial Services
  • Education
  • Computer Hardware

Cost

Azure Machine Learning Studio can be used for free, with the following limitations:

  • Maximum number of modules per experiment is 100.
  • Maximum duration of experiments is set at 1 hour.
  • Maximum storage space allowed is 10 GB.
  • Only a single node is allowed 
  • No production web API.

The Standard plan, on the other hand, allows an unlimited number of modules and storage space, multiple nodes, and experiments can run for up to seven days. The price is $9.99 per ML studio workspace, per month and $1 per hour for studio experimentation. 

The Standard plan includes the ability to deploy your experiments as a web service, but this is subject to additional cost that starts at $100.13 up to $9,999.98.

Ratings 

Azure Machine Learning Studio has a 4.4 and 4.5 star rating on G2 Crowd and Capterra, respectively, with 928 total reviews.

#37 MLJAR

MLJAR  is a machine learning platform for developing, prototyping, and deploying pattern recognition algorithms. It aims to learn different models for each algorithm as it processes the data, so it’s relatively slower than other machine learning platforms.

reporting tool_mljar

Features

MLJAR ’s features include one interface for multiple algorithms, built in hyperparameters search, smart defaults for parameters, cloud access using their REST API, and the ability to compute predictions within the user interface.

Markets Supported

Companies that use MLJAR belong to different industries such as Computer Software and Computer Hardware, Human Resources, Financial Services, Education, and Information Technology

Cost

MLJAR has a free tier where you are allowed one machine,30 days of project history, and a dataset limit of 0.25 GB. Their paid tiers with unlimited project history and the ability to compute on MLJAR cloud are as follows:

  • Professional: $199 a month for 4 machines, dataset limit of 1 GB, and unlimited project history.
  • Startup: $499 a month for 8 machines and 2 GB dataset limit.
  • Business: $999 a month, for 12 machines and dataset limit of 4 GB.
  • Organization: The price is not disclosed for this plan, but it includes an unlimited number of machines and a dataset limit of 32 GB. 

Ratings 

MLJAR has no available rating on G2 Crowd and Capterra.

#38 Amazon Lex

Amazon Lex is a platform that enables users to build conversational interfaces into any application using text and voice. With deep learning functionalities involved in ASR (automatic speech recognition) and NLU (natural language understanding), you are able to convert speech to text, know the intent of the text, so you can develop applications that has a high level of user engagement with conversational interactions that are lifelike.

reporting tool_lex

Amazon Lex is built with the same deep learning technologies that Amazon built Alexa, so any person can now develop conversational bots.

Features

Amazon Lex’s most attractive features are:

  • It is easy to use.
  • Built in integration with AWS
  • Seamless deployment and scalability
  • Cost effective

Markets Supported

The companies that use Amazon Lex are Liberty Mutual, KloudGin, RedAwning, Dynatrace, Rubrik, Astro, Infor Coleman, BuildFax, Kelley Blue Book, NASA, and American Heart Association, among others. 

These companies belong to a wide range of industries, including Insurance, Automobile, Computer Software, Telecommunications, and the Public Sector. 

Cost

Like other AWS services, Amazon Lex is priced on a per-use basis, and the rates are as follows:

  • $0.004 for each voice request
  • $0.00075 for each text request

Ratings 

Amazon Lex is rated 4.3 stars on G2 Crowd, based on 29 respondents.

#39 IBM Watson Studio

IBM Watson Studio is a collaborative environment for cleansing and shaping data, analyzing and visualizing data, and creating machine learning models. The platform speeds up data science operations across several phases

reporting tool_watson studio

Features

IBM lists these functionalities of IBM Watson Studio:

  • Bring algorithms to where data resides
  • Increase productivity across your data science team
  • Operationalize the data science lifecycle
  • Deploy in hybrid, multicloud environments
  • Available on IBM Cloud™ Pak for Data

Markets Supported

According to Enlyft, IBM Watson Studio has 25% of the market share for machine learning. The top industries that use Watson Studio are Computer Software, Hospital and Health Care, Information Technology and Services, Higher Education, Staffing and Recruiting, and Financial Services. 

Cost

IBM Watson Studio is available in three variations:

  • Watson Studio Cloud: This enables you to prepare data in a fully managed IBM Cloud environment. Price starts at $99 a month for 50 capacity unit hours and $6,000 a month for 5,000 capacity unit hours.
  • Watson Studio Desktop: This tier is for individuals who want to perform data science operations on desktops that run on Mac or Windows. Price is at $199 a month per authorized user. A 30-day free trial is also available.
  • Watson Studio Local: Data science teams and enterprises can access visualization tools and open source data science tools behind their own firewall. Contact IBM for the pricing. 

Ratings 

IBM Watson Studio has a 4.1 star rating on G2 Crowd.

