Data Analytics: Tools you must know in 2019

 

Are you a budding data analyst? The data analytics tools listed here can make a heck of a difference to you at the workplace. Some of them are absolutely critical – you wouldn’t be able to last a day in your job without them. Others are important, but not irreplaceable. Let’s take a quick look at all of them.

Data Analytics Tools You Must Know In 2019

1. Excel

Everyone knows about Microsoft Excel – the most popular spreadsheet application in the world. Excel has been around for more than 30 years now, but is still as important as ever. Excel is absolutely essential to a data analyst. You can perform all sorts of operations related to finance and statistics. Excel also supports VBA (Visual Basic for Application).

2. SAS

SAS is a software tool used by data analysts for tasks related to advanced analytics, business intelligence, predictive modeling and data management. You will need to master SAS in order to work with massive amount of data or perform statistical modeling.

3. R

One good alternative to SAS is R. R is a programming language as well as a software suite for performing tasks related to graphics and statistical computing. It is an open source tool, which means you can carry out any sort of experimentation with it. Also, R has a comprehensive support system around it. So, if you’re stuck anywhere, you can always depend on the massive R online community for help.

4. SQL

As a data analyst, you will work with massive databases. Which is why you should know SQL (or Structured Query Language), programming language that helps with database management. SQL is easy to master, as long as you are good at problem solving – which is a skill every data analyst should have. Knowledge of SQL is absolutely essential in this job.

5. Python

Python is one of the most popular programming languages right now. Anyone can master Python as it has only a few simple commands. But it is very fast, powerful, and has a massive library base for data analysis.

6. Apache Spark

Apache Spark is a fast and powerful data processing engine essential for working with Hadoop applications. It comes with a large library of machine algorithms that make your life easier as a data analyst. Spark can help automate regression, classification, clustering, filtering and other repetitive tasks and saves time and energy.

7. Splunk

Splunk is an essential tool that helps with the analysis of machine-generated data. It puts together all text-based log data, for example, and allows you to sift through it systematically. Splunk can prove to be absolutely important during statistical analysis.

So You Want To Apply For Data Analyst Jobs?

You will need to have the right skills for that. Start by joining the Data Analyst Skills Training (DAST) with Excel program at SKILLFIN LEARNING. You will learn critical skills in data analysis, synthesis, cleaning, visualization and manipulation in Excel. This online course in Excel for data analysts is designed for students, recent graduates and busy working professionals.

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