Remove Data Lake Remove Data Processing Remove Sales
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How BMW streamlined data access using AWS Lake Formation fine-grained access control

AWS Big Data

The CDH is used to create, discover, and consume data products through a central metadata catalog, while enforcing permission policies and tightly integrating data engineering, analytics, and machine learning services to streamline the user journey from data to insight.

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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture. To achieve this, they plan to use machine learning (ML) models to extract insights from data.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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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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Enrich your serverless data lake with Amazon Bedrock

AWS Big Data

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging. About the Authors Dave Horne is a Sr.

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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

The DataFrame code generation now extends beyond AWS Glue DynamicFrame to support a broader range of data processing scenarios. This pipeline reads data from different Amazon S3 based Data Catalog tables, performs transformations on the data, and writes the transformed data back into an Amazon S3.

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Top 15 data management platforms

CIO Business Intelligence

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.