Best Data Analysis Software for DataHub
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Compare the Top Data Analysis Software that integrates with DataHub as of July 2025
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This a list of Data Analysis software that integrates with DataHub. Use the filters on the left to add additional filters for products that have integrations with DataHub. View the products that work with DataHub in the table below.
What is Data Analysis Software for DataHub?
Data analysis software is software used to collect, process, and interpret large datasets to identify patterns, trends, and insights. It allows users to visualize data through interactive charts, graphs, and dashboards, making complex information more accessible. These tools often incorporate statistical, predictive, and machine learning features to support informed decision-making. Data analysis software is utilized across various industries, including finance, healthcare, marketing, and research, to enhance strategic planning and operational efficiency. By transforming raw data into actionable insights, it empowers organizations to make data-driven decisions. Compare and read user reviews of the best Data Analysis software for DataHub currently available using the table below. This list is updated regularly.
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1
Google Cloud BigQuery
Google
BigQuery offers high-performance tools for analyzing large datasets quickly and accurately, enabling businesses to extract valuable insights from their data. It supports both structured and semi-structured data, making it versatile for different types of data analysis, from simple queries to advanced analytics. Whether it’s running complex aggregations or time-series analyses, BigQuery’s scalability ensures consistent performance across a range of tasks. New customers can use their $300 in free credits to explore its full suite of data analysis tools, helping them gain insights and make data-driven decisions faster. The platform also supports real-time analytics, allowing businesses to react to data changes as they happen.Starting Price: Free ($300 in free credits) -
2
Looker
Google
Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time. -
3
Tableau
Salesforce
Tableau, now enhanced with AI-powered capabilities and integrated with Salesforce, is an advanced analytics platform that helps businesses turn data into actionable insights. With Tableau Next, users can unlock the full potential of their data by accessing trusted AI-driven analytics. Whether deployed in the cloud, on-premises, or natively within Salesforce CRM, Tableau enables seamless data integration, powerful visualizations, and collaboration. The platform is designed to support organizations of all sizes in making data-driven decisions, while fostering a Data Culture through easy-to-use, intuitive tools for analysts, business leaders, IT leaders, and developers alike.Starting Price: $75/user/month -
4
Teradata VantageCloud
Teradata
Teradata VantageCloud is a comprehensive cloud-based analytics and data platform that allows businesses to unlock the full potential of their data with unparalleled speed, scalability, and operational flexibility. Engineered for enterprise-grade performance, VantageCloud supports seamless AI and machine learning integration, enabling organizations to generate real-time insights and make informed decisions faster. It offers deployment flexibility across public clouds, hybrid environments, or on-premise setups, making it highly adaptable to existing infrastructures. With features like unified data architecture, intelligent governance, and optimized cost-efficiency, VantageCloud helps businesses reduce complexity, drive innovation, and maintain a competitive edge in today’s data-driven world. -
5
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
6
Metabase
Metabase
Meet the easy, open source way for everyone in your company to ask questions and learn from data. Connect to your data and get it in front of your team. Dashboards (like this one) are easy to build, share, and explore. Anyone on your team can get answers to questions about your data with just a few clicks, whether it's the CEO or Customer Support. When the questions get more complicated, SQL and our notebook editor are there for the data savvy. Visual joins, multiple aggregations and filtering steps give you the tools to dig deeper into your data. Add variables to your queries to create interactive visualizations that users can tweak and explore. Set up alerts and scheduled reports to get the right data in front of the right people at the right time. Start in a couple clicks with the hosted version, or use Docker to get up and running on your own for free. Connect to your existing data, invite your team, and you have a BI solution that would usually take a sales call. -
7
Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.
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