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Top 10 Data Analytics Tools You Need To Know In 2024

Last updated on Apr 18,2024 147.2K Views

6 / 10 Blog from Data Science Introduction

The word ‘Data’ has been in existence for ages now.  In the era of 2.5 Quintillion bytes of data being generated daily, data plays a crucial role in decision-making for business operations. But how do you think we can deal with so much data? Well, there are several roles in the industry today that deal with data to gather insights, and one such vital role is of a Data Analyst.  A Data Analyst requires many tools to gather insights from data. This article on the Top 10 Data Analytics Tools will discuss the top tools that every budding Data Analyst to a skilled professional must learn in 2024.

In this article, we will explore a range of popular data analysis tools, including R and Python, Microsoft Excel, Tableau, RapidMiner, KNIME, Power BI, Apache Spark, QlikView, Talend, and Splunk. These tools offer diverse capabilities for data analysts and are widely used in the industry for various analytical tasks.

  1. R and Python
  2. Microsoft Excel
  3. Tableau
  4. RapidMiner
  5. KNIME
  6. Power BI
  7. Apache Spark
  8. QlikView
  9. Talend
  10. Splunk

Let’s dive into this article from the 10th tool on our list i.e Splunk.

10. Splunk

Splunk Logo - Top 10 Data Analytics Tools - Edureka

Splunk is a platform used to search, analyze, and visualize the machine-generated data gathered from applications,  websites, etc. Being named by Gartner as a Visionary in the 2024 Magic Quadrant for APM, Splunk has evolved products in various fields such as IT, Security, DevOps, Analytics.


  • Splunk Free
  • Splunk Enterprise
  • Splunk Cloud

All these 3 products differ by the bandwidth of the features they offer and are available for free download and trial versions. The pricing options for Splunk products are based on predictive pricing, Infrastructure-based pricing, and also rapid adoption packages.

Companies using 

Trusted by 92 out of the Fortune 100, companies such as Dominos, Otto Group, Intel, Lenovo are using Splunk in their day to day practices to discover the processes and correlate data in real-time. 

Recent Advancements/ Features

Since almost all the organizations need to deal with data across various divisions, according to Splunk official website Splunk aims to bring data to every part of your organization, by helping teams use Splunk to prevent and predict problems with monitoring experience, detect and diagnose issues with clear visibility, explore and visualize business processes and streamline the entire security stack.

Pros: Scalable, Real-time Monitoring, Rich Ecosystem of Add-ons
Cons: High Cost, Steep Learning Curve, Resource-Intensive

If you are looking for an online training program in Splunk, you can refer to our Splunk Certification Program.

9. Talend

Talend Logo - Top 10 Data Analytics Tools - Edureka

Talend is one of the most powerful data integration ETL tools available in the market and is developed in the Eclipse graphical development environment. Being named as a Leader in Gartner’s Magic Quadrant for Data Integration Tools and Data Quality tools 2019, this tool lets you easily manage all the steps involved in the ETL process and aims to deliver compliant, accessible and clean data for everyone. 


Talend comes with the following five products:

  • Talend Open Source
  • Stitch Data Loader
  • Talend Pipeline Designer
  • Talend Cloud Data Integration
  • Talend Data Fabric

Out of these, few are completely free, few are free for 14 days and few are licensed. All these products differ in their functionalities and pricing options.

Companies using 

Small startups to multinational companies such as ALDO, ABInBev, EuroNext, AstraZeneca are using Talend to make critical decisions.

Recent Advancements/ Features

Talend is the only platform that delivers complete and clean data at the moment you need it by maintaining data quality, providing Big Data integration, cloud API services, Preparing Data, and providing Data Catalog and Stitch Data Loader.

Recently Talend has also accelerated the journey to the lakehouse paradigm and the path to reveal intelligence in data. Not only this but the Talend Cloud is now available in  Microsoft Azure Marketplace.

Pros: Highly customizable, real-time data tracking, seamless integration with other tools.
Cons: Steeper learning curve, limited out-of-the-box templates, higher initial setup costs.

If you are looking for an online training program in Talend, you can refer to our Talend Certification Program.

8. QlikView

QlikView Logo - Top 10 Data Analytics Tools - Edureka

QlikView is a Self-Service Business Intelligence, Data Visualization, and Data Analytics tool. Being named a leader in Gartner Magic Quadrant 2024 for Analytics and BI platforms, it aims to accelerate business value through data by providing features such as Data Integration, Data Literacy, and Data Analytics.


QlikView comes with a variety of products and services for Data Integration, Data Analytics, and Developer platforms, out of which few are available for a free trial period of 30 days.

Companies using 

Trusted by more than 50,000 customers worldwide few of the top customers of QlikView are CISCO, NHS, KitchenAid, SAMSUNG.

Recent Advancements/ Features

Recently QlikView has launched an intelligent alerting platform Qlik Alerting for Qlik Sense® which helps the organizations handle the exceptions, notify users of potential issues, help users analyze further, and also prompts actions based on the derived insights.

