4 Analytics Tools You Should Learn In 2022

The new year is almost upon us and it is time to jot down some resolutions for 2022. 2020 has affected a lot of activities, one of them being formative education. Let us hope the new year will be better and more opportune. We must make sure that we are equipped. There has been a lot of noise about how great a career prospect is held by the field of data analytics. Well, some of that noise does make sense given the rapid digital transformation of businesses and investments made by all major industries in analytics. Since we are talking about new opportunities and being equipped with them, let us look at the data analytics tools you can learn come 2022.

Tableau

This is probably not the first tool you would have expected to be on this list. Well, it is. Tableau is primarily a tool for data visualization, arguably more suited for business intelligence and descriptive analysis than data analytics as we have come to understand it in the last few years. However, to be completely honest it is the descriptive part of analytics that most enterprises use on a daily basis. A midsize enterprise has to go to great lengths to integrate advanced predictive or prescriptive analytics powered by Neural Networks and artificial intelligence in general.

Tableau makes it easy for you to turn data into graphical representation. With inbuilt tables and charts, massive scalability, and compatibility with data from diverse sources, it is one of the most powerful visualization tools you can lay your hand on. More importantly it features interactive dashboards which makes the to and fro between the analyst and the executives much easier.

Python

You have probably considered learning Python from the moment you started eyeing a career in analytics. If you have not, you should. It is a simple and elegant language with libraries dedicated for data analysis. Python makes life easier for data analysts and data scientists. It has incredible scalability as well as flexibility. Python seems quite unbeatable in the industry right now in terms of popularity and demand.

Python has a relatively moderate learning curve, so if coding has not really been your strong suite, Python is a good starting point.

SQL

SQL is not as hyped up as Python nor do people talk about it as much as Hadoop or Tableau, however, every data professional tends to use it. Structured query language or SQL is a programming language used to access and manipulate databases. Knowing SQL gives you a lot of independence around different databases.

Spark

Apache Spark is an open source tool for data processing and it is high in demand. Spark allows in memory processing which gives it incredible speed in terms of data processing. Small and midsize organizations love working with Spark, nevertheless it has some pretty huge users too.

If you are looking for data analytics training in Bangalore you are likely to move forward with Apache Spark right after you have had your groundwork done.