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Automating Model Risk Compliance: Model Validation

DataRobot Blog

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

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Rebranding IT for the modernized IT mission

CIO Business Intelligence

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications. What comes first: A new brand or operating model?

IT 73
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Cloud Analytics Powered by FinOps

Cloudera

Agility, innovation, and time-to-value are the key differentiators cloud service providers (CSP) claim to help organizations speed up digital transformation projects and business objectives. However, the reality is that the “move to cloud” is a turbulent flight for many of them. But FinOps is not only about cost management and control.

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Practical advice to optimize savings with cloud migrations

CIO Business Intelligence

Host Isaac Sacolick ( @nyike ) was joined by a bevy of consultants and practitioners who had no shortage of advice on the topic. Lacking a clear strategy determined by business objectives. Out of the gate, participants were asked what kinds of hidden costs organizations encounter when moving to the public cloud.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. They can help a company forecast demand, or anticipate fraud. There’s A Wealth Of Choice.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. Time Saving : Big data tools and technologies can collect and analyze data from multiple sources in real-time, enabling businesses to make quick decisions based on insights. It is scalable and secure to use.

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How Encored Technologies built serverless event-driven data pipelines with AWS

AWS Big Data

For example, the volume of data required for training one of the ML models is more than 200 TB. To meet the growing requirements of the business, the data science and platform team needed to speed up the process of delivering model outputs. The first step was to convert GRIB to the Parquet file format. northeast-2.amazonaws.com