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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021.

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2020 Data Impact Award Winner Spotlight: Merck KGaA

Cloudera

It established a data governance framework within its enterprise data lake. Powered and supported by Cloudera, this framework brings together disparate data sources, combining internal data with public data, and structured data with unstructured data. We’d love to see your entry!

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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

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. The audience of these few reports was limited—a maximum of 20 people from management.

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The Rising Need for Data Governance in Healthcare

Alation

Storing the same data in multiple places can lead to: Human error: mistakes when transcribing data reduce its quality and integrity. Multiple data structures: different departments use distinct technologies and data structures. Data governance is the solution to these challenges.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!