Remove Business Objectives Remove Data Quality Remove Data-driven Remove Measurement
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How to Build a Data Quality Strategy to Get Executive Buy-In

Octopai

BAAAAAAAAD data. Okay, maybe “less-than-stellar-qualitydata, if you want to be PC about it. But you see the “way-less-than-stellar” impact this data is having on your ostensibly data-driven organization. Tie data quality directly to business objectives. Better data quality?

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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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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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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Second, doing something new (especially something “big” and disruptive) must align with your business objectives – otherwise, you may be steering your business into deep uncharted waters that you haven’t the resources and talent to navigate.

Strategy 289
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6 strategic imperatives for your next data strategy

CIO Business Intelligence

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

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Best BI Tools Examples for 2024: Business Intelligence Software

FineReport

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

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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.

Marketing 362