Remove Data Transformation Remove Finance Remove Metadata
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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

Datasphere goes beyond the “big three” data usage end-user requirements (ease of discovery, access, and delivery) to include data orchestration (data ops and data transformations) and business data contextualization (semantics, metadata, catalog services).

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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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How Your Finance Team Can Lead Your Enterprise Data Transformation

Alation

Because of the criticality of the data they deal with, we think that finance teams should lead the enterprise adoption of data and analytics solutions. Recent articles extol the benefits of supercharging analytics for finance departments 1. This is because accurate data is “table stakes” for finance teams.

Finance 52
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

Competitive advantage: As mentioned in the previous points, the bottom line of being in possession of good quality data is improved performance across all areas of the organization. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset. You might notice that this differs slightly from traditional ETL.

Analytics 111
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Empowering data mesh: The tools to deliver BI excellence

erwin

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Positive curation means adding items from certain domains, such as finance, legal and regulatory, cybersecurity, and sustainability, that are important for enterprise users. Increase trust in AI outcomes.

Risk 70