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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

After launching industry-specific data lakehouses for the retail, financial services and healthcare sectors over the past three months, Databricks is releasing a solution targeting the media and the entertainment (M&E) sector. Features focus on media and entertainment firms.

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How an Entertainment Giant with More than 20 million Subscribers Streamlined Reporting & Analytics

Data Virtualization

Reading Time: 3 minutes MultiChoice Group is a media and entertainment giant from South Africa that provides satellite television service with brands such as DStv and GOtv. With its Showmax brand, it also operates in the online subscription video-on-demand segment and competes with international.

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Unlock innovation in data and AI at AWS re:Invent 2023

AWS Big Data

million data points per second. F1 uses all that data with AWS to gain insights on race strategy and car performance. They also integrate some of those insights into the live TV broadcast to entertain and educate fans.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

This means the data files in the data lake aren’t modified during the migration and all Apache Iceberg metadata files (manifests, manifest files, and table metadata files) are generated outside the purview of the data. This can be a much less expensive operation compared to rewriting all the data files.

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Why You’re Not Ready for Knowledge Graphs!

Ontotext

Data integration If your organization’s idea of data integration is printing out multiple reports and manually cross-referencing them, you might not be ready for a knowledge graph. At any stage of the project, they’ll know if what they are doing is taking them closer or further from their goal.

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Entity resolution and fuzzy matches in AWS Glue using the Zingg open source library

AWS Big Data

In today’s data-driven world, organizations often deal with data from multiple sources, leading to challenges in data integration and governance. This process is crucial for maintaining data integrity and avoiding duplication that could skew analytics and insights.

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Comparing DynamoDB and MongoDB for Big Data Management

Smart Data Collective

You don’t get queryable backup on DynamoDB and you might need to manually recreate many configurations that are not backed up. DynamoDB is a bit more limited and complicated to manage as indexes are sized, billed, and provisioned separately from your data. MongoDB offers on-demand, continuous backups — as does DynamoDB.

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