Top Tools for Data Analytics

As we continue to use our devices to share and search for information, more data is going to be accumulated by businesses across the globe. Businesses require software tools to make sense of this data so they can optimize business processes, learn more about customer habits, and ultimately improve their products to earn more money.

There are dozens of tools out there to help analyze and visualize data, and choosing which to use can seem impossible with so many options available. Here, we’ll discuss some of the most popular tools on the market to hopefully make your decision a bit easier. 

Tableau

Let’s start with the fastest-growing data analytics tool currently available. Tableau, utilized by major companies like Amazon, Verizon, and HelloFresh, is especially well known for its stunning and easily understandable visualizations of data. It can quickly analyze any kind of data—Excel spreadsheets, cloud databases, and data sorted in places like Hadoop. The drag and drop feature allows for further ease of use. Tableau’s main objective is to help businesses gain insight into their processes and improve outcomes using data they’ve already produced. By making data analysis easier to accomplish, the hope is that more employees will be able to use data visualization to their advantage. 

Excel

On the surface, Excel seems like a relatively simple tool but don’t let the blank spreadsheet fool you. This is a powerful tool that is used by companies like Samsung Electronics and Dell Technologies for all sorts of data analysis. The software is not free to use, but it is included in the Microsoft Office suite of programs. Because Excel is so widely used, there are hundreds of free and reliable online tutorials to help those who are just starting. Excel offers a Data Analysis Toolpak that, once configured, quickly creates understandable representations of data and allows for quicker decision making. 

Microsoft Power BI

Another Microsoft product, Microsoft Power BI (Business Intelligence) offers three versions of their data visualization software: Desktop, Pro, and Premium. The desktop version is free while the other two require additional investment. This program allows you to connect many sources of data and create live dashboards to generate reports. Power BI offers a wide range of templates that helps transform raw data in the form of a spreadsheet transformed into visually appealing illustrations. Some of the top companies that use Power BI are Nestle and Ecolab. 

SAS

Designed to work with data from multiple sources, SAS is popular for business intelligence across industries around the world. Many major corporations use SAS to complete their data analysis including Discover, World Wildlife Foundation, and Nestle. This program can merge multiple tables of data and perform predictive analysis. It also contains a robust visual analytics program that will create appealing reports. SAS is particularly popular in the pharmaceutical and clinical research industries. Usage of the program requires a subscription, though there is a Free University Edition available for students to learn the program for non-commercial use. 

Apache Spark

This program is capable of processing data on a very large scale in a relatively short amount of time. It was designed to be used by researchers, developers, and data scientists. One of the benefits of Apache Spark is that it is a free and open-source program with experienced developers that consistently contribute to its maintenance. One of the reasons it can perform tasks quickly is that it can distribute responsibilities across multiple systems, allowing data to be analyzed in smaller batches. Apple, IBM, and Facebook use Apache Spark for their data processing needs.

Python

Although it was originally developed for web and software development, Python has since been modified for use with data science. Like Apache Spark, Python is also an open-source, free program. Pandas is its designated data analysis library and it can perform tasks such as masking, merging, grouping, and cleaning your data. Python contains several other libraries that can also be used for data mining and statistical modeling. Companies that use Python for data analysis include NASA, Spotify, and CERN.

Qlik

This tech company offers an entire platform of data analysis and business intelligence tools. Their ad hoc query feature allows the user to easily access the information needed. The program boasts quick processing speeds, the ability to automate data association, workspace security, and a range of methods to represent data. Companies around the world use Qlik including Lenovo, Johnson & Johnson, and Siemens Healthineers.

Learn More about Data Analytics with Career Centers

If you’d like to boost your skills in some of the tools listed above, you can check out the list of data analytics classes offered by Career Centers. These courses can be taken remotely or in-person at Career Centers’ headquarters in New York City. Career Centers allows students one free retake of any course to cement the information. Career Centers has a Microsoft Excel Bootcamp, a Power BI Bootcamp, and a Tableau Bootcamp available. Its Data Analytics Technologies Bootcamp is another option if you’d like to learn about multiple tools at once. 

Noble Desktop, a partner school of Career Centers, also has a handful of data analytics courses to check out. The Python for Data Science Bootcamp is geared toward beginners who want to learn more about how the programming language of Python can be used for manipulating and visualizing datasets. Finally, its Data Analytics Certificate is a great choice if you’d like a more comprehensive experience. You’ll learn some of the most in-demand skills for professional data analysts. Your instructors will help you produce a portfolio of projects to present to hiring managers as you start your career.