Remove 2010 Remove Big Data Remove Optimization Remove Reporting
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AI and ML: No Longer the Stuff of Science Fiction

Cloudera

The category “Data for Enterprise AI” awards companies from around the world that have built and deployed use cases for enterprise-scale machine learning and have industrialized AI to automate, secure, and optimize data-driven decision making and/or applications. Winner of the Data Impact Awards 2021: Data for Enterprise AI.

Data Lake 106
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An Overview of Sales Analytics in Event Industry

BizAcuity

With more and more information became readily available online in the mid 2000s, companies started taking advantage of it by leveraging big data analytics. Sales Analytics began to emerge as the scientific approach to selling in 2010 with sales becoming less about certain methodology or personality and more of a number game.

Sales 67
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Structural Evolutions in Data

O'Reilly on Data

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

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

Occam's Razor

In blue is how much time we spent in 2010 and in blue the time spent in 2014. was the dramatic shift between 2010 to 2014 to mobile content consumption. Dive into Mobile Reporting and Analysis. Dive into Mobile Reporting and Analysis. Dive into Mobile Reporting and Analysis. What do you learn from this report?

Metrics 141
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7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++

Occam's Razor

There are three elements to our "big data" efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis. We are all aware that the best companies in the world have an optimal DC-DR-DA allocation when it comes to time/money/people: 15%-20%-65%.

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The Artificial Intelligence Opportunity: A Camel to Cars Moment

Occam's Razor

From the ability to speed up discovery of new medicines to the unbelievable speed with which Machine Learning techniques are becoming particularly adept at diagnosis (think blood reports, X-rays, cancers etc.). In orange is a summary of what “Machines” and humans will be optimally suited for in the near-future. An example I love.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. A/B testing isn’t simple just because data is big — the law of large numbers doesn’t take care of everything! An efficient bandit algorithm for realtime multivariate optimization." 2015): 37-45. [3]