Remove Events Remove Experimentation Remove Metrics Remove Strategy
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Rebranding IT for the modernized IT mission

CIO Business Intelligence

At a recent Coffee with Digital Trailblazers event that I host on Fridays at 11 am ET, we debated not if but when and how top CIOs should rebrand and recast IT’s mission. A best practice is to include a recurring communication strategy , so executives see rebranding as not a one-and-done activity.

IT 108
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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

Nothing I can tell you about the importance of having an incredible mobile strategy will surprise you. If you look at the mobile marketing strategies, you will see they don't reflect this shift to mobile. Create a distinct mobile website and mobile app measurement strategies. Media-Mix Modeling/Experimentation.

Metrics 141
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10 digital transformation roadblocks — and 5 tips for overcoming them

CIO Business Intelligence

Digital transformation is not a one-time event but a continuous process. Develop a clear strategy: A clear strategy that outlines goals and objectives, timelines, and resources required is essential for digital transformation success. Digital Transformation, IT Leadership, IT Strategy

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Bringing More AI to Snowflake, the Data Cloud

DataRobot Blog

While this can be an excellent strategy for a future-oriented company, it can prove futile if you don’t maximize the value of your investment. According to Flexera 1 , 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy. launch event on March 16th.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

Still, there is a steep divide between rogue and shadow IT, which came under discussion at a recent Coffee with Digital Trailblazers event I hosted. That’s where an IT strategy that frames shadow IT as an opportunity for improved collaboration can have a profound impact.

IT 127
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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. 4) AIOps increasingly became a focus in AI strategy conversations. 2) MLOps became the expected norm in machine learning and data science projects.

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Higher-ed CIOs embrace academia’s AI challenges

CIO Business Intelligence

But we also have teams responsible for data analytics, and teams of audio-visual experts to ensure our concert halls and event centers can support a range of activities. We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We