Organizations are leveraging data to drive innovation, create significant value and differentiate themselves. However, as organizations recast data from an operation by product to an enterprise asset, they are confronted with challenges related to data complexity, such as a proliferation of data volumes, variety, velocity and structure. A preliminary step in exploiting data as corporate asset is data preparation. Data preparation involves collecting, combining, transforming, and organizing data from disparate sources. Data preparation is a critical but time intensive process that ensures data citizens have high quality data sets to drive informed, data-driven decisions
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Use machine learning recommendations to format, join, tag and cleanse data. No coding required.
Share transformed data sets throughout the enterprise and with BI and analytics tools.
Connect to data governance, lineage and privacy tools to drive compliance and value.
Integrate all your data, on premises or on any cloud — on this flexible multicloud platform.
Access, curate, categorize and share business-ready data using this enterprise data catalog.
Read this ebook to learn how machine learning can speed data preparation for business-ready data.
Explore to see how DataOps builds a scalable, agile data culture with automation, data quality and governance.
Learn how intelligent cataloging and machine learning-powered data governance helps to deliver business-ready data.