Top 7 Data Analytics Tools

According to Forbes, humans today crank out roughly 2.5 exabytes or 2,500 petabytes of data every day. Now, that’s big, big data. Without the best data analytics tools, it’s nearly impossible to accurately analyze this surging sea of data. Data analysis transforms amorphous data into valuable information presented in easy-to-use formats. Discover the top 7 data analytics tools that make data preparation, data analysis, and data visualization a breeze.

Not all Data Analytics Tools are Created Equal

Data quality is dependent upon the quality of the tools used as well as the analyst’s skill. Want to get the most of your data? You must couple your data analysis expertise to the best data analysis software available.

Luckily, developers have created lots of amazing data software packages. But testing each tool to establish its potency and appropriateness is a time-consuming process. The following list (hopefully) makes the search for the perfect data analysis tool easy and quick.

Let’s jump right in and examine each of the tools. Besides, if you are looking for data management training in Kenya, then, Uphilos consultancy got you covered. 

Top 7 Data Analytics Tools


2. Excel

3. Python

4. SAS


6. R Programming



Developed by SPSS Inc. in 1968, the tool has been around for more than 50 years. IBM later acquired SPSS (in 2009), and the tool’s name changed to IBM SPSS Statistics. But no one ever refers to the software by that name — everyone calls it SPSS.

What SPSS Can Do for Your Data

SPSS is a sophisticated tool originally designed to support analysis and management of social science data. Today, the software sees widespread usage in academia, but academics aren’t the only professionals who use it.

Number crunchers in insurance, government, financial services, market research, healthcare, retail, risk management, and telecommunication swear by SPSS. You won’t find a data analysis tool that’s more versatile than SPSS. It is one of the most popular courses in data management training Kenya. 

The Beauty of SPSS

SPSS is super easy to use. But that doesn’t mean someone with zero data analysis training won’t face difficulties using it. It just means it’s user-friendly. Whether you’re prepping to perform descriptive statistics, linear regression, factor analysis, or cluster analysis, SPSS has got you covered.

2. Excel

What makes Excel one of the top 7 data analytics tools? You guessed right, it’s the tool’s built-in PivotTables. Also, Excel is pretty easy to use. You won’t need to sign up for expensive data analysis courses. But figuring out the PivotTables can be somewhat challenging.

A Feature-rich Tool

Excel is a feature-rich data analysis tool that enables analysts to get the most of their data. With this software, you can sort or filter your data any way you want. For instance, you can sort the data from the highest to the lowest values. You can also filter your data on the basis of various criteria.

Create Charts and Tables Easily and Quickly

Prepping for a presentation? Why not create simple Excel charts so your audience can read your data quickly and retain more of it? Instead of charts, you may also create tables easily and quickly to help you analyze and visualize the data. Then there’s “What if Analysis.” The feature lets you use Excel’s Scenario Manager to create different scenarios for smarter decision-making.

Easily Analyze Statistical, Engineering, or Financial Data

Looking for a suitable tool to analyze financial, engineering, or statistical data? Look no further than Excel’s Analysis ToolPak.

Another useful feature is Solver. The feature enables you to find optimal solutions for different types of decision problems.

Leverage Excel’s PivotTables

PivotTables are probably the most powerful feature in Excel. If you have a humongous, detailed dataset and need to extract its significance, turn to PivotTables.

With all these amazing features, it’s hardly surprising that Excel has hypnotized so many data analysts.

3. Python

Python is a lot more than just a popular programming language. It’s doubles up as a terrific data analytics tool. It helps you perform lots of advanced procedures and supports sophisticated model development.

You can also use Python to import and export datasets. In addition, you can use it to handle simple linear regression, multiple linear regression, and polynomial regression.

There’s more.

The tool comes in handy when you want to clean or prepare your data. Cleaning and prepping of data involves various processes including data formatting and binning. It also includes data normalization, identifying and addressing missing values. Grouping data sets, correlation, and descriptive statistics are other critical functions you can perform using Python.

Have You Mastered These?

