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    4.8 out of 5 by 3278 learners
    14 X industry demand

Every business grows gradually, even the biggest of them. Nobody ever heard of a business tycoon saying it has been a cakewalk reaching where they are. But how do they begin with their idea altogether, given the competitors, profit margins, break-even analysis, etc. involved? The answer is ‘data analysis’. Most of us consider data analysis as a career niche but the truth is it is the backbone of every project, whether big or small. Only a thorough research & analysis of such data can lead to successful business plan or any kind of product/service upgradation at hand.
Also Read: How to Differentiate Between Data Analysts and Data Scientists?
Many of us are great with number crunching and have totally been in love with numbers back in school. For most of them, becoming a Data Analyst can be as much a passion as singing or writing for others. But a lot of us are unaware of the skills that are inevitable to be a successful data analyst. So, let us take you through the basics skills for you to thrive as a data analyst.

Strong mathematical skills

The whole idea of analysing large volumes of data available through primary & secondary forms of research is to get absolute/approximate figures. If crunching down a data set with a huge sample size is not something that you find exciting, you aren't really going to like the role of a data analyst altogether.

Familiarity with MS-Office Suite

Gone are the days when it took days to plan the sales targets, market viability and the PPP (purchasing power parity) of your product/service. All thanks to Microsoft Office tools, precisely MS-Word, Excel & PowerPoint. Your grasp on the MS-Excel tool can be a real boon at work. There are many short & long term courses for MS-Excel & MS-Office respectively that are available these days. Do enroll yourself in one of them if you aren't aware of the huge functions that Excel has to offer you.

Strong Presentation Skills

Any analysis holds value if the desired information/statistics are presented in a meaningful way. As a data analyst, you are expected to come up with facts & inputs that help others make a decision. Therefore, it is crucial to be able to present your findings in a manner that others find easy to draw inferences. So be confident and perfectly knowledgeable about your area of research & it's very statistics.

Knowledge of Industry Tools

Data analysis is a vast subject. Data types vary from industry to industry, whereas analysis depends upon the specific project. Depending on the project, you might be expected to be well-versed in scripting, query and statistical language tools.A few prominent tools that are used these days are MATLAB, Python, SAS, SQL, Hive, etc. While MATLAB & Python are majorly Scripting languages, Hive & SQL are used for Querying, SAS & R are predominantly statistical languages in terms of modern-day technology.

Strong Communication Skills

A data analyst is presumably a meticulous, focused and the one with a hawk's eye for details. Let’s take an example here:
Sentence 1: The market share of ABC Pvt. Ltd. is 27.25%.
Sentence 2: The market share of ABC Pvt. Ltd. has been 27.25%.
Are you able to spot the fallacy here? If not, you need to be a lot more cautious of how you explain your analysis for others to base their strategies upon it.
Data analysis is one of the most robust functions of any organization and is equally vast as a subject altogether. In the current era of Big Data, Hadoop and many others, it is inevitable for an aspiring Data analyst to stay abreast of all the available technology updates in order to excel on the professional front.
Related Article: What is Data Analysis and Who Are Data Analysts?

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About Imarticus
Imarticus Learning is India’s leading professional education institute that offers training in Financial Services, Data Analytics & Technology. We’ve successfully transformed careers of over 35,000+ individuals globally through our Certification, Prodegree, and Post Graduate programs offered in association with leading and renowned global organisations in the Financial Services, Data Analytics & Technology domain.
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