Pros: Quick Data Visualization, Drag-and-Drop Functionality, Robust Analytics.
Cons: Steep Learning Curve, Limited Customization, Higher Cost.

If you are looking for an online training program in QlikView, you can refer to our QlikView Certification Program.

7. Apache Spark

Apache Spark Logo - Top 10 Data Analytics Tools - Edureka

Apache Spark is one of the most successful projects in the Apache Software Foundation and is a  cluster computing framework that is open-source and is used for real-time processing. Being the most active Apache project currently, it comes with a fantastic open-source community and an interface for programming. This interface makes sure of fault tolerance and implicit data parallelism.


Apache Spark keeps on releasing new releases with new features. You can also choose the various package types for Spark. The recent version is 2.4.5 and 3.0.0 is in preview.

Companies using 

Companies such as  Oracle, Hortonworks, Verizon, Visa use Apache Spark for real-time computation of data with ease of use and speed.

Recent Advancements/ Features

  • In today’s world Spark runs on Kubernetes, Apache Mesos, standalone, Hadoop, or in the cloud.
  • It provides high-level APIs in Java, Scala, Python, and R, and Spark code can be written in any of these four languages.
  • Spark’s MLlib –  the Machine Learning component is handy when it comes to Big Data processing. 

Pros: Fast, dynamic, easy to use.
Cons: No file management system, rigid user interface.

If you are looking for an online training program in Apache Spark, you can refer to our Apache Spark Certification Program.

6. Power BI

Power BI Logo - Top 10 Data Analytics Tools - Edureka

Power BI is a Microsoft product used for business analytics. Named as a leader for the 13th consecutive year in the Gartner 2024 Magic Quadrant,  it provides interactive visualizations with self-service business intelligence capabilities, where end users can create dashboards and reports by themselves, without having to depend on anybody.


Power BI provides the following products:

  • Power BI Desktop
  • Power BI Pro
  • Power BI Premium
  • Power BI Mobile
  • Power BI Embedded
  • Power BI Report Server

All these products differ by the functionalities offered by them. Few of them are free for a certain period of time and then you have to take the licensed versions

Companies using 

Multinational organizations such as Adobe, Heathrow, Worldsmart, GE Healthcare are using Power BI to achieve powerful results from their data.

Recent Advancements/ Features

Power BI has recently come up with solutions such as Azure + Power BI and Office 365 + Power BI to help the users analyze the data, connect the data and protect the data across various Office platforms.

Pros: It’s fast, it’s interactive, and it works on mobile devices.
Cons: No pre-processing of data and bad version control.

If you are looking for an online training program in Power BI, you can refer to our Power BI Certification.


KNIME Logo - Top 10 Data Analytics Tools - Edureka

Konstanz Information Miner or most commonly known as KNIME is free and an open-source data analytics, reporting, and integration platform built for analytics on a GUI based workflow. 


KNIME provides the following two software:

  • KNIME Analytics Platform – Is an open-source and used to clean & gather data, make reusable components accessible to everyone, and create Data Science workflows.

  • KNIME Server – Is a platform used by enterprises for the deployment of Data Science workflows, team collaboration, management, and automation.

Companies using 

Companies such as Siemens, Novartis, Deutsche Telekom, Continental use KNime to make sense of their data and leverage meaningful insights.

Recent Advancements/ Features

You do not need prior programming knowledge to use KNIME and derive insights. You can work all the way from gathering data and creating models to deployment and production.

Pros: It is an open-source platform that is great for programming that is based on images.
Cons: It can’t be scaled up, and some functions need technical knowledge.

4. RapidMiner

RapidMiner Logo - Top 10 Data Analytics Tools - Edureka

RapidMiner is the next tool on our list. Being named a Visionary in 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms, RapidMiner is a  platform for data processing, building Machine Learning models, and deployment.


The products of RapidMiner are as follows:

  • Studio
  • GO
  • Server
  • Real-Time Scoring
  • Radoop

All these products have sub-versions which differ by features offered by them and pricing options.

Companies using 

Companies such as BMW, Hewlett Packard Enterprise, EZCater, Sanofi use RapidMiner for their Data Processing and Machine Learning models.

Recent Advancements/ Features

Recently RapidMiner has launched RapidMiner 9.6 which has extended the platform to full-time coders and BI Users. It is a fully transparent, end-to-end Data Science platform that enables data preparation, Machine Learning, and model operations.

Pros: User-Friendly, Extensive Data Analytics Capabilities, Strong Community Support.
Cons: Limited Customization, Steep Learning Curve for Advanced Features, Resource-Intensive.

3. Tableau

Tableau Logo - Top 10 Data Analytics Tools - Edureka

Tableau is a market-leading Business Intelligence tool used to analyze and visualize data in an easy format. Being named as a leader in the Gartner Magic Quadrant 2024 For the eighth consecutive year, Tableau allows you to work on live data-set and spend more time on Data Analysis rather than Data Wrangling.