#40 Automatic Statistician

Automatic Statistician was developed with the goal of making it easier for anyone to turn raw data into useful information by making predictions, decisions, and interpretations based on it. Automatic Statistician is a system that produces possible statistical models to explain the data, and the output produced includes figures and natural language text.

reporting tool_statistician

The developers developed an early version of the tool which return a 15-page report that described the data pattern. At the same time, a statistical model was also returned. All these were made possible with the use of reasoning over open-ended language of nonparametric models utilizing Bayesian inference. 

Features

What sets Automatic Statistician apart from other tools is its ability to discover possible statistical models from data input and the ability to explain these discoveries in natural English language. This feature is apt for its name as it can turn anyone into a statistician with the report that the tool can generate.

Markets Supported

Automatic Statistician is used across a wide range of industries, including Retail, Ecommerce, Manufacturing, Advertising and Marketing, Health Care, Computer Software and Hardware, and Information Technology.

Cost

No pricing data is available for Automatic Statistician, but you can request for a demo.

Ratings 

No ratings are available on G2 Crowd and Capterra.

#41 PythonReports

PythonReports is a toolkit that enables users to build database reports in Python programs. It already provides report template designers, report builders, and printout renderers for GUI and graphic output.

reporting tool_pythonreports

Features

PythonReports is simple to use and it is already a comprehensive toolkit. Reports can be saved to file or rendered to a screen, PDF, printer, or any output. 

Markets Supported

PythonReports is used by companies running Python programs. 

Cost

PythonReports is free to use.

Ratings 

There are no ratings available for PythonReports.

#42 R

R is an extensible programming language and computing environment that offers a wide variety of statistical and graphical techniques. A few of the statistical techniques it provides are linear and nonlinear modelling, classical statistical tests, clustering, data analysis, and classification.

reporting tool_R

Features

With R, plots are well designed and of high quality. Formulae and mathematical symbols are also included. The R environment includes:

  • A suite of operators that make calculations possible,
  • A storage and data handling facility,
  • Graphical interfaces for data analysis which can be printed on hardcopy or shown on screen.
  • Simple and well-developed programming language.

Markets Supported

R programming is used in Banking, Social Media, Healthcare, E-commerce, and Finance. It is famously used by Facebook, Google, Ford Motor Company, Microsoft, Mozilla, New York Times, Twitter, and ANZ Bank. 

Cost

R is available in source code form as free software under the Free Software Foundation’s GNU General Public License. 

Ratings 

No rating is available.

#43 Apache Spark

Apache Spark is an inclusive analytics tool used primarily for large scale processing of data, ETL processing, machine learning, and graph computation. For this reason, several data scientists are using this tool. 

reporting tools_spark

Features 

Among the features of Apache Spark are:

  • Multi-language support
  • Speed
  • Advanced analytics
  • Real time data collection
  • Hadoop integration
  • Data distribution

The best thing about Apache Spark is its speed. The tool is able to reduce the number of read/write operations, enabling it to run applications up to 100 times faster on memory and 10 times faster on disk.

Markets Supported

Apache Spark is being used in the following industries:

  • Computer Software
  • IT and IT Services
  • Staffing and Recruiting
  • Higher Education
  • Financial Services
  • Hospital and Health Care
  • Management Consulting

Cost

Apache has not disclosed pricing for this product.

Ratings 

Apache Spark is rated 4 out of 5 stars in G2 Crowd, though the number of respondents were only 7.

#44 Anaconda

Anaconda is an AI enablement platform that allows data science teams to perform operations at scale. It is a free open source distribution of the R and Python programming languages whose goal is to make package management and deployment simple.

reporting tool_anaconda

Features

Anaconda is widely used by different companies and organizations because of these features:

  • Access more than 1500 Python and R packages and libraries securely.
  • Ability to create package policies that can blacklist/whitelist license types and versions.
  • Easy and quick sharing of notebooks.
  • Filter notebook access to individuals or groups.
  • Automated version control.
  • Connect to different data sources including Hadoop and Spark.
  • Share GPU clusters with other teams.

Markets Supported

Companies that use Anaconda belong to a wide range of industries. A few of these companies are Ford Motors Company, Bank of America, Walmart, Charles Schwab, and Experian. Top industries that use the platform are:

  • Technical
  • Education
  • Banking and Finance
  • Business Services
  • Manufacturing
  • Government
  • Healthcare
  • Retail

Cost

Anaconda is a free and open source distro.

Ratings 

There are no ratings for the tool on G2 Crowd and Capterra.

#45  Keras

Keras is a deep learning library that is written in Python and can run on top of TensorFlow, Theano, and CNTK.

reporting tool_keras

Features

Keras has the following functionalities:

  • Keras is a simple API developed for humans and not for machines.
  • It gives clear error messages that can easily be understood and acted upon by the user.
  • It reduces cognitive load and minimizes the number of actions required of the user.
  • Keras uses standalone modules that can be combined to create new models.
  • It’s easy to add new modules, making Keras extensible.

