Remove Data Analytics Remove Data Architecture Remove Data Transformation Remove Reporting
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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Flat files – Other systems supply data in the form of flat files of different formats.

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Introducing the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

The Amazon EMR TCO report with the new Amazon EMR design can demonstrate the Amazon EMR migration with detailed cost saving and business benefits. Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

The downstream consumers consist of business intelligence (BI) tools, with multiple data science and data analytics teams having their own WLM queues with appropriate priority values. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. This data is then used by various applications for streaming analytics, business intelligence, and reporting.

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Lay the groundwork now for advanced analytics and AI

CIO Business Intelligence

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

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“You Complete Me,” said Data Lineage to DataOps Observability.

DataKitchen

For example, a data error may only be apparent when combined with other data or used in a specific analysis or report. Additionally, data lineage may not capture the impact of data errors on downstream systems or processes. Which report tab is wrong? Which production job filled that report?

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