Remove Data Architecture Remove Data Transformation Remove Finance
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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Analytics 111
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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 115
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Empowering data mesh: The tools to deliver BI excellence

erwin

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

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The Chief Marketing Officer and the CDO – A Modern Fable

Peter James Thomas

If you don’t work in Marketing, then maybe a further transformation will convince you: Most [Chief financial officers] are brought in to instill a finance strategy across the business; once that is done their role should no longer be needed. It may be to build a new (or a first) Data Architecture.

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Unlocking Trino’s Full Potential With Simba Drivers for BI & ETL

Jet Global

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

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What Is Embedded Analytics?

Jet Global

Data Environment First off, the solutions you consider should be compatible with your current data architecture. We have outlined the requirements that most providers ask for: Data Sources Strategic Objective Use native connectivity optimized for the data source. addresses).