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Cloudera Lakehouse Optimizer Makes it Easier Than Ever to Deliver High-Performance Iceberg Tables

Cloudera

It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse. Let’s take a look at some of the features in Cloudera Lakehouse Optimizer, the benefits they provide, and the road ahead for this service.

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Integrating Data Governance and Enterprise Architecture

erwin

Why should you integrate data governance (DG) and enterprise architecture (EA)? Data governance provides time-sensitive, current-state architecture information with a high level of quality. Data governance provides time-sensitive, current-state architecture information with a high level of quality.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 114
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Doing Cloud Migration and Data Governance Right the First Time

erwin

That means your cloud data assets must be available for use by the right people for the right purposes to maximize their security, quality and value. Why You Need Cloud Data Governance. Regulatory compliance is also a major driver of data governance (e.g., GDPR, CCPA, HIPAA, SOX, PIC DSS).

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Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed.

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Build a transactional data lake using Apache Iceberg, AWS Glue, and cross-account data shares using AWS Lake Formation and Amazon Athena

AWS Big Data

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.