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Use AI Via an End-to-End Data Lakehouse to Increase Data Lifecycle Efficiency From Ingestion to Prediction

Use AI Via an End-to-End Data Lakehouse to Increase Data Lifecycle Efficiency From Ingestion to Prediction
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Enable employees to generate and execute on valuable insights with the right data platform

To increase productivity and profitability, data scientists need access to a seamless data experience that combines management, analytics, and data science functions to promote interoperability, automation, security, and governance.

This report—based on a commissioned online survey conducted by Forrester Consulting on behalf of Cloudera, HPE, and Intel of data practitioners and decision makers—uncovered technical and organizational challenges related to data projects across increasingly distributed data science teams.

Read the report to get key recommendations on how an end-to-end data lakehouse can help overcome those challenges by:

  • Reducing data integration efforts
  • Accelerating time to value for advanced analytics
  • Improving governance and productivity through enhanced collaborations

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