Markets Supported

Vanguard, Verizon, IBM, Tailwind, and Amgen are just a few companies that use Keras. Top industries that use the tool are Technology, Business Services, Education, Manufacturing, Finance, Healthcare, Retail, Media and Internet, and Telecommunications.

Cost

Keras is an open source software.

Ratings 

Keras is rated 4.5 stars on both G2 Crowd and Capterra, with reviews from 59 respondents.

#46 Feature Labs

Feature Labs develops APIs and tools that are helpful in data science and data analytics. It has three main products namely Feautetools, MLApps, and Tempo. 

reporting tool_featureslabs

Features

Featuretools uses a simple Python API so that developers can integrate Feature Labs’ automation technology. MLApps give business owners and data science teams access to prepackaged machine learning solution that includes fraud prediction, predict next purchase, anti-money laundering, credit scoring, and hospital readmission, and so many more.

Lastly, Tempo is for anyone who wants to build their own machine learning operations using Feature Labs’ automation tools.

Markets Supported

Feature Labs products can be used in different industries such as Banking and Finance, Healthcare, Information Technology, Insurance, Industrial, Retails, and Sales and Marketing.

Cost

Featuretools for individual users is priced at $50,000 a year, and $100,000 a year for the whole team. Custom pricing applies if you want to use Featuretools Enterprise.

The other two Feature Labs products are on a quote-based pricing. 

Ratings 

There are no ratings available for Feature Labs or any of its products. 

#47 RStudio

RStudio is an IDE or Integrated Development Environment developed for the R programming language. It is available in both open source and commercial editions and can run on desktops or through a web browser.

reporting tool_studio

Features

Some of the features highlighted on RStudion’s website are:

  • Syntax highlighting, code completion, and smart indentation
  • Execute R code directly from the source editor
  • Quickly jump to function definitions
  • Integrated R help and documentation
  • Easily manage multiple working directories using projects
  • Workspace browser and data viewer
  • Interactive debugger to diagnose and fix errors quickly
  • Extensive package development tools
  • Authoring with Sweave and R Markdown

Markets Supported

RStudio is used in the Computer Software, Retail, Manufacturing, Banking and Finance, and Insurance industries.

Cost

The open source edition of RStudio is of course, free of charge under the AGPL v3 license. The commercial edition, on the other hand, costs $4,975 for five users per year. This already includes access to all features, administrative tools, enhanced security and authentication, advanced resource management, and other functionalities not available in the open source edition.

Ratings 

RStudio is rated 4.5 stars in G2 Crowd, based on 469 reviews.

#48 GraphLab Create

GraphLab Create is primarily a Python library which aims to help data scientists and developers build scalable, high performance applications. 

reporting tool_graphlab

Features

Users have access to toolkits that make application development simple and effective. Developers can use the same codes both on desktops and in distributed environment. The API is also flexible, so developers can customize it based on the machine learning task.

Markets Supported

Industries that use GraphLab Create are Computer Software, Education, Information Technology, Internet, Hospital & Healthcare, and Financial Services. 

Cost

GraphLab is open source and they don’t have a commercial edition. Anyone can avail of their renewable one-year license for free. 

Ratings 

GraphLab Create is rated 5 stars in G2 Crowd

#49 KNIME Analytics Platform

KNIME Analytics Platform is an integrated and intuitive open source software for creating data science. With the software, it’s easier to understand data and perform data science operations. 

reporting tool_knime

Features

KNIME Analytics Platform highlights these features:

  • Intuitive, drag-and-drop interface that do not require coding.
  • Ability to blend tools from different domains with KNIME native nodes.
  • Over 2,000 native nodes to choose from.
  • There are already available workflows available.
  • Combine data from any source, whether simple text formats, unstructured data, or time series data.
  • Access and retrieve data from Twitter, Google Sheets, Azure, AWS, and other sources. 

Markets Supported

Companies and institutions that use KNIME Analytics Platform include Prairie View A & M University, Horizontal Integrations, University of Washington Medical Center, and NUWAVE Solutions.

Most of these companies belong to the following industries:

  • Computer Software
  • Education
  • Information Technology and Services
  • Hospital and Healthcare
  • Biotechnology
  • Financial Services

Cost

KNIME Analytics Platform is open source and can be downloaded for free.

Ratings 

KNIME is rate 4.3 and 4.5 stars on G2 Crowd and Capterra, respectively. 

