What are the Skills to Build a Good Career in Data Analytics?
Last updated on Tue 17 Mar 2020
If you wish to begin a career in Data Analytics, Here are the skills to build a good career in Data Analytics.
For those who consider that simply studying SAS or R or Python is going to be sufficient to get you a career in analytics/data science, then you might be wrong.
1. Analyzing and solving skills using data:
Analytics goes well beyond knowing tools like SAS, SPSS, and R and so on. The first and essential is understanding if you have problem-solving skills using data.
The basic essence of analytics is that you need to solve issues. Routinely the problems may really well-structured and all you must do is release your repository of tools and methods and reach a conclusion. However most times the problems will be indistinct and unstructured and will require big innovative thinking for your phase.
2. Domain or Business understanding:
The second sets of skills necessary are a domain or business understanding. On account that regularly you're going to be solving industry problems; you must understand the theme of that business or industry well and the important metrics in that industry or area. A skill to be able to pick up through expertise, curiosity, a hunger to learn extra and sitting with the industry guys.
3. Knowledge of Math and Statistical skills:
The third set of skills would be numerical and technical ones. You must be first-rate at math and stats, the applied sort and not the theory part only. Yes, the tools SAS, R, Python, SPSS, Hive, Pig, etc are primary however there may be much more to analytics than the tools. The tools don't mean much if you don't know what to do with them.
Since your job is analyzing data you need to know the tactics of analyzing data which are data instruction and cleansing techniques, statistical/predictive analytics methods and decoding the statistical output, machine learning techniques. More important is to know when and where to apply what technique. Learning all of this at one go just isn't vital. Since you are learning SAS, you should grasp it and also be trained R now along with Python.
These core tutorials that help you to be trained the basics of the Data Analytics platform.
For in-depth advantage and practical expertise explore online Data Science training.
4. Verbal & written communication:
Fourth skills would be verbal & written communication. You can be excellent at problem-solving and the technical stuff but if you are not able to communicate your analysis to the business guys you need the capability to visualize data by the way of creating interesting charts, tables, maps etc, inform reports, create presentations, have the tact and capacity to let the industry guys recognize their gut feeling used to be wrong and your data analysis was correct.
These are the skills need to develop in data analysis, if you are a beginner.