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Back to the Financial Regulatory Future

Cloudera

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.

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A Data Prediction for 2025

DataKitchen

The crazy idea is that data teams are beyond the boom decade of “spending extravagance” and need to focus on doing more with less. This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. ’ They are data enabling vs. value delivery.

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Top 6 predictions for AI advancements and trends in 2024

IBM Big Data Hub

These assistants, capable of handling numerous customer inquiries in real time, provided tailored responses based on individual customer data. Additionally, the retailer used IBM’s AI-driven summarization tools to efficiently analyze customer feedback and sales data, enabling swift and informed decision-making.

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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. Data enables Innovation & Agility. Risk Management. One of the more obvious use cases of data’s role in reducing risk is insurance policies.

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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.

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ISO 20022: Are your payment systems ready?

IBM Big Data Hub

Increased automation: ISO 20022 provides a more structured way of exchanging payment data, enabling greater automation and reducing the need for manual intervention, all of which help reduce errors and improve overall payment processing efficiency. appeared first on IBM Blog.

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

datapine

Winkenbach said that his data showed that “deliveries in big cities are almost always improved by creating multi-tiered systems with smaller distribution centers spread out in several neighborhoods, or simply pre-designated parking spots in garages or lots where smaller vehicles can take packages the rest of the way.”

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