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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

In fact, by putting a single label like AI on all the steps of a data-driven business process, we have effectively not only blurred the process, but we have also blurred the particular characteristics that make each step separately distinct, uniquely critical, and ultimately dependent on specialized, specific technologies at each step.

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What is Data Mapping?

Jet Global

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

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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. Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data.

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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

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle.

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How Infomedia built a serverless data pipeline with change data capture using AWS Glue and Apache Hudi

AWS Big Data

Performance and scalability of both the data pipeline and API endpoint were key success criteria. The data pipeline needed to have sufficient performance to allow for fast turnaround in the event that data issues needed to be corrected.

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A Stitch in Time: How Jet Analytics Boosts Microsoft Fabric Time-to-Value

Jet Global

Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric. It offers a transparent and accurate view of how data flows through the system, ensuring robust compliance. I understand that I can withdraw my consent at any time. Privacy Policy.