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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

According to data from Robert Half’s 2021 Technology and IT Salary Guide, the average salary for data scientists, based on experience, breaks down as follows: 25th percentile: $109,000 50th percentile: $129,000 75th percentile: $156,500 95th percentile: $185,750 Data scientist responsibilities.

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Eight Silly Data Things Marketing People Believe That Get Them Fired.

Occam's Razor

It turns out that Marketers, especially Digital Marketers, make really silly mistakes when it comes to data. Small data. Here's why… Real-time data is very expensive. It is expensive from a systems/platforms/data processing/data reporting perspective. Focus on that, and you'll get big 5.

Marketing 166
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Digital Marketing & Analytics: Five Deadly Myths De-mythified!

Occam's Razor

Programmatic advertising is all the rage. Google's Adwords is perhaps the simplest example of programmatic advertising. I love the shift to intent-based targeting (I cannot stress how massively important to the future of advertising and marketing). Our advertising will rain down massive revenues! !" Does Yahoo!

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Product Management for AI

Domino Data Lab

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

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Five Key Elements For A Big Analytics Driven Business Impact

Occam's Razor

I was asked a few weeks back: " What companies should we proactively help with analytics, for free, so that they can make smarter data-influenced decisions ?" You got me, I am ignoring all the data layer and custom stuff! " That lead to this post. All that is great. When I come to work I know what matters.

Analytics 141
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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Keep in mind that data science is fundamentally interdisciplinary. Let’s look through some antidotes.