Remove 2025 Remove Data Analytics Remove Data Enablement Remove Risk
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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. Enhanced Risk Management: better identify and manage risks, such as fraud, credit risk and operational risk.

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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? ’ They are data enabling vs. value delivery.

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

DataKitchen

are more efficient in prioritizing data delivery demands.” Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” Learn, improve, and iterate quickly (with feedback from the customer) with low risk. What if you took another perspective?

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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.

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How Can Manufacturing Data Help Your Organization?

Sisense

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. The world of data in modern manufacturing. Manufacturing companies that adopted computerization years ago are already taking the next step as they transform into smart data-driven organizations.

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How to choose the best AI platform

IBM Big Data Hub

.” When observing its potential impact within industry, McKinsey Global Institute estimates that in just the manufacturing sector, emerging technologies that use AI will by 2025 add as much as USD 3.7 It can also hamper scaling of ML processes, making results harder to reproduce and risking errors due to incorrect or incomplete data.

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

Andrew White

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Risk Management (most likely within context of governance).