These 5 Skills Will Make You a Successful Data Analyst. Read to Know about.

By POOJA BISHT |Email | May 6, 2019 | 5883 Views

Data Science is a growing field and the demand for Data Scientists and Data Analysts are increasing with every coming day.  The rise of the Big Data could be accounted for the increased importance of Data Science today. While the jobs are lucrative in Data Science and are in large number, it is also a fact that many of the positions go vacant just because of the dearth of the right skills possessed by the candidates. Developing the right skills has become the necessity of the hour today for any learner developing a career in the field and it is required that candidates develop the right set of skills for the different positions in Data Science so that they get to their desired companies quickly. In this article, we will discuss the 7 skills that you require to become a Successful Data Analyst.  I have also been an enthusiast in the field and had explored many of the resources for the same during the starting of my career. Here, I have organized and presented these skills in a way so to provide you the best in brief. 

Here are my top 5 skills for a Successful Data Analyst:

  • Analytical Skills
Analytical skills are the key skills required in a Data Analyst role. You need to analyze a lot of Data to gather useful insights for the business. Analyzing and finding insights are the key responsibility of any Data Analyst so you need to develop the required Analytical skills for that. As an individual you can develop your analytical skills by asking questions, challenge situations, finding solutions to real life problems and be a more problem loving.

  • SQL
You need and must develop the knowledge of this database language i.e., SQL. As an analyst, you will do a majority of work using SQL. I have also written an article regarding the importance of SQL in Data Science which you must read.

You can read the complete article from here. 

SQL is helpful while handling big datasets, so a lot of companies, in fact, the majority of the companies still use SQL. So you must learn to work with SQL. Learning SQL is easy, so Kudos for that.

  • Knowledge of R
For visualizing big datasets and finding relevant patterns you will need a language which is helpful in Data Visualization. Most of the companies use R for it while some are more comfortable using SAS. If you are confused over what to learn and ask about my personal opinion I would suggest you learn R as most of the organizations today are shifting towards using R over SAS. R contains more statistical features as compared to SAS.

  • Presentation Skills
The role of a Data Analyst is not limited to finding insights but also presenting and explaining them before the different departments of the company and Stakeholders. So you need good presentation skills for that. Good presentation of all your insights using correct visualizing software like Tableau along with excellent communication skills will make your presentation appealing and understandable to your audience. So you get prepared that you are working and spending a good amount of your time learning the recent and the advanced visualization software along with the right set of communication skills for interacting with your colleagues. 

  • Passion to work and learn
This point may not be related to any of your technical skills but this is the soft skill that you will require in your entire Analyst career. You should have a passion to work with data. You should have a passion to work with challenging and unstructured data and the most important thing -"You should have a passion and desire to learn something new daily". Data Science is a growing field and also a changing field. The new automation software reshaping the industries, new technologies like cloud spreading all over the business demands you to be updated daily. Whether it is the new visualization software or the other programming language to learn, you should get yourself ready to be molded.

I am sure the above points will help you in successfully developing your career as a Data Analyst. All the Best!

Source: HOB