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

Ontotext

In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.

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What is a Data Mesh?

DataKitchen

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

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The steep cost of a poor data management strategy

CIO Business Intelligence

Such is the case with a data management strategy. That gap is becoming increasingly apparent because of artificial intelligence’s (AI) dependence on effective data management. For many organizations, the real challenge is quantifying the ROI benefits of data management in terms of dollars and cents.

Strategy 112
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The essential check list for effective data democratization

CIO Business Intelligence

Truly data-driven companies see significantly better business outcomes than those that aren’t. But to get maximum value out of data and analytics, companies need to have a data-driven culture permeating the entire organization, one in which every business unit gets full access to the data it needs in the way it needs it.

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How the right data and AI foundation can empower a successful ESG strategy

IBM Big Data Hub

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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The Benefits Of Doing A Data Maturity Assessment

Anmut

Data is becoming an increasingly important driver of business success, and organisations are recognising the need to manage and leverage their data effectively. However, achieving a high level of data maturity can be a challenging journey. What is a Data Maturity Assessment? How do you do a Data Maturity Assessment?