Remove Data Quality Remove Data Transformation Remove Forecasting
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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How does Data Virtualization manage data quality requirements? In forecasting future events.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

For that reason, businesses must think about the flow of data across multiple systems that fuel organizational decision-making. For example, the marketing department uses demographics and customer behavior to forecast sales. Business terms and data policies should be implemented through standardized and documented business rules.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. The offensive side?

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Sure, Trust Your Data… Until It Breaks Everything: How Automated Data Lineage Saves the Day

Octopai

They invested heavily in data infrastructure and hired a talented team of data scientists and analysts. The goal was to develop sophisticated data products, such as predictive analytics models to forecast patient needs, patient care optimization tools, and operational efficiency dashboards.

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An AI Chat Bot Wrote This Blog Post …

DataKitchen

In addition to monitoring the performance of data-related systems, DataOps observability also involves the use of analytics and machine learning to gain insights into the behavior and trends of data. ChatGPT> DataOps is typically used by organizations that rely on data analytics and machine learning to drive their decision making.

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Smart Factories: Artificial Intelligence and Automation for Reduced OPEX in Manufacturing

DataRobot Blog

As manufacturing plants start to inject autonomous machines into their day-to-day operations, there is a growing need to monitor these devices and forecast maintenance requirements before failure and downtime. Time-Series Forecasting?—? Over the past two years our supply chain has been in the spotlight.