We don’t need to tell you that data analysis is big business. From tech companies to government to universities and even hospitals—companies and institutions are collecting, storing and analyzing data like never before. Data analysis has become an indispensable expertise in the modern business world.

As a result, demand for qualified data analysts is growing by the day. It’s no easy job, but luckily, data analysts have plenty of options to choose from when it comes to specialized tools designed to make their work easier. With a little know-how, choosing the right tools to suit your business or industry can make the responsibilities of data analysis seem that much less daunting.

We'll take you through the key factors to consider before you select the data analysis tools to suit your career goals. We’ve also compiled a list of some of the most popular and efficient tools currently at your disposal.

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Preparing for Data Analysis

In order to select the right tools for the type of data analysis you’ll be doing, you have to have a few important things in order first:

Selecting the Right Tools for Data Analysis

Once you have centralized your data, you can get down to the business of analyzing it for business insights, which you will then use to plan strategies that will help grow your business. But how do you know which one fits your business to a T?

First, you’ll need to develop a list of your business needs and gauge the technical know-how of the staff who intend to use these tools. Is your data being dealt with by highly-trained data scientists and analysts, or by employees with limited technical knowledge? Or both?

If your team is less experienced, then a simple, intuitive interface would be a wise choice. If they’re at the other end of the spectrum, then you could make use of a platform that has provisions for an interactive interface for making iterations on code. You should also ascertain if the visualization tools of the platform satisfy your organization's needs.

The modeling abilities of the tool also need to be analyzed. Some platforms are advanced enough to carry out data modeling automatically. If that doesn’t fit the bill, and you insist on using homegrown modeling, it'll have to be a platform that uses SQL to model your data before you analyze it.

Last but not the least, the pricing and licensing fee of the platform needs to be researched. Most of the options available are free, while some choose to charge a fee or subscription. And just because a platform requires you to pay doesn’t mean that it’s the best option—some of the free tools pack quite a substantial punch.

The Tools Data Analysts Swear By

Let’s take a look at some of the most powerful and user friendly data analysis tools currently available.

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