Remove solutions roles data-analytics-architects
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CDAOs: The new disruptors accelerating AI maturity and adoption

Collibra

As a Chief Data and Analytics Officer (CDAO) or Chief Data Officer (CDO), you stand at the forefront of transforming data into a strategic asset. Today, a typical data use case can take 6 to 9 months to have an impact. The challenges are varied and complex – Data ownership across an organization.

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Architect to operationalize your sustainability goals

IBM Big Data Hub

While many companies utilize siloed software solutions to operationalize their environmental efforts, this introduces additional complexities and cost. Challenges arise when these software solutions need to be integrated in order to expose insights that could maximize their benefits.

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Ensuring data reliability for AI-driven success: The critical role of data engineers

Collibra

Trust in AI requires trust in data Data reliability is paramount for Artificial Intelligence (AI). Accuracy and trust in AI generated insights is directly dependent on the quality of the underlying data. Most commonly, organizations need to avoid modification of production data directly.

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Evaluating Collibra’s data intelligence maturity with our IDC Assessment tool

Collibra

To find, understand, and trust the data within your enterprise, it is essential to have sound data intelligence practices. The organization may rely on these practices to enable the end users to utilize data effectively. Our Collibra Data Office used our own Collibra Data Intelligence Assessment to do just that.

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What is metadata management and why is it important?

Collibra

Metadata management is a cross-organizational agreement on how to define informational assets for converting data into an enterprise asset. As data volumes and diversity grow, metadata management is even more critical to derive business value from the gigantic amounts of data. . Some consider metadata as “what identifies data.”

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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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What is data lineage and why is it important?

Collibra

Data lineage describes how data transforms and flows as it is transported from source to destination, across its entire data lifecycle. It helps organizations get the full story behind their data so they can use their data to make impactful business decisions. . Why is data lineage important? .

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