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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

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The Differences Between Data Warehouses and Data Lakes

Sisense

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

With the right analytics approach, this is possible. In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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How Morningstar used tag-based access controls in AWS Lake Formation to manage permissions for an Amazon Redshift data warehouse

AWS Big Data

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. However, our consumers pushed us for better query performance and enhanced analytical capabilities.

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Modernizing the Data Warehouse: Challenges and Benefits

BI-Survey

Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. But what are the right measures to make the data warehouse and BI fit for the future? The following insights came from a global BARC survey into the current status of data warehouse modernization.

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

Jet Global

It sells a myriad of different software products, including a growing portfolio of software-as-a-service (SaaS) offerings. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements.