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3 key digital transformation priorities for 2024

CIO Business Intelligence

In the 2023 State of Data Science and Machine Learning Report , only 18% of respondents said that at least half their machine learning models make it into production. Third, in the CDO Agenda: 2024: Navigating Data and Generative AI Frontiers , 57% of respondents haven’t changed their data environments to support generative AI.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

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10 things to watch out for with open source gen AI

CIO Business Intelligence

They might come out of data science teams, or skunkworks. This should fall under the responsibility of a company’s risk management team, she says, and the person who makes sure that developers, and the business as a whole, understands there’s a process is the CIO. It’s almost a way to mitigate risk.”

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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. There are at least four major ways for data scientists to find bugs in ML models: sensitivity analysis, residual analysis, benchmark models, and ML security audits. Sensitivity analysis.

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Transforming FSI in ASEAN with Cloud Analytics

CIO Business Intelligence

Its success is one of many instances illustrating how the financial services industry is quickly recognizing the benefits of data analytics and what it can offer, especially in terms of risk management automation, customized experiences, and personalization. .

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3 new steps in the data mining process to ensure trustworthy AI

IBM Big Data Hub

Model risk management. Again, data quality should be tracked by comparing the production data distribution to the data used to train the model. Often variables are correlated and bias can sneak in through one of the correlated fields, living as a proxy replacement in the model.

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4 Steps to Data-first Modernization

CIO Business Intelligence

The strategy should put formalized processes in place to quantify the value of different types of information, leveraging the skills of a chief data officer (CDO), who should form and chair a data governance committee. Data Security: Achieving authentication, access control, and encryption without negatively impacting productivity.