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The case for predictive AI

CIO Business Intelligence

All forward-thinking businesses are toying with or have already invested in AI — from boutique startups to enterprise conglomerates. It’s easy to think about these pieces of technology in two separate categories: one creates something new, the other forecasts future outcomes. AI is taking the world by storm.

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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.

Analytics 111
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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? After examining their data, UPS found that trucks turning left were costing them a lot of money. Big data enables automated systems by intelligently routing many data sets and data streams.

Big Data 275
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Operational Finance in the Age of Covid-19: Time to Change the Basics?

Jet Global

Not only have finance teams had to close companies’ books remotely, but they’ve also been required to provide the insight and information needed for some extremely complex decision-making, and continuously plan and forecast for events with little or no historical context. Tip 2: Improving accounts receivable procedures.

Finance 98
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The Impact of Healthcare BI Tools on Decision-Making and Patient Care

FineReport

Healthcare data governance plays a pivotal role in ensuring the secure handling of patient data while complying with stringent regulations. The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance.

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How OLAP and AI can enable better business

IBM Big Data Hub

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 58
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Business process management (BPM) examples

IBM Big Data Hub

And while enterprise resource planning (ERP) integrates and manages all aspects of a business, BPM focuses on its individual functions—optimizing the organization’s existing, repeatable processes end-to-end. BPM uses workflow automation to automate repetitive tasks such as data entry, reconciliation and report generation.