Top 15 Data Analysis Tools For Managing Data Like A Pro

Qlik supports many types of charts that users can customize with both embedded SQL and drag-and-drop modules. By evaluating these distinct criteria carefully, our methodology provides a clear insight into each tool’s strengths and weaknesses. We don’t simply assign a rank; instead, we explain how each tool performs in different aspects that matter most to you. From cost considerations to innovative features, we’ve dissected what makes each tool unique. Our approach ensures an unbiased assessment, aiming to assist you in identifying the best data analytics tools that align with your specific requirements and budget constraints. The goal is to offer you a well-rounded guide that transcends mere rankings, enabling you to make an informed decision tailored to your unique needs and goals.

  • A relative newcomer to predictive analytics, H2O gained traction with a popular open source offering.
  • It also facilitates team collaboration and includes a visual workflow designer for Spark and Hadoop.
  • Our data analytics tools article wouldn’t be complete without business intelligence, and datapine is one example that covers most of the requirements both for beginner and advanced users.
  • SAS Business Intelligence provides a suite of applications for self-service analytics.
  • In this case, you may need to consider the number of users required or—if you’re looking on solely a project-to-project basis—the potential length of the subscription.
  • His words have been published in print and online, including in the Daily Telegraph, TES, and across other education sector media.

With businesses increasingly leveraging business analytics tools, multiple avenues are opening up for qualified business analysts in diverse sectors, including automotive, healthcare, retail, banking, hospitality, and aviation. One of the most up-to-date business analytics tools, Microstrategy, incorporates insightful analytical and statistical capabilities that enable real-time trend forecasting, with options for third-party data mining. R is an interpreted programming language designed for use in statistical computing and graphics.

Data Analysis Tools to Know

Taking that into account, automation tools could not be left out of this list. In simple words, data analytics automation is the practice of using systems and processes to perform analytical tasks with almost no human interaction. That said, automating analytical processes significantly increases productivity, leaving more time to perform more important tasks.

A 2017 and 2018 Most Influential Business Journalist and 2021 “Who’s Who” in Data Management, Tim is a recognized industry thought leader and changemaker. 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. 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 2020 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.

Talend can efficiently process millions of data records and handle any size project. It features data preparation, big data integration, cloud pipeline designer, and Stitch Data Loader, covering an assortment of data management requirements for any sized organization. Board features in the list of top-rated business analyst software tools because of its industry-leading business analytics model that permits users to create interactive and intuitive business analytics reports and dashboards. Short for Konstanz Information Miner, KNIME is a free, open-source analytics platform that supports the integration, processing, visualization and reporting of data, allowing it to make interpretations and predictions.

Data Analytics Tools

Besides that it also offers a cloud platform for business analytics called SAS Viya and also to get a strong grip on AI & ML, they have introduced new tools and products. This open-source data analysis tool enables users to leverage powerful scripting languages like R and Python to build data science apps. Its drag-and-drop GUI is simple to navigate and easy to learn for beginners and provides users with an excellent way to analyze and model data via visual programming. The platform is kitted out with a collection of drag-and-drop tools and interactive dashboards for a more collaborative and easy user experience. And it is all built on an API-driven, cloud-native architecture to allow for flexible and scalable deployment.


Owned by software giant Salesforce, Tableau is designed so that everyone at a given company can see essential patterns and correlations in institutional data, without having to write a single line of code. Rather than technical data mining, Tableau relies on a person’s innate ability to spot patterns, so its visualizations range from color-coded maps to live graphics that update in real time. Much of Tableau runs on top of its core query language, VizQL, which translates drag-and-drop components into back-end queries — thus minimizing the need for the end user to optimize its performance. Metabase is yet another free and open-source analytics and business intelligence platform. But what sets it apart is its ability to allow users to ask questions, providing a more approachable way for less-than-techie users to analyze their data with simple filtering and aggregations.

