Ask a data expert how he/she prefers to spend time when free? The answer would be – reading through data science papers and journals. Yes, that’s the level of seriousness one expects to develop to build a career in Big Data and Analytics. However, intellectual curiosity is just a part of forging Big Data analytics career. There are at least 10 steps; you can call them building blocks that one needs to lay in this path.  

This article covers the basic, foundational steps that any professional should take as a big data analyst and scientist. 

Knowing the A-B-Cs of Data Science and Programming Industry  

The most interesting aspect of Big Data Analytics courses is the way they teach the basics data science and programming, including regression and decision tree modeling. Those straight from the grad school are best poised to undertake the grueling sessions in Big Data Analytics courses and succeed. Graduation program prepares the aspirant to spend quality time with the course material and physical programming classes.  

Knowing What Works, and What Doesn’t!  

If you can apply logical reasoning to complex problems, your job is straightened to a great degree. For example, your logic should be able to tell how many people would buy heels over sports shoes?  

If you can reason that out well, your code would do the rest -- including predicting the numbers and choices unknown population would make if they were to be offered more than two options!  

Sounds too complex to comprehend, right? Yes, that’s why you should enroll with Big Data Analytics courses. 

Setting up the Data Analyst Toolkit  

All professionals have their own go-to toolkits. It could also include a manual of past cases that tells you what to do and what not to do, if you face complex problem. Like plumbers have their own toolkits, a data analyst needs to build a toolkit too. 

So what does a tool kit for data analyst include?  

Here is a close look into the toolkit. 

- Introduction to programming languages, R, SQL, Python and Commands in R 

- Power BI Data and Analytics

- MS -Excel commands and functions

- SAS, Apache Spark

- Tableau Public

- RapidMiner

Big Data Analytics courses would take care of these toolkit components in the first six to eight months of training.  

Training in Industry Roles  

Big Data Analytics courses also teach professionals about their immediate and long-term job responsibilities once they enter the industry. While most traditional courses would set an IT job as their first target, high-level advanced Big Data Analytics courses train aspirants to learn the following— 

- Come up with disaster management plans and contingency plans in case of data loss, theft and corruption of data.  

- Design, conduct, analyze and report various aspects of survey and polls.

- Evaluate the records of data policies and processes, using automation and human intelligence

- Build man-machine interaction to monitor and audit data management processes

With the proper Big Data Analytics courses, you have every chance to make a great career in data science.