Remove customer

What Works - What Doesn't

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Enterprise Architecture in the Agile Era: Less Policing, More Coaching

What Works - What Doesn't

Modern agile enterprise architects start small, deliver value quickly, and collaborate with product teams. They try to deliver value quickly, work closely with product teams, and develop architectural principles rather than an inflexible list of platforms product developers are permitted to use.

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Enough About Us! How to Tune Pitch Decks for the Reader

What Works - What Doesn't

Of the hundreds of pitch decks I’ve seen as a trade press editor, too many left me waiting until slide 26 for a clue about the company’s value proposition, or even a clear description of their product or service. Customize More Carefully. Bare lists of customer logos. Context, context, context! Bare lists of brand name partners.

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What's on CIO's Minds: Data, Governance and of Course AI

What Works - What Doesn't

Such insurers will often insist a policyholder leave the hacked systems undisturbed and offline until their security experts determine what happened, said Jeff Reichard, vice president of solution strategy/product strategy at backup and recovery software vendor Veeam. Alex Singla, senior partner at McKinsey & Co.,

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3 Areas Where AIops Excels - and 2 Where It Still Falls Short

What Works - What Doesn't

But CIOs should not expect what some customers call “magic” results, such as automatically predicting and fixing any conceivable IT issue, or even just accepting any log or event steam and analyzing it without any data cleansing or normalization.

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ChatGPT Can't Replace Me. Yet. Maybe

What Works - What Doesn't

Most importantly, the ChatGPT content was not customized for the needs of my client, which has an offering in this space they need to discreetly promote. It found and spit back information about the chip’s security advantages, but didn’t find a more recent story about a hardware (and thus unpatchable) security flaw.

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Mine the Past for IT Thought Leadership

What Works - What Doesn't

What similar questions should we be asking about data lakehouses that we are not, and how should that affect product development, customer purchase choices and marketing? Security: The problem that keeps sucking up more money but never seems to get better.