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What Works - What Doesn't

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

What Works - What Doesn't

But AIops efforts can fail if businesses don’t understand its limits. Along with standalone AIops platforms, many IT observability, management, and monitoring tools integrate with AIops platforms or have added AI capabilities to their products. Continue reading with a free subscription to CIO.com.

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Five Tips: Hiring Freelancers to Polish an RFP Response

What Works - What Doesn't

On each case, both the client and I had the best of intentions but ran afoul of five systematic problems. But I can’t tell you how much time I spend on projects fixing things like improper capitalization, names of business units (it is “life sciences” or “health sciences”) and the like rather than the higher level work they’re paying me for.

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

What Works - What Doesn't

Instead, describe the three to five specific pain points you do the best job of solving. (In Too often, what passes for differentiation is a generic statement of end results (“We deliver true enterprise-wide protection against the threats facing your business.”) In security, for example, it might in the range of threats you track.

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

What Works - What Doesn't

MIT’s Sloan CIO Symposium always provides a strategic, high level overview of the business and technical challenges facing chief information officers. That means companies need a separate backup infrastructure to keep the business going in case their insurer turns their primary system into a virtual crime scene.