Remove Accessible Remove Data Schemas Remove Data Warehouse Remove Metadata
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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

Netflix Tech

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

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A Cost-Effective Data Warehouse Solution in CDP Public Cloud – Part1

Cloudera

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

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Enabling Self-Service Business Insights with Cloudera Data Warehouse

Cloudera

How self-service data warehousing frees IT resources. Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Simplified provisioning.

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Modern Data Engineering

Towards Data Science

Often it is a data warehouse solution (DWH) in the central part of our infrastructure. Data warehouse exmaple. What I like about it is that it makes it really easy to work with various data file formats, i.e. SQL, XML, XLS, CSV and JSON. It will be a great tool for those with minimal Python knowledge.

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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., Glue uses ETL jobs for extracting data from various AWS cloud services and integrating it into data warehouses and lakes.

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Top Data Catalog Tools

Monte Carlo

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

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Monte Carlo Announces Delta Lake, Unity Catalog Integrations To Bring End-to-End Data Observability to Databricks

Monte Carlo

Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem. By design, data was less structured with limited metadata and no ACID properties. Since then, Databricks has aggressively moved toward allowing users to add more structure to their data.