Data Analytics Tools

Rather you want someone to look into your code for errors or provide any other kind of feedback to your work, a document sharing tool is the way to go. These solutions enable users to share interactive documents which can contain live code and other multimedia elements for a collaborative process. Below, we will present Jupyter Notebook, one of the most popular and efficient platforms for this purpose. Additionally, the platform provides flexible deployment options to support multiple scenarios, business sizes and use cases.

Companies using

Visualizing data isn’t confined to rigid, predefined charts; you can drag and drop variables onto a canvas, seeing instant and insightful visualizations. Think of it as painting a portrait of your audience, using numbers and trends as your color palette. Sisense doesn’t simply deliver analytics; it injects them directly into the products. Development teams can weave dashboards and predictive insights into their existing ecosystem without breaking a sweat. It’s like fitting a custom-tailored suit rather than an off-the-rack disappointment. The platform’s design vision allows brands to maintain consistency, keeping the analytics from becoming a distracting sidebar.

Data Analytics Tools

RapidMiner can also be extended using R and Python scripts, and numerous third-party plugins are available through the company’s marketplace. However, the product is heavily optimized for its graphical interface so that analysts can prepare data and run models business analytics instrument on their own. Qlik provides a self-service data analytics and business intelligence platform that supports both cloud and on-premises deployment. The tool boasts strong support for data exploration and discovery by technical and nontechnical users alike.

Discover a List of The 17 Best Data Analysis Software & Tools On The Market

Google Data Studio is a free dashboarding and data visualization tool that automatically integrates with most other Google applications, such as Google Analytics, Google Ads, and Google BigQuery. Thanks to its integration with other Google services, Data Studio is great for those who need to analyze their Google data. For instance, marketers can build dashboards for their Google Ads and Analytics data to better understand customer conversion and retention.

With sub-second queries at scale, Domo allows you to select from packages that include data storage and query volumes. It has self-service data preparation and management capabilities, as well as an intuitive drag-and-drop interface augmented with AI and ML capabilities. Zoho Analytics has a wide range of APIs that allow it to be readily expanded.

Data Studio can work with data from a variety of other sources as well, provided that the data is first replicated to BigQuery using a data pipeline like Stitch. Klipfolio is data analytics software that is best suited for businesses of all sizes that are looking to get instant insights from their data. Looker is data analytics software that is best suited for businesses that want to use data to visualize patterns and important traits. First, consider that there’s no one singular data analytics tool that will address all the data analytics issues you may have.

Getting started is easy with thousands of ready-to-use automation templates to choose from. AI tools are trained using one set of criteria, and are often customizable, so you can ensure that your data delivers accurate and actionable insights. Structured query language (SQL) is the standard language created to communicate with databases and is particularly useful when handling structured data. Used to search, add, update, and delete data, among others, SQL makes it easy to organize structured data. Looker integrates with existing tools to introduce new, highly-focused data that can show previously unseen data relationships to help teams make more informed decisions. Depending on your skills and interests, you may specialize in a business analyst role, such as Big Data Engineer, Data Scientist, Database Administrator, Marketing Analytics Manager, or Data Visualization Specialist.

Qubole provides end-to-end services in moving data pipelines with reduced time and effort. It’s an open-source big data tool that helps in fetching data in a value of chain using ad-hoc analysis in machine learning. Qubole is a data lake platform that offers end-to-end service with reduced time and effort which are required in moving data pipelines. It is capable of configuring multi-cloud services such as AWS, Azure, and Google Cloud.

These types of analytics tools each offer unique perspectives and capabilities. They form a toolkit that’s not just about crunching numbers but about understanding, predicting, guiding and transforming data into a dynamic roadmap for success. It’s like having various lenses to view your business landscape, each providing a different, invaluable angle. Domo is data analytics software that is best suited for businesses looking to streamline workflows. Now that we’ve checked out all of the data analysis tools, let’s see how to choose the right one for your business needs. It also offers strong data visualization but has room for improvement in other areas.