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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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Overcome these six data consumption challenges for a more data-driven enterprise

IBM Big Data Hub

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle.

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Analyzing the business-case approach Perdue Farms takes to derive value from data

CIO Business Intelligence

But the more challenging work is in making our processes as efficient as possible so we capture the right data in our desire to become a more data-driven business. If your processes aren’t efficient, you’ll capture the wrong data, and you wind up with the wrong insights. How are you populating your data lake?

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Data Mesh 101: How Data Mesh Can Be Used in an Organization

Ontotext

Part one of this three-part series discussed the concept of data mesh and explored what it is and why an organization should care. Here, part two provides best practices for data mesh, including practical guidance, challenges, and limitations. Enterprises should identify and adopt specific data mesh elements to achieve velocity.

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AWS Lake Formation 2022 year in review

AWS Big Data

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

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Five benefits of a data catalog

IBM Big Data Hub

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.