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Data architecture strategy for data quality

IBM Big Data Hub

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

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Using Strategic Data Governance to Manage GDPR/CCPA Complexity

erwin

The complexity of regulatory requirements in and of themselves is aggravated by the complexity of the business and data landscapes within most enterprises. Creating and automating a curated enterprise data catalog , complete with physical assets, data models, data movement, data quality and on-demand lineage.

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2023 Predictions: Data Trends That Will Dominate Business Agenda in APAC

Cloudera

As more industries mature digitally and widely adopt AI and machine learning technologies, 2023 will be a pivotal year for organizations looking to deploy emerging tech solutions company-wide to fulfill business objectives. 1- Treating data as a strategic business asset .

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5 recommendations to get your data strategy right

IBM Big Data Hub

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. This requires a deep understanding of the organization’s strengths and weaknesses.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Sandipan Bhaumik (Sandi) is a Senior Analytics Specialist Solutions Architect at AWS.

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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. However, data mesh is not about introducing new technologies.