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Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

AI-powered data integration tools leverage advanced algorithms and predictive analytics to automate and streamline the data integration process. AI-powered data integration solutions are particularly effective in handling complex, unstructured data sources, such as social media feeds, sensor data, and customer interactions.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts. Over the past decade, business intelligence has been revolutionized.

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Conversational AI use cases for enterprises

IBM Big Data Hub

The emergence of NLG has dramatically improved the quality of automated customer service tools, making interactions more pleasant for users, and reducing reliance on human agents for routine inquiries. These technologies enable systems to interact, learn from interactions, adapt and become more efficient. billion by 2030.

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Three Types of Actionable Business Analytics Not Called Predictive or Prescriptive

Rocket-Powered Data Science

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. This is predictive power discovery. Or more simply: given Y, find X.

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3 technology trends set to revolutionize retail

CIO Business Intelligence

These solutions leverage the latest advances in IoT and weighing scale and camera technologies to minimize or even eliminate friction, as they can precisely track the items customers add to their baskets and bill them when they exit the store. From 250 such stores in 2021, the study forecasts the number to touch 12,000 by 2027.

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PepsiCo transforms for the digital era

CIO Business Intelligence

To date the company has moved 5,000 applications to Microsoft Azure as it applies predictive analytics , AI, robotics, and process automation in many of its business operations. The company is also refining its data analytics operations, and it is deploying advanced manufacturing using IoT devices, as well as AI-enhanced robotics.

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Minimizing Supply Chain Disruptions with Advanced Analytics

Cloudera

In summary, predicting future supply chain demands using last year’s data, just doesn’t work. Accurate demand forecasting can’t rely upon last year’s data based upon dated consumer preferences, lifestyle and demand patterns that just don’t exist today – the world has changed.

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