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Predictive Analytics

Big Data and Ford's Faster Horses

September 15, 2014 by Arent van 't Spijker

Horse? Or horseless carriage?

In the late 19th century, a New York City planner put out a warning that by 1950 the city would be completely uninhabitable. The problem, as he saw it, was that at the current growth rates the city would not be able to sustain the growing number of horses.[read more]

Intelligence Input = Sales Output

September 3, 2014 by Ray Major

Test of time.

In my experience many tech professionals, especially the executive ranks, consider themselves forward-thinkers, early adopters, one or two steps ahead, dispensers of wisdom. “If companies or consumers would just take our advice and buy our product or license our app, businesses would run better, people would be happier.” Or some variation on that theme.[read more]

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Derailing Your Supply Chain BI Project

September 1, 2014 by Ray Major

Derailing a project.

Remind people that data doesn’t kill dreams. A Supply Chain Business Intelligence initiative is not a funeral service for their creativity. Quite the opposite, in fact. The insights they gain from BI will pave the way for the boldest, most creative options you’ve ever considered as a business.[read more]

Untangling the Retail Supply Chain with Real-Time Analytics

August 26, 2014 by Dale Skeen

Untangling the retail supply chain.

Retail supply chains are longer and more tangled than ever before – the complexity of the data sets and the management of far-flung suppliers coupled with high customer expectations around service and reliability are taxing traditional approaches to supply chain management to their limits.[read more]

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Spark the Flame: The Power Behind Real Time Analytics

August 26, 2014 by Gil Allouche

Real time analytics/Deviantart.net 

Real time data analytics is like a burning fire. Consider this analogy. Once a spark catches, several chemical and physical changes occur. The fuel (data) is processed while heat (or data outcomes) is simultaneously emitted. Once the process of data streaming begins, it is seamless and very efficient. The process will continue to be efficient as long as data is fed into the system.[read more]

How Big Data Enables Hyper-Local Real-Time Weather Forecasting

August 21, 2014 by Mark van Rijmenam

Weather forecasting.

Accurate weather predictions are very important for economic activities and with more extreme weather conditions happening, knowing what to expect could save a lot of money, and lives. Such hyper-local real-time weather forecasting is becoming more common every day.[read more]

Supply Chain Business Intelligence Is More Than Just Technology

August 20, 2014 by Ray Major

Supply chain BI.

Interestingly the technology implementation requires the most hard dollar costs, and returns the least in terms of ROI. The real value in Holistic BI is in garnering the corporate buy in or, in other words, training the people to make better data-driven business decisions based on the data.[read more]

Similarities and Differences Between Predictive Analytics and Business Intelligence

August 12, 2014 by Dean Abbott

Predictive analytics vs. BI.

BI and PA are important but complementary disciplines. BI is a much larger field and understandably so. PA is more of a specialty, but a specialty that is gaining visibility and recognition as an important skill set to have in any organization. Here’s to further collaboration in the future![read more]

From Human Screen to Machine: Predictive Analytics Helps Avoid a Major Point of Hiring Failure

August 11, 2014 by Mike Kennedy

Employees bring in revenue, rescue a customer, make your products, deliver goods, and sustain your profitability going forward. Identifying the right people, and avoiding the wrong ones, is an imperative to business sustainability. But how is initial candidate screening handled at your organization? Many employers take an approach that isn’t at all what we expected.[read more]

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Data Scientist: Sexiest Job on the Planet

August 7, 2014 by Ray Major

Data scientist.

If you paid close attention, you could see it coming. The tortoise eventually beats the hare, but it does take time. Allow me to make my case using the following more or less chronological, non-linear and highly selective history of the modern era.[read more]

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How to Create an OBIEE Dashboard Tutorial

August 2, 2014 by Julie Johnson

OBIEE dashboard tutorial.

This tutorial will show you the basic steps required to build an Oracle OBIEE dashboard. By building on these principles you will be able to create dashboards to meet the specific needs of your users and to give you instant oversight of your business data.[read more]

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3 Organizations That Can See the Future with Predictive Analytics

July 26, 2014 by Michele Nemschoff

Predictive analytics.

The ability to foresee the future would certainly be the ultimate competitive advantage. In reality though, no business has a crystal ball for making critical decisions. That’s why all critical business decisions have always carried a certain amount of risk. This risk has always and will always be part of the competitive game.[read more]

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The Amazing Ways Big Data Is Now Used in HR

July 22, 2014 by Bernard Marr

The Big Data Guru column.

Employees are a both a business’s greatest asset and its greatest expense. One company offering unique solutions to help others tackle this challenge is Evolv, and in this post I will have a look at what they do, and why it’s an important – but controversial - example of big data analysis driving business growth.[read more]

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How the Internet of Things Is Making Food Safer

July 22, 2014 by Rick Delgado

Food safety.

One area that stands to benefit greatly from the IoT is the food industry, more specifically making improvements in food safety. With advances in wireless technology and cloud computing, the IoT has the potential to make food safer from the farm all the way to the customer’s dinner plate.[read more]

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Data and Dating: How Agencies are Using Big Data to Find the Perfect Match

July 17, 2014 by Rick Delgado

Data and dating.

Dating agencies still have plenty of challenges to overcome to fully utilize big data. Sites need to work on fine tuning their algorithms to make better matches. They also need to find new ways to generate data, while filtering out data that is inaccurate or leads to less than satisfying results.[read more]