Tableau Product Family include the following:

  • Tableau Desktop
  • Tableau Server
  • Tableau Online
  • Tableau Reader
  • Tableau Public

Out of all, Tableau Public is a free Tableau software that you can use to make visualizations with but you need to save your workbook or worksheets in the Tableau Server which can be viewed by anyone.

Companies using 

Multinational organizations such as Citibank, Deloitte, Skype, and Audi use Tableau to visualize their data and generate meaningful insights.

Recent Advancements/ Features

Tableau is coming up with frequent updates to provide users with the following:

  • Fast Analytics
  • Smart Dashboards
  • Update Automatically
  • Ease of Use
  • Explore any data
  • Publish a dashboard and share it live on the web and on mobile devices.

Pros: It’s fast, it’s interactive, and it works on mobile devices.
Cons: No pre-processing of data and bad version control.

If you are looking for an online training program in Tableau, you can refer to our Tableau certification course.

2. Microsoft Excel

Microsoft Excel Logo - Top 10 Data Analytics Tools - Edureka

Microsoft Excel is a platform that will help you get better insights into your data. Being one of the most popular tools for Data Analytics, Microsoft Excel provides the users with features such as sharing workbooks, work on the latest version for real-time collaboration, and adding data to Excel directly from a photo and so on.


Microsoft Excel offers products in the following three categories:

  • For Home
  • For Business
  • For Enterprises

Few of the versions are available for free for 1 month. All these products have various versions which differ by features and their pricing options.

Companies using 

Almost all organizations use Microsoft Excel on a daily basis to gather meaningful insights from the data. A few of the popular names are McDonald’s, IKEA, Marriot.

Recent Advancements/ Features

The recent advancements vary on the basis of the platform. Few of the recent  advancements in Windows platform are as follows:

  • You can  get a snapshot of your workbook with Workbook Statistics
  • You can give your documents more flair with backgrounds and high-quality stock images absolutely for free

Pros: It’s used by a lot of people and has a lot of useful features and plug-ins.
Cons: Cost, mistakes in calculations, and bad at handling big amounts of data.

If you are looking for an online training program in Microsoft Excel, you can refer to our Microsoft Excel Certification Program.

1. Programming Languages: R & Python

R and Python Logo - Top 10 Data Analytics Tools - Edureka

R and Python are the top programming languages used in the Data Analytics field. R is an open-source tool used for Statistics and Analytics whereas Python is a high level, an interpreted language that has an easy syntax and dynamic semantics. 


Both R and Python are completely free and you can easily download both of them from their respective official websites. 

Companies using 

Companies such as ANZ, Google, Firefox use R, and other multinational companies such as YouTube, Netflix Facebook use Python.

Recent Advancements/ Features

Python and R are developing their features and functionalities to ease the process of Data Analysis with high speed and accuracy. They are coming up with various releases on a frequent basis with their updated features.

Pros: It works on any platform, is very compatible, and has a lot of packages.
Cons: It’s slower, less safe, and harder to pick up than Python.

How to choose a data analysis tool

You’ve got your data set up and ready to go, and now you need the right software to analyze it. How do you determine which one will best serve your company?

To begin, keep in mind that there is no silver bullet when it comes to data analytics software. You may find that one tool on this list meets the majority of your needs, while another is needed for more specialized tasks.

Second, you should think about your company’s requirements and identify who will need access to the data analysis tools. Who will be their target audience, other data analysts and scientists, or non-technical users who need an interactive and intuitive interface? Both novice and seasoned techies will find useful options here.

Third, think about how well the tool can model data. Do these features exist in the tool, or will you need to perform data modeling in SQL or another tool before diving into analysis?

Finally, the fourth consideration is the cost and licensing requirements. Some of the alternatives don’t cost anything, while others have a freemium model where some features are freemium but the full product requires a paid license. Some data analysis resources will require a paid membership or license to access. If you’re looking at this on a project-by-project basis, the subscription length may be less of a concern than the number of users.

Ready to unlock the power of data? Dive into Python for Data Science today! Whether you’re analyzing trends, building predictive models, or extracting valuable insights, Python’s versatile libraries like NumPy, pandas, and scikit-learn empower you to conquer any data challenge

With this, we have come to the end of our Top 10 Data Analytics Tools list.

Data Analyst Training Course follows a set structure with 4 core courses and 7 electives spread across 15 weeks. It makes you an expert in key technologies related to Data Analytics. It is a structured learning path recommended by leading industry experts and ensures that you transform into an expert Data Analytics professional while making you learn the usage of tools such as R, SAS, Tableau, QlikView, Advanced Excel, Machine Learning, etc. Individual courses focus on specialization in one or two specific skills, however, if you intend to become a Data Analyst, then this is the path for you to follow. 

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Top 10 Data Analytics Tools You Need To Know In 2024