In this rapidly expanding digital world, new technologies and associated roles are appearing at a rate that education system is not able to revamp its syllabus parallelly. One such technology is Data Science and the associated role is Data Analyst.
Most of the computer-related graduation courses are currently not offering Data Analytics as a major subject. As a result, most of the Data Analysts have learned the skills themselves. It indicates that you can also become a Data Analyst with no prior experience.
Fasten the seatbelts, let us board the flight that will cover everything related to the data analytics, and it will help you in becoming a good Data Analyst with no prior experience by the end of this journey.
Data analytics is actually the art of analyzing a huge amount of data collected from any particular organization or group of organizations with an intention of pulling out conclusions that will enhance the productivity of the organization and will also enhance their decision making ability on quantitative as well as the qualitative basis.
Do not confuse data analytics and data analysis, both terms hold the same meaning and are often used interchangeably.
Nowadays almost every organization which deal with any sort of data have a huge amount of data that keeps increasing with the time, data analysis can be performed over these data to get useful insights from the pool of data. For carrying out this analysis work a highly skilled person is needed and this highly skilled person is known as the Data Analyst. They are also known as Data Scientist.
What is the actual work of Data Analyst?
Data Analyst uses a proper combination of mathematics, programming tools, software, and statistical methods to draw out insights from the bulky data sets provided to them. Insights provided by the Data Analyst helps companies to re-define their products and services according to their average customer needs. Not only in product enhancement but also their insights act as an aid to marketing strategy, as well as to effective production process.
Are you looking for the set of basic skills that are needed to become a good Data Analyst?
A good Data Analyst should have the following skills:
1. Mathematics: If you are someone who does not like Mathematics and calculations then you should drop the idea of becoming a good Data Analyst. You should know about an amazing relation between mathematics and data analysis before you drop the idea of becoming a good Data Analyst: The mathematics which you studied in your school and college days were usually not related to real-life problems and situations, there are great chances that you will start loving mathematics when you start dealing with the real situations.
The degree of mathematics you need to know to become a good Data Analyst has always been a confusing and highly debatable topic. One group of people thinks that a huge amount of mathematical skills are required and another group of people says that since most of the calculations have to be done by software then there is no use of much mathematical skills to become a good Data Analyst. It actually depends on many factors. There is no straightforward answer to this. it highly depends on how an organization is defining Data Analyst. Some organizations give a title of “Data Analyst” but make you work as a “Data Engineer”, whose actual work is much inclined towards software engineering which doesn’t require many mathematical skills. Not only this, some companies hire different sets of people one who is good at Maths and calculations and others who are good at coding and finally combine them in a team for better results. On the other hand, few organizations hire someone who possesses both the skills. These were the real source of confusion. We do not want to get into this debate. Let the data guide you, DataScienceWeekly has published a list of average mathematical skills you should be possessing in order to become a good Data Analyst:
- Linear algebra (and ideally basic multivariate calculus)
- Regression … linear regression and the things that violate the assumptions of linear models (e.g., autocorrelation in time series data, non-independent observations)
- Probability theory … especially Bayes’ Law and Central Limit Theorem
- Numerical analysis (e.g., time series analysis and forecasting)
- Core machine learning methods (clustering, decision trees, k-NN)
2. Programming: To become a good Data Analyst, you need to be an expert in at least one of the programming language. Though, it will be always a plus point if you are good in multiple programming languages that are commonly used in data analysis such as R, Python, C++, Java, MATLAB, PHP, etc. The capability to program helps Data Analyst in a number of ways. If there is some work that they need to perform for many times(very common case in the field of data analysis) on a daily basis, they can automate such works using scripts which will decrease the time consumption and hence will increase efficiency as well as the productivity. They can also write scripts that can transform data from one format to another which is another common task in data analysis.
3. Machine Learning: Machine learning is technology based on artificial intelligence (AI) that provides systems the intelligence to automatically learn and improve with time and experience. They are not explicitly programmed. Machine learning provides a kind of algorithm that allows software applications to become more accurate in foretelling results. Almost every small and big companies know that big data can take their company to another level, but sooner they have started realizing that big data analysis along with Machine learning is even more powerful. With an exceptional computational ability, machine learning is being effectively used in the field of data analysis. Machine learning can be used to make decisions and predictions based on data, and that is why it is very useful in data analysis..
