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

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 115
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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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Unleash deeper insights with Amazon Redshift data sharing for data lake tables

AWS Big Data

Over the years, this customer-centric approach has led to the introduction of groundbreaking features such as zero-ETL , data sharing , streaming ingestion , data lake integration , Amazon Redshift ML , Amazon Q generative SQL , and transactional data lake capabilities.

Data Lake 101
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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 125
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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes. Azure Data Lakes are highly complex and designed with a different fundamental purpose in mind than financial and operational reporting. Data lakes are not a mature technology.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments.

Insurance 250
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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

In the context of comprehensive data governance, Amazon DataZone offers organization-wide data lineage visualization using Amazon Web Services (AWS) services, while dbt provides project-level lineage through model analysis and supports cross-project integration between data lakes and warehouses.