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The future of data: A 5-pillar approach to modern data management

CIO

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. Operational errors because of manual management of data platforms can be extremely costly in the long run.

Data 167
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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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United Airlines’ AI strategy: The airline that makes decisions fastest wins

CIO

Uniteds methodical building of data infrastructure, compliance frameworks, and specialized talent demonstrates how traditional companies can develop true AI readiness that delivers measurable results for both customers and employees. We also built an organization skilled in the data engineering and data science required for AI.

Airlines 124
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AI data readiness: C-suite fantasy, big IT problem

CIO

If youre spending so much time to keep the lights on for operational side of data and cleansing, then youre not utilizing your domain experts for larger strategic tasks, he says. Data hygiene, data quality, and data security are all topics that weve been talking about for 20 years, Peterson says.

Data 201
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Deletion Vectors in Delta Live Tables: Identifying and Remediating Compliance Risks

Perficient

Our Databricks Practice holds FinOps as a core architectural tenet, but sometimes compliance overrules cost savings. There is a catch once we consider data deletion within the context of regulatory compliance. However; in regulated industries, their default implementation may introduce compliance risks that must be addressed.

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From legacy to lakehouse: Centralizing insurance data with Delta Lake

CIO

Use mechanisms like ACID transactions to guarantee that every data update is either fully completed or reliably reversed in case of an error. Features like time-travel allow you to review historical data for audits or compliance. data lake for exploration, data warehouse for BI, separate ML platforms).

Insurance 164
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What is data architecture? A framework to manage data

CIO

To do this, organizations should identify the data they need to collect, analyze, and store based on strategic objectives. Ensure data governance and compliance. Choose the right tools and technologies.