Machine learning along with data analysis is actually helping companies in examining a large amount of data that are already very complex, to unveil cryptic patterns, expose market trends, and to get an understanding of customer taste regarding their product. When the process is automated and it is happening on a speed that manual human-based analysis can’t even think of competing, the result is extraordinary and positively surprising as well.
Let us go through a real-life scenario to understand the real application of machine learning in data analysis. E-commerce: In e-commerce, machine learning along with data analysis collect and analyze data in a dynamic environment and use the result to change the shopping environment in real time based on the behavior of the visitor on the website. It actually discovers similarities and differences in customer behavior on the website. The final result can be very interesting like visitors originating from a particular geographic location usually purchase a certain category of products, and use a particular payment method. In such cases, customers can be presented with similar products recommendations with some discount coupons depending on the company policies.
4. Statistics: If you are good at programming, mathematical, and software skills, but at the same time you do not have proper knowledge of statistics then you are lacking one of the unavoidable skill set that is required to become a Data Analyst.
If you are not good at statistics then you can give a kind of results to the stakeholders using which they may have to face a huge loss and related consequences. All good Data Analyst has a different set of skills and they work with different technologies, but one skill that keeps them under one roof is a deep understanding of statistics. So start learning statistics if you really want to work in the field of data analysis as a Data Analyst.
5. Microsoft Excel: Before performing any sort of data analysis organizing data in a systematic way and performing calculations are two of the main tasks of Data Analysts, which indicates that you should be very good at using Excel. Excel itself is very powerful, all you need is to learn how to use Excel efficiently. You will get many online guides for using Excel to its full potential.
6. Good Communication skills: Being a Data Analyst you will have to communicate with stakeholders, decision-makers, fellow Data Analysts and software engineers for collecting and sharing information and results inside the channel as well as outside the channel. Sometimes you will have to do one on one with the end clients to understand their actual requirement and also a great communication skill is needed when there is a change in plan. A good communication skill is required in all the above scenarios. Because if you are not able to communicate well, you will not be able to understand their requirement and unfortunately you won’t be able to give them the required results. All your efforts will be wasted if you are not able to present your point correctly to them. So, you need to start working on your communication skill if you are not very good at it.
Try learning new tools once you are content with ones you are already using. Not every tool work for every problem, different tools can be good for solving different types of problems.
Data analysts have a great career option in almost every sectors which deal with data. It is actually an endless journey to turn data into meaningful conclusions which can be used to improve the product as well as service. Data Analysts are the experts who can serve this purpose. They are the people who actually know connecting random dots into a particular pattern. Hence, the increasing need for data analysis is continuously creating a huge career opportunity for the Data Analysts.
Below are some sectors where Data Analysts are in huge demand:
1. Sales:- An enormous amount of data occurring from product sales in a company is analyzed, the result obtained after analyzing the data is used to increase product sales as well as customer satisfaction (which is directly responsible for the increasing sales). Data analysis also helps in recognizing the factors which are seriously acting as a hindrance to expected sales. So, there is always a need for Data Analyst in this sector.
2. Market Research:- Data analysis is heavily being used by companies for doing market research before launching a new product or service to get an idea if their product or service is going to be liked by the common or the targeted people depending on the product and target audience or not. In case if they get to know that their upcoming product is not going to be used by people they will drop the idea and will switch to another product that will be liked by their target audience based on the analysis report. This will save their money which was about to get wasted. So, there is always a need for Data Analyst in the product based companies for market research.
3. Healthcare:- Data analysis is playing a great role in the healthcare industry. By performing data analysis on the several patient’s data, we are getting results that are miraculous, based on deep data analysis reports doctors are able to suggest what can be done to treat the patient in the best way under given circumstances.
It is intensifying the diagnostic process, diminishing the possibility of misdiagnosis. Not only in treatment, but data analysis is also helping in creating better medicines. Health care industry will always need Data Analysts as saving and serving life is always been humans first priority.
4. Government :- Government is also making use of data analysis to know what exactly common people needs and also what should be done to serve the people in the best possible way. The outcomes are also improving resource allocation to those who actually need help.
5. Telecommunication:- Telecommunication is growing at a great speed, and the reason behind this tremendous development is the increasing availability of new wireless technologies. Telecommunication is no more a term that is just linked to the tools we use to contact each other, but to virtually every item we are interacting with and are going to interact with the introduction of ‘Internet of Things.’ Data analysts are building the tools and algorithms that will be used to gain a fuller understanding of how people interact with such tools, and how to improve services. This sector still requires a huge workforce.
