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Unleash deeper insights with Amazon Redshift data sharing for data lake tables

AWS Big Data

Amazon Redshift has established itself as a highly scalable, fully managed cloud data warehouse trusted by tens of thousands of customers for its superior price-performance and advanced data analytics capabilities. This allows you to maintain a comprehensive view of your data while optimizing for cost-efficiency.

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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.

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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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What I Learned At Gartner Data & Analytics 2022

Timo Elliott

First, data is by default, and by definition, a liability , because it costs money and has risks associated with it. To turn data into an asset , you actually have to do something with it and drive the business. And the best way to do that is to embed data, analytics, and decisions into business workflows.

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Gartner Data & Analytics Sydney 2022

Timo Elliott

For the last 30 years, whenever you want to do analytics, the first step is to rip it out of the operational applications and try and move it to a different environment—so data warehousing, data lakes, data lakehouses and now data clouds.

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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

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios.

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

Corinium

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. 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.

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