Key Stakeholders: IT managers, data scientists, data analysts, database administrators, application developers, enterprise statisticians, machine learning directors and managers, existing enterprise Cloudera customers Why It Matters: As Cloudera continues its pivot towards becoming a full-service machine learning and analytics platform, its latest updates enhance its ability to retain existing customers of its commercial data lake and Hadoop distribution looking to expand into data science workflows, and attract net-new data science customers. Top Takeaway: Cloudera's additions to its Data Science Workbench provide a more rigorous, scientific approach to data science than prior versions, and allow for speedier implementation of results into...
Cloudera Improves Enterprise Rigor and Reuse by Putting the “Science” in Data Science Workbench
- Tags:
- application developers
- Cloudera Data Science Workbench
- Data Analysts
- Data Scientists
- Database Administrators
- enterprise statisticians
- existing enterprise Cloudera customers
- IT Managers
- machine learning directors and managers
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