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A step-by-step guide to setting up a data governance program

IBM Big Data Hub

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

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The Analytics Practices Startups Should Follow To Achieve Growth In 2022

Aryng

Misalignment between business objectives and success metrics is a common problem, especially as a start-up is in its journey of growing and evolving.

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3 things CIOs must do now to accurately hit net-zero targets

CIO Business Intelligence

However, the latest and largest UNGC-Accenture CEO study revealed that 91% of CEOs report insufficient technology solutions as a barrier to seizing opportunities in the net-zero transition, building resilience in their organization, and overcoming current volatility in the business landscape.

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Bringing an AI Product to Market

O'Reilly on Data

It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Agreeing on metrics. This is particularly true for AI products.

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KPI Management And Best Practices: How To Find The Perfect KPI Solutions?

datapine

An even more interesting fact: The blogs we read regularly are not only influenced by KPI management but also concerning content, style, and flow; they’re often molded by the suggestions of these goal-driven metrics. Ineffective management of KPIs means little actionable data and a terrible return on investment.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade.

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12 considerations when choosing MES software

IBM Big Data Hub

If you are experiencing inefficiencies, bottlenecks, quality control challenges or compliance issues in your production processes, an MES can provide real-time data and performance analysis across production lines to identify and address these issues promptly. Adequate training for your team members is crucial for successful adoption.