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

datapine

Working with a mix of historic (trend-based), real-time, and predictive insights, everyone on your team will be able to make valuable strategic suggestions, take active measures to spot any spiraling trends before they cause organizational damage, and keep on top of every process or operation with pinpoint precision.

Big Data 275
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Are You Harnessing the Power of SaaS BI Tools for Dynamic Data Access?

FineReport

Defining Business Intelligence and SaaS Business Intelligence (BI) encompasses the technologies and strategies used for data analysis and decision-making within organizations. On the other hand, Software as a Service (SaaS) refers to cloud-based bi software solutions that offer on-demand access to applications over the Internet.

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Understanding Data Drill Down And Drill Through Analysis And Their Role In Efficient Reporting

datapine

From automated reporting, predictive analytics, and interactive data visualizations, reporting on data has never been easier. Now, if you are just getting started with data analysis and business intelligence it is important that you are informed about the most efficient ways to manage your data.

Reporting 173
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Smart manufacturing technology is transforming mass production

IBM Big Data Hub

In smart factories, IIoT devices are used to enhance machine vision, track inventory levels and analyze data to optimize the mass production process. Artificial intelligence (AI) One of the most significant benefits of AI technology in smart manufacturing is its ability to conduct real-time data analysis efficiently.

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Buy Your Embedded Analytics and Empower Your End-Users With the Right Data

Jet Global

The value of embedded analytics is unmistakable. Application teams that embed dashboards and reports drive revenue, reduce customer churn, and differentiate their software from the competition. The challenge is collecting all that data into one place and making it understandable. What Are the Hidden Costs and Challenges?

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

CIO Business Intelligence

AI-powered data integration One of the most promising advancements in data integration is the integration of artificial intelligence (AI) and machine learning (ML) technologies. AI-powered data integration tools leverage advanced algorithms and predictive analytics to automate and streamline the data integration process.

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Debunking observability myths – Part 5: You can create an observable system without observability-driven automation

IBM Big Data Hub

Fact: Automation plays a crucial role in observability (and in any modern IT organization) High-performing IT departments tend to release software more frequently, and trying to keep up manually is neither sustainable nor scalable. This information is vital for capacity planning and performance optimization.