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How does a data catalog work?

Alation

The post How does a data catalog work? The architectures of the past for BI and analytics – the Corporate Information Factory or the Bus Architecture – are now only one part of a complete analytical environment. Figure 1 gives you a good idea of […]. appeared first on Alation.

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Addressing Data Mesh Technical Challenges with DataOps

DataKitchen

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility.

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Streaming Ingestion for Apache Iceberg With Cloudera Stream Processing

Cloudera

Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets. This enables you to maximize utilization of streaming data at scale. The Catalog Type should be set to Hive. ssb_default`.`iceberg_hive_example`

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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. That is: (1) What is it you want to do and where does it fit within the context of your organization? (2) These changes may include requirements drift, data drift, model drift, or concept drift.

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Introducing Apache Hudi support with AWS Glue crawlers

AWS Big Data

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

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Extracting key insights from Amazon S3 access logs with AWS Glue for Ray

AWS Big Data

Customers of all sizes and industries use Amazon Simple Storage Service (Amazon S3) to store data globally for a variety of use cases. Customers want to know how their data is being accessed, when it is being accessed, and who is accessing it. With exponential growth in data volume, centralized monitoring becomes challenging.

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Unlock data across organizational boundaries using Amazon DataZone – now generally available 

AWS Big Data

Amazon DataZone enables customers to discover, access, share, and govern data at scale across organizational boundaries, reducing the undifferentiated heavy lifting of making data and analytics tools accessible to everyone in the organization. This is challenging because access to data is managed differently by each of the tools.