Remove 2021 Remove Cost-Benefit Remove Data Lake Remove Unstructured Data
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Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design

erwin

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data Modeling.

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2020 Data Impact Award Winner Spotlight: Merck KGaA

Cloudera

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Driving innovation with secure and governed data .

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. In 2021, cloud databases accounted for 85% 1 of the market growth in databases.

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Optimize data layout by bucketing with Amazon Athena and AWS Glue to accelerate downstream queries

AWS Big Data

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

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Celebrating Data Superheroes: The 2021 Data Impact Awards Winners

Cloudera

Every one of our 22 finalists is utilizing cloud technology to push next-generation data solutions to benefit the everyday people who need it most – across industries including science, health, financial services and telecommunications. Data Lifecycle Connection. It deals with all U.S. Security & Governance Leadership.

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. We also discuss the benefits Ruparupa gained after the implementation.

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How foundation models and data stores unlock the business potential of generative AI

IBM Big Data Hub

Organizations that utilize them correctly can see a myriad of benefits—from increased operational efficiency and improved decision-making to the rapid creation of marketing content. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? All watsonx.ai