#50 Logical Glue

Logical Glue focuses on “explainable, reliable, and interpretable” AI solutions. It’s a practical and intuitive platform for building and deploying predictive models, using over 25 technologies from different companies.

reporting tool_logical

Features

Because Logical Glue is powered by explainable artificial intelligence or XAI, data science operations are quick, transparent, and trustworthy. It aids businesses make logical, reliable and performance-driven decisions.

Markets Supported

Logical Glue is used in the Insurance and Lending industries, as well as in Automotive Manufacturing, Healthcare, Pharmaceutical, E-commerce, and Marketing. 

Cost

Get in touch with Logical Glue’s sales team to get a quote-based pricing.

Ratings 

There are no reviews and ratings available on G2 Crowd and Capterra.

#51 NumPy

NumPy is a package for scientific computing with Python, and it is also an efficient container of generic data. NumPy can integrate with no problem with different types of databases since arbitrary data types can be defined.

reporting tool_numpy

Features

Numpy cites these features on its website:

  • Powerful N-dimensional array object
  • Sophisticated (broadcasting) functions
  • Tools for integrating C/C++ and Fortran code
  • Useful linear algebra, Fourier transform, and random number capabilities

Markets Supported

Thousands of companies belonging to a wide variety of industries use NumPy. Here are some examples of thee industries:

  • Technical
  • Business Services
  • Education
  • Manufacturing
  • Finance
  • Healthcare
  • Retail
  • Media and Internet
  • Energy, Utilities, and Waste Management

Cost

NumPy is free with some provisions stipulated in their license.

Ratings 

NumPy is rated 4.6 stars on G2 Crowd.

#52 Octave

Octave is a free mathematics syntax that contains pre-built plotting and visualization tools.

The Octave syntax is compatible with Matlab and can run on GNU, macOS, Windows, and BSD.

reporting tool_octave

Features

Octave syntax enables users to solve equations involving linear algebra operations on vectors and matrices. On top of this, it also allows you to visualize your data in 2D or 3D using high-level commands.

Markets Supported

Since GNU Octave works with Matlab, several industries use the syntax. This includes Medical Devices, Computer Software, Civil Engineering, Higher Education, Aviation, and IT Services.

Cost

Octave is a free software licensed under the GNU General Public License (GPL). 

Ratings 

Octave is rated 4.2 on G2 Crowd, with 30 reviews.

#53 OpenRefine

As the tool’s tagline suggests, OpenRefine specializes in transforming messy and raw data into something useful. With OpenRefine, users can explore, clean, transform, reconcile, and match all data. OpenRefine is a desktop application and is formerly known as Google Refine. 

reporting tool_openrefine

Features

Notable features of OpenRefine that makes it a powerful yet simple database are:

  • Data facet
  • Data Clustering
  • Editing cells
  • Data matching and reconciliation
  • Web service
  • Data linking
  • Data export/import
  • Data exploration
  • Dataset linking
  • Data partition
  • Data format conversion

Markets Supported

OpenRefine is being used in several companies and industries since it has been around since 2010.

Cost

OpenRefine is a free and open source software.

Ratings 

OpenRefine has a 4.6-star rating on G2 Crowd.

#54 Pandas

Pandas is an open source library that offers easy to use data structures and powerful data analysis tools using the Python programming language. 

reporting tool_pandas

Features

Aside from being free and open source, Pandas make data wrangling easy and simply.  Files can be read easily by typing a simple command line. It can also manage any kind of data, and can sort a large number of data in a hierarchical way with no problem. Pandas is also a great visualization tool as it is based on Matplotlib. 

Markets Supported

Pandas is used in several industries including the following:

  • Technical
  • Business Services
  • Finance
  • Education
  • Manufacturing
  • Healthcare
  • Media and Internet
  • Retail
  • Energy, Utilities, and Waste Management

Cost

Pandas is free to use under the BSD license.

Ratings 

The tools is rated 4.5 stars on G2 Crowd, with 38 reviews. 

To Wrap Up

This has been an exhaustive and comprehensive list of reporting tools for data scientists that are effective in 2019. We will keep this list updated from time to time to make sure that every tool is still being distributed and that prices are up to date.

Most of the tools are commercially distributed so you would need to shell out your hard-earned money for them, so you have to make sure that the tools aren’t easily hacked or blocked by web-based applications you integrate them with. 

An important consideration is the security measures you put in place while using any of the tools listed above. Data scientists invest in proxy servers along with any automation tool they use to add an extra layer of protection. 

Limeproxies is the best security tool for data scientists because of our super elite, highly anonymous proxies. When you settle on one of the reporting tools above, why not try Limeproxies for free along with it. 

Contact us now to avail of the two-day free trial of our high-performance proxies.

Sources:

Capterra

G2 Crowd

Enlyft

About the author

Rachael Chapman

A Complete gamer and a Tech Geek. Brings out all her thoughts and love in writing blogs on IOT, software, technology etc

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