Remove Big Data Analytics Remove Data Quality Remove Data Silos
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Why Your Data Governance Strategy is Failing

Alation

Perhaps even more alarming: fewer than 33% expect to exceed their returns on investment for data analytics within the next two years. Gartner further estimates that 60 to 85% of organizations fail in their big data analytics strategies annually (1). Roadblock #3: Silos Breed Misunderstanding.

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

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A Guide to Clinical Decision Support Systems (CDSS)

Pickl AI

Here, we have highlighted the concerning issues like usability, data quality, and clinician trust. Data Quality The accuracy of CDSS recommendations hinges on the quality of patient data fed into the system. This can create data silos and hinder the flow of information within a healthcare organization.

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What is AIOps? A Comprehensive Guide

Pickl AI

Understanding AIOps Think of AIOps as a multi-layered application of Big Data Analytics , AI, and ML specifically tailored for IT operations. Its primary goal is to automate routine tasks, identify patterns in IT data, and proactively address potential issues. This might involve data cleansing and standardization efforts.