Remove Data Lake Remove Metadata Remove Predictive Modeling
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Perform data parity at scale for data modernization programs using AWS Glue Data Quality

AWS Big Data

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Compare ongoing data that is replicated from the source on-premises database to the target S3 data lake.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

The business end-users were given a tool to discover data assets produced within the mesh and seamlessly self-serve on their data sharing needs. The integration of Databricks Delta tables into Amazon DataZone is done using the AWS Glue Data Catalog. The following figure illustrates the data mesh architecture.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models can use language, vision and more to affect the real world. Foundation models can apply what they learn from one situation to another through self-supervised and transfer learning.

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Announcing the 2021 Data Impact Awards

Cloudera

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. Data Security & Governance: Merck KGaA, Darmstadt, Germany — Established a data governance framework with their data lake to discover, analyze, store, mine, and govern relevant data.

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Of Muffins and Machine Learning Models

Cloudera

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

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The Cloud Connection: How Governance Supports Security

Alation

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. Pushing data to a data lake and assuming it is ready for use is shortsighted.