Guide to become a Data Analyst with no Experience:
The minimum degree you need to have to become a Data Analyst for most of the entry-level Data Analyst positions is a Bachelor’s degree. The eligible streams are Economics, Finance, Mathematics, Statistics, Information Management, and Computer Science.
The best part about Data Analyst job position is that you can get into it, even if you don’t have any former work experience as a Data Analyst. Luckily, because of an immense need for Data Analysts, there are many data analysis internship opportunities. You can exploit such opportunities by working as an intern, it will help you in gaining some work experience in data analysis field and it will also give you an extra edge among other in a job interview for freshers.
The probability of being selected for an entry-level Data analyst position at a company depends on two major factors: your former education and how you are going to present your data analysis related skills.
You are in a better position and most probably you can get a position as Data Analyst if you have many interesting data analysis projects displayed in your resume, or if you have a degree in a heavily connected discipline such as mathematics, computer science, economics, statistics, or general disciplines such as humanities, social sciences, or if you have done a data analysis related course.
Let us make it more clear to you with a scenario: suppose there are two individuals John and Tony. John is a self-taught person with very good data analysis skills. But he has gaps in his academics. In this case of John, he will have to showcase his skills as much as possible to overshadow his educational drawback in front of interviewers. On the other hand, Tony has a relevant degree in the field of computer science. In this case of Tony, he will not have to present many skills to interviewers.
Some companies claim that they won’t hire any candidate without a proper relevant degree. But it is suggested that you should always appear in such interviews too if you are having good skills which can force them to re-think about their hiring policy.
Few tips that will help you in starting your career as a Data Analyst without prior experience:
It is always suggested to make a portfolio which shows an inclination towards data analysis in form of interesting project that you can demonstrate in length in a confident systematic way. Avoid including mini projects that you’ve never really done or is partially completed.
As discussed above, having a sound resume that shows a relevant degree and indicates that you have the potential to work in the field of data analysis always help. You can also include ongoing courses if you are doing one related to data analysis.
Interviewers usually give more importance to your problem-solving approach than the right answer. So, it has always been a better strategy to solve top 20 data analysis questions available online before you go for an interview. It will help you in improving your logic and will also help in polishing your problem-solving approach.
Keep reading about data analysis through various blogs and communities.
There are several company forums, meet, and conferences which you can attend to develop more understanding of data analysis.
Internships have always been an awesome step to kick-start your career in the world of data analysis. Internships provide you a hint of the work related to data analysis under proper guidance with ample workload.
You need to be really very creative during the interview. There are chances that they might ask you to solve a data analysis problem during, the interview process. In such case do not forget to take a look around the interview room. If the interview room has a whiteboard or other stuff, make use of them to communicate your ideas among the interviewers, normally they won’t mind, but to be on the safer side you can ask for permission to use them.
A very important pre-interview homework that we often forget is to research the company. An interviewer may ask you to tell him about your perception towards the company and what do you know about the company and the current technologies or the projects the company is working on.
Asking questions in an interview where things are not very clear is always a good approach. There are times when questions are kept obscure. It is to test how do you deal with a vague situation. At the end of the interview, ask questions which can help you understand the position better and most of the times you will end up impressing the interviewer.
For non-experience personnel, there are certification courses organized by SAS training institute, Jigsaw Academy (Online), and many other good institutes. Getting certified by doing these certification courses can drastically increase the likelihoods of getting a job as a Data Analyst in some of the best companies.
At the end..
In this article, we walked you through the journey of becoming a good Data Analyst without any prior experience, or it will be better to say that we started from scratch. We discussed what actually is data analysis, who is a Data Analyst, in what ways different companies hold different meaning and has different work for a Data Analyst. We also went through the average skills every candidate should have if he or she wants to become a good Data Analyst. We also covered interview preparation tips and general tricks to crack Data Analyst interview. Now it’s up to you, just follow the proper guidelines keep practicing and enter into the big evolving world of data analysis.
It will be great if you want to share your journey to a successful Data Analyst. The comments section is always open for you. Your journey might help someone in becoming a good Data Analyst.
Should you have any queries related to Data Analyst role. Write to us in the comments section below.