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Big Data

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Can Fossil Analysis Software Help Us Plan Curriculum?

August 20, 2014 by J. Kevin Byrne

Fossil analysis software.

Paleontologists use (free) software (known as PAST) for their statistical analysis. I bumped into it via key-word web-search to support academic planning I was doing. I offloaded it, took a close look, and I discovered I could use a specific menu within it (hierarchical analysis) to help reconceptualize curriculum at my design college.[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]

Lessons from How Amazon Uses Big Data

August 20, 2014 by MIKE20 Governance Association

Big data.

Entering the field of big data is no cake walk. Due to the many nuances of big data architecture combined with the fact that it’s so new, relatively speaking, it can be overwhelming for many executives to implement. Or, instead of being overwhelming, there’s simply a lack of experience and understanding. That misunderstanding leads management, all too often, to use big data inefficiently.[read more]

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How Big Data Is Changing Insurance Forever

August 19, 2014 by Bernard Marr

The Big Data Guru column.

Insurers such as Progressive in the US and Prudential in the UK are now pushing for wider acceptance of “telematics” devices, which feed back real-time data on a driver’s behaviour. So young drivers who can demonstrate that they keep within speed limits and do not brake suddenly too often, can pay less.[read more]

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Should the Entire Internet Be Encrypted?

August 19, 2014 by Shawn Gordon

Encrypt all the things!

Until the entire Internet is encrypting all its traffic, solutions like IceBrowser are a good way to protect yourself online. This isn’t about things as mundane as pornography; this is about protecting every piece of information and every footprint you leave out there.[read more]

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Dear Facebook, It’s Not You, It’s Us

August 15, 2014 by Tamara Dull

The Big Data MOPS Series.

Last week, we reached our 7-year anniversary mark. Have we really been together that long?! Because, honestly, it feels like forever. I’m sorry we didn’t celebrate, but I really didn’t feel like it. Ever since you asked me for my home address a few months ago, my feelings have begun to change. You crossed a line, dude.[read more]

A Pitfall to Avoid When Funding Big Data Analytics

August 15, 2014 by Bill Franks

Funding big data analytics.

If analytics are to continue to become more strategic and grow in impact to organizations, then there must be a mechanism to distinguish between IT costs that are truly overhead and those that can be tied to revenue. The costs of analytic systems must be directly associated not just with IT, but with the business processes and products they support.[read more]

The Future of Big Data Will Be Data

August 14, 2014 by Mark van Rijmenam

We live in exponential times, where new technological inventions are followed rapidly by innovative applications for consumers and businesses. The common denominator with all of these new applications is that they are generating vast amounts of data.[read more]

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Gigascience: A Science Journal That Provides Full Data Sets

August 13, 2014 by Hallam Stevens

Gigascience.

Gigascience’s data is useful because it is shared and open. More specifically, it is valuable because it is made available for use and re-use in multiple places and in multiple contexts. The rice genomes might now