5 Tips for Non-Programmers Learning Big Data Analytics

Learn Big Data Analytics- Programming is one of the essential skills required to become a data scientist. So does that mean that a non-programmer cannot become a big data analyst or a data scientist? The answer is a big “No.” Today, various open source tools are available that don’t require knowledge of programming and that can be easily used by big data analysts to analyse and explore data. Moreover, there are other important skills besides programming that non-programmers can develop in order to become an effective data analyst or data scientist.

Tips for Non-Programmers Learning Big Data Analytics

Tips for Non-Programmers Learning Big Data Analytics:

Here is a list of 5 tips for non-programmers learning Analytics:

  1. Excellent knowledge of Graphical User Interface (GUI) tools: If programming is not your cup of tea, you could look at acquiring knowledge of various simple and easy GUI tools that are widely available. For starters or beginners in big data analytics, you could explore the humble “Excel” and then move on to more complicated tools like Tableau, Datawrapper, Fusioo, Timeline JS, etc. The best part of these tools is that most of them are available free of charge. Furthermore, they allow you to analyse and present data with the help of charts, graphs, and other special graphics. Many big data certification programs offer training in these tools. You need to possess excellent visualisation abilities rather than programming abilities in order to effectively use these tools.
  2. Presentation skills: Although data can be analysed and mined with the help of expert data scientists who may or may not be excellent programmers, another equally important part of this process is communication of results to the stakeholders. For this, you require excellent oral and written communication skills in order to effectively communicate the results of the analysis to the target audience which includes programmers, non-programmers and lay people. Just as it is essential to twist and turn data (of course within ethical limits) in order to obtain worthy results, it is equally important to twist, turn and filter out irrelevant information in order to capture the attention of the target audience. Hence, it would be beneficial to develop this skill and include it in your bag of data analytical skills.
  3. Marketing skills: Once the analysis is done and you have communicated the results to the stakeholders, the next step is to use this information to market your product or services and reach out to a larger audience. This would require excellent persuasive skills, knowledge of latest trends and developments in marketing, etc. Hence, companies would prefer to hire someone with excellent big data analytical skills as well as marketing skills.
  4. Statistical and mathematical skills: Statistics and data analysis or big data analytics go hand in hand. If you possess a graduate or post graduate degree in Statistics/Mathematics, you definitely stand a good chance of becoming an effective and excellent data scientist. In case you do not hold a degree in these fields, you could also look at completing some certificate courses or online courses in Statistics/Mathematics that will give you an introduction to the subject and some basic skills. This could give you a head start as a non-programmer learning analytics. You could then look at more advanced programs if required. Although there are many programmers who can analyse data in a matter of seconds, the number of qualified mathematicians and statisticians is dwindling day by day. Consequently, their demand is increasing today.
  5. Hands on expertise in a specific field: Are you an expert in retail sales or do you have wide experience in the healthcare industry? Then, you have reason to cheer. You definitely possess more knowledge about the nuances, intricacies and tricks of the trade than any big data analyst or programmer. Such knowledge is highly valued by any big data analytics company. Hence, you can use your experience along with your data analytic skills and create magic.

Today, the mantra in most organizations is, “the more you know, the better.” Although specialized knowledge with respect to programming is highly appreciated, organizations are looking at hiring professionals with diverse skill sets. A big data analyst with excellent communication skills, marketing skills and statistical knowledge is definitely preferred over a data scientist with specialized programming skills. Hence, non-programmers learning analytics have reasons to rejoice and should look at developing the above-mentioned skills in order to excel in the world of big data analytics.

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