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A Data Prediction for 2025

DataKitchen

What will the world of data tools be like at the end of 2025? The crazy idea is that data teams are beyond the boom decade of “spending extravagance” and need to focus on doing more with less. What will exist at the end of 2025? Central IT Data Teams focus on standards, compliance, and cost reduction.

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ISO 20022: Are your payment systems ready?

IBM Big Data Hub

Real-Time Payments, for example, have widely adopted ISO 20022 across many countries, and Wire Payments networks are also announcing their support plans, including Fedwire, Lynx and SWIFT, by the end of 2025. Given these ISO 20022 payment scheme announcements, the question is: is your financial institution ready?

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

datapine

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries. Did you know?

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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

Data Engineering teams often deliver to one or more self-service teams in a hub and spoke or data enablement organization model. This idea sometimes means sh** flows downhill to the data engineer team from self-service teams – your team gets all the blame and none of the glory from delivering business value.

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How The Explosive Growth Of Data Access Affects Your Engineer’s Team Efficiency

Smart Data Collective

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

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How to choose the best AI platform

IBM Big Data Hub

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. This would be part of a Data Literacy program. Decision modeling (one of my favorites). And not just for synthetic data techniques.