Remove 2019 Remove Big Data Remove Data Integration Remove Data Warehouse
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Three Takeaways from Gartner’s 2019 Magic Quadrant for Data Management Solutions for Analytics

Cloudera

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. We recognize the following takeaways from Gartner’s 2019 MQ DMSA: 1. 3. Expansion beyond core data management. Cloudera’s 3 Key Takeaways.

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Simplifying data processing at Capitec with Amazon Redshift integration for Apache Spark

AWS Big Data

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. He has supported Capitec in their AWS journey since 2019.

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Cloudera & Informatica – Next-Gen Analytics Partners

Cloudera

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

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How Metadata Makes Data Meaningful

erwin

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

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How Metadata Makes Data Meaningful

erwin

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Most of the data management moved to back-end servers, e.g., databases.

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The DataOps Vendor Landscape, 2021

DataKitchen

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

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