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AI, predictive analytics top list of hot technologies for banks

CIO Business Intelligence

Among the hot technologies, artificial intelligence and machine learning — a subset of AI that that makes more accurate forecasts and analysis as it ingests data — continue to be of high interest as banks keep a strong focus on costs while trying to boost customer experience and revenue.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT). One group has declared , “IoT companies will dominate the 2020s: Prepare your resume!” trillion by 2030. trillion by 2030.”.

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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. According to a recent forecast by Grand View Research, the global serverless computing market is expected to reach a staggering $21.4 billion by 2025.

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Here’s How Big Data And Business Card Marketing Go Together

Smart Data Collective

They believe that advances in big data have made business cards, brochures and direct mail marketing obsolete. We previously published an article on the state of direct mail marketing. We showed that marketers are actually using big data to improve the performance of their direct mail marketing campaigns.

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Best Ways to Integrate Big Data into Your Business

Smart Data Collective

IoT Sensors generate IoT data. For example, predictive analytics detect unlawful trading and fraudulent transactions in the banking industry. This allows them to predict the goods that customers wish to see and target customers with more relevant and personalized marketing. Spotify is a good example.

Big Data 101
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Streamlining supply chain management: Strategies for the future

IBM Big Data Hub

On top of disruption, companies with global supply chains must also deal with different regulatory environments, cultural norms and market conditions. Big data and predictive analytics are increasingly being used to improve forecasting accuracy, allowing businesses to respond more effectively to changes in customer needs.

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How to Manage Risk with Modern Data Architectures

Cloudera

Up your liquidity risk management game Historically, technological limitations made it difficult for financial institutions to accurately forecast and manage liquidity risk. Financial institutions can use ML and AI to: Support liquidity monitoring and forecasting in real time. Apply emerging technology to intraday liquidity management.