Best Data Cleansing Software for IRI Voracity

Find and compare the best Data Cleansing software for IRI Voracity in 2024

Use the comparison tool below to compare the top Data Cleansing software for IRI Voracity on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

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    IBM Cognos Analytics Reviews
    Cognos Analytics with Watson brings BI to a new level with AI capabilities that provide a complete, trustworthy, and complete picture of your company. They can forecast the future, predict outcomes, and explain why they might happen. Built-in AI can be used to speed up and improve the blending of data or find the best tables for your model. AI can help you uncover hidden trends and drivers and provide insights in real-time. You can create powerful visualizations and tell the story of your data. You can also share insights via email or Slack. Combine advanced analytics with data science to unlock new opportunities. Self-service analytics that is governed and secures data from misuse adapts to your needs. You can deploy it wherever you need it - on premises, on the cloud, on IBM Cloud Pak®, for Data or as a hybrid option.
  • 2
    Trillium Quality Reviews
    High-volume, disconnected data can be quickly transformed into actionable business insights using scalable enterprise data quality. Trillium Quality, a flexible, powerful data quality tool, supports your rapidly changing business requirements, data sources, and enterprise infrastructures, including big data and cloud. Its data cleansing features and standardization capabilities automatically understand global data such as customer, product, and financial data in any context. Pre-formatting and preprocessing are unnecessary. Trillium Quality services can be deployed on-premises or remotely in real time, in batch or in the cloud. They use the same rules and standards across a wide range of applications and systems. Open APIs allow you to seamlessly connect to third-party and custom applications while centrally managing and controlling data quality services.
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