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8 strategies for accelerating IT modernization

CIO Business Intelligence

Traditionally, such an initiative would involve business process analysis, a fit-gap analysis, and process re-engineering — all of which eats up time. Adopt a buy, not build, mindset IT has come a long way since those early years when it built all its own software in-house.

Strategy 140
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The art and science of data product portfolio management

AWS Big Data

As part of this practice, a gap analysis is conducted between the current and target data product portfolio, and a set of required actions and estimated time and effort prepared for review by the organization. Key deliverables include project management and software or service development deliverables and artefacts.

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What’s the Difference: Quantitative vs Qualitative Data

Alation

Easy to automate: Technologies, such as tracking software or social media analytics, offer consumable information without users having to engage in manual tasks. Although quantitative data is valuable, it also has several limitations or disadvantages, including: The data you need for the analysis needs to be: Available.

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Beyond the hype: Key components of an effective AI policy

CIO Business Intelligence

Assessment and gap analysis Amazon faced scrutiny when its AI-powered recruiting tool was found to exhibit bias against women. Identify gaps related to ethics, transparency, risk and compliance. This gap analysis will help pinpoint areas that need improvement as you craft your AI policy.

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In transition: How Kyndryl’s CIO weaned the company off IBM’s systems

CIO Business Intelligence

We didn’t do fit-gap analysis workshops because 95% of the time, the solution looks exactly like what the teams have today,” he says. “We We’re completely running in Azure or are software-as-a-service based.” We weren’t going to go down that path.” We now have no mainframe applications,” Bradshaw says.

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Security is dead: Long live risk management

CIO Business Intelligence

Information risk management is no longer a checkpoint at the end of development but must be woven throughout the entire software delivery lifecycle. They demand a reimagining of how we integrate security and compliance into every stage of software delivery.