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Streamline AI-driven analytics with governance: Integrating Tableau with Amazon DataZone

AWS Big Data

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and from third-party sources.

Analytics 119
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Scaling RISE with SAP data and AWS Glue

AWS Big Data

Customers often want to augment and enrich SAP source data with other non-SAP source data. Such analytic use cases can be enabled by building a data warehouse or data lake. Customers can now use the AWS Glue SAP OData connector to extract data from SAP.

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Addressing Data Mesh Technical Challenges with DataOps

DataKitchen

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility. Source: Thoughtworks.

Testing 246
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Amazon EMR 7.5 runtime for Apache Spark and Iceberg can run Spark workloads 3.6 times faster than Spark 3.5.3 and Iceberg 1.6.1

AWS Big Data

4xlarge instances, providing observable gains for data processing tasks. To minimize the influence of external catalogs like AWS Glue and Hive, we used the Hadoop catalog for the Iceberg tables. This uses the underlying file system, specifically Amazon S3, as the catalog. with Iceberg 1.6.1 and Iceberg 1.5.2.

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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246
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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.