The use of Artificial Intelligence tools to analyze data can make data visualization simple. AI enables homogeneous data analysis across all inputs. It lacks human bias and can analyze large volumes of data at breakneck speeds. AI can predict how your campaigns will perform, and even provide insight to help you make informed decisions.
You can use this tool to manage and review your data, even if you’re not a data scientist. AI tools enable you to analyze your data without the need to spend time and the expensive process of designing algorithms.
Tableau is a popular business intelligence and data visualization platform. It can help you analyze, understand, and communicate your data. Tableau allows you to connect to multiple data sources, create interactive dashboards and visualizations and share your insights with other users.
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In just a few clicks, Polymer’s powerful AI drives your spreadsheet. This allows you to review your data and gain more insight. There are no lengthy onboarding procedures or instructional videos to watch. Polymer will convert your spreadsheet into an organized database that you can easily navigate.
3. Power BI
Microsoft Power BI is a data visualization and business intelligence tool that can help you understand, communicate and analyze your data better. A variety of tools and capabilities make it easy to connect to data sources and create interactive dashboards or reports. You can also share your insights with others thanks to the many tools and capabilities available.
Splunk can be used to gather, analyze, and display machine data. It is possible to index large amounts of data in real-time, which allows for fast searches and analysis to identify patterns and provide solutions.
RapidMiner is a powerful data mining and machine-learning platform that makes it possible to analyze data and create prediction models. It is easy to use, so you can start using it immediately even if you are not familiar with data mining or machine learning.
It is an additional data analytics tool that enables developers and analysts to browse and display their data. The platform is easy to use thanks to its drag-and-drop capabilities and dynamic user interface. Sisense gives users access to their “In-Chip”, which allows them to choose between RAM or CPU when processing large datasets. These speed up computation.
KNIME is an open-source data analysis platform that can be used to model, transform and analyze data (Konstanz Information Miner). You can use its user-friendly interface and flexible design to create customized data pipelines or workflows for various data analysis tasks.
8. Apache Spark
It’s an open-source distributed computing platform for processing and analyzing big datasets. Its simple and quick design makes it easy to use. You can build and release data pipelines, and apps that can handle petabyte-sized data.
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QlikView is a business intelligence and data visualization software that facilitates data analysis, comprehension, and communication. It is user-friendly. Even if you have never done data analysis before you can get started right away.
Talend is a real-time and big data processing capability that can handle many types of data. You can use Talend to process and analyze data from a variety of big data platforms such as Hadoop or Spark or Hive utilizing big data tools like Pig, Hive, or Mahout.