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

CIO Business Intelligence

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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Key Data Trends And Forecasts In The Energy Sector

Smart Data Collective

Using Data to Understand the Future. Corporations need data to forecast the market’s future and the recent drop in the price of fossil fuels have invigorated alternative energy projects globally. According to a report by Capgemini from 2019, up to $813 billion is feasible if we integrate the necessary tech.

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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

Data professionals need to access and work with this information for businesses to run efficiently, and to make strategic forecasting decisions through AI-powered data models. Without integrating mainframe data, it is likely that AI models and analytics initiatives will have blind spots.

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Better Budgeting, Planning, and Forecasting With Bizview D365BC Connector

Jet Global

This applies to collaborative planning, budgeting, and forecasting, which, without the right tools, can be daunting on its best day. What holds us back from working smarter is the risk of integrating better tools that, although the tool is seemingly an improvement, runs the risk of throwing off your whole process. Bizview Smarts.

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Transforming Task Automation: The Future of Intelligent Orchestration

David Menninger's Analyst Perspectives

Integrating with various data sources is crucial for enhancing the capabilities of automation platforms , allowing enterprises to derive actionable insights from all available datasets. This ability facilitates breaking down silos between departments and fosters a collaborative approach to data use.

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Core technologies and tools for AI, big data, and cloud computing

O'Reilly on Data

Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. Temporal data and time-series analytics. Forecasting Financial Time Series with Deep Learning on Azure”.

Big Data 222
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Yogurt maker stirs in SAP to boost its demand planning capability

CIO Business Intelligence

More than 120 ‘flavors’ to handle When your company is dealing with today’s volatile market, a variety of products, and a supply chain covering 120+ countries – each with its own rules and processes – demand planning, including forecasting, can get a bit gut-wrenching. Such was the case with Danone.