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What is technical debt? A business risk IT must manage

CIO

What is technical debt? Technical debt is the cost accrued over time from technology implementation decisions that emphasize expediency over long-term quality and maintenance. Why is technical debt important? So, is technical debt bad? The question misses the point of its importance.

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Cybersecurity Snapshot: New Guides Offer Best Practices for Preventing Shadow AI and for Deploying Secure Software Updates

Tenable

Aim to provide a holistic view, and avoid using technical jargon. Aim to advise instead of to educate. You may find useful ideas in the Cloud Security Alliance’s new “ AI Organizational Responsibilities: Governance, Risk Management, Compliance and Cultural Aspects ” white paper. s cyber agency has found.

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The rise of the data lakehouse: A new era of data value

CIO

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). based Walgreens consolidated its systems of insight into a single data lakehouse.

Data 210
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Technical Feasibility in Software Engineering: Things to Consider Before Development Starts

Altexsoft

The authorities admitted that the previous 2024 deadline for human landing “ was not grounded on technical feasibility.”. Technical feasibility inspects whether software can be built at all with available tools and experts. In this article, we’ll concentrate on the technical side of feasibility that is our immediate area of expertise.

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CVE-2020-11651, CVE-2020-11652: Critical Salt Framework Vulnerabilities Exploited in the Wild

Tenable

Shortly after the public disclosure of critical vulnerabilities in the Salt framework, exploitation attempts were observed, as two open source projects were breached using these flaws. Salt utilizes a “master” server that controls agents known as “minions" that collect data for the system and carries out tasks. Background.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

ML apps need to be developed through cycles of experimentation: due to the constant exposure to data, we don’t learn the behavior of ML apps through logical reasoning but through empirical observation. Either paradigm is insufficient by itself: it would be ill-advised to suggest building a modern ML application in Excel.

DevOps 145
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Don’t let collation versions corrupt your PostgreSQL indexes

The Citus Data

As part of my work on the open source PostgreSQL team at Microsoft , I recently committed a new feature into PostgreSQL 14 to track dependencies on collation versions, with help from co-author Julien Rouhaud and the many others who contributed ideas. Reviewed-by: Peter Eisentraut (earlier versions) Discussion: [link].