When it comes to data analysis using Python, you’ll need to master Pandas DataFrames, SciPy libraries, and Numpy multidimensional arrays. Maybe all this sounds complex. But Python isn’t exactly rocket science. Still, you’ll want to enroll in any of the best data analysis courses for beginners you can afford.

4. SAS

What do Bank of America, Discover, Orlando Magic, and Honda have in common? They’re all subscribed to SAS. And that’s no accident — SAS is among the finest data analysis tools available today.

Pretty much any conceivable industry can benefit enormously from leveraging the vast potential of SAS. Industries that rely heavily on SAS include banking, automotive, healthcare, education, insurance, manufacturing, oil & gas, sports, and utilities.

Incorporates AI — SAS is Smart

The tool was developed by SAS Institute between 1966 and 1976 at North Carolina State University. It leverages the awesome power of Artificial Intelligence to become arguably the smartest data analytics tool ever created.

SAS is among the top 7 data analytics tools as it seamlessly supports multivariate analysis, advanced analytics, business intelligence, predictive analytics, and data management.

Want to Learn SAS?

How will you master SAS considering you’re time-starved? Stop worrying. The web swarms with proven data analysts who provide affordable data analysis training online. Sure, you’ll have to sink a little money and time into the investment. Good news: you’ll come out ahead.


Researchers of all hues have StataCorp to thank for creating STATA in 1985. The tool is an all-purpose software package that always returns reliable results.

Pretty much everyone can use STATA to analyze data. That said, researchers in biomedicine, sociology, epidemiology, economics, and political science seem to have made the tool their preference. Data scientists, too, love STATA.

If you’re looking for a “by researchers for researchers” kind of tool for data management training in Kenya, grab STATA now. The software boasts a whole slew of amazing statistical features so you can analyze your data like a pro.

Accomplish Great Things with STATA

STATA is easy to use, grow with, automate, and extend. It offers dynamic document creation that props production of truly reproducible research. And when you need publication-quality graphics to go with your kickass content, look no further than this tool.

Here’s one more thing that makes STATA great: it’s compatible across platforms. Throw in world-class technical support, and you have a research companion you’ll praise ceaselessly.

6. R Programming

Do you aspire to become a valuable business analyst, data scientist, data analyst, or data miner? That’s great, and you should master R soonest possible. R is both a hugely popular programming language and one of the best data analysts tools.

Present Complex Datasets

R supports machine learning and advanced data analysis. This smart software allows researchers to incorporate superior quality graphics into their work.

Want a reliable piece of data analysis software that enables you to present complex datasets seamlessly and compellingly? If yes, choose R Programming.

Is R User-friendly?

It is, but wrapping your head around the tool takes a bit of training. To perform procedures such as data manipulation and visualization, you must understand how to navigate R’s packages.

Don’t worry, though. The mighty web provides gazillions of R Programming experts who can teach you the craft. Simply ask your favorite search engine to guide you to where you can find the best data analysis training online. Alternatively, ask us.


So you’ve collected loads of high-quality qualitative or mixed-methods data and are now prepping to analyze it. You need an appropriate data analytics tool and put it to some really good use. NVIVO prides itself on being among the finest qualitative and mixed-methods data analysis software ever designed.

NVIVO was developed by QSR International. The tool helps researchers glean meaning from research material laden with lots of multimedia and text-based information. The tool enables researchers to dive deep and exhaustively analyze their data.

Easily Do This with NVIVO

NVIVO lets you store and organize your data in one platform. It’s also great at categorizing and analyzing data. With this tool, you can easily and quickly tabulate and visualize your findings. Once you do that, you can map ideas, brainstorm, and spot relationships between variables. Also, properly visualized data makes it easy to discover areas that need further investigation.

7 Top Data Analytics Tools: Final Thought

Do you agree these software packages are the greatest data analytics tools in the world? Maybe you have a different opinion. And that’s all right. But the hundreds of thousands of people who swear by these tools can’t all be wrong. Still, we’d love to have your thoughts in the comments below. Meanwhile, grab an effective and appropriate tool and start extracting information from your data. If you are looking for data management training in Kenya, check our Data Science Training Courses and train with us.

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