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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

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Data architecture strategy for data quality

IBM Journey to AI blog

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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How IBM HR leverages IBM Watson® Knowledge Catalog to improve data quality and deliver superior talent insights

IBM Journey to AI blog

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

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How Can The Adoption of a Data Platform Simplify Data Governance For An Organization?

Pickl AI

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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18 Data Profiling Tools Every Developer Must Know

Marktechpost

In addition, organizations that rely on data must prioritize data quality review. Data profiling is a crucial tool. For evaluating data quality. Data profiling gives your company the tools to spot patterns, anticipate consumer actions, and create a solid data governance plan.

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Rohit Choudhary, Founder & CEO of Acceldata – Interview Series

Unite.AI

My experience as Director of Engineering at Hortonworks exposed me to a recurring theme: companies with ambitious data strategies were struggling to find stability in their data platforms, despite significant investments in data analytics. They couldn't reliably deliver data when the business needed it most.

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Popular Data Transformation Tools: Importance and Best Practices

Pickl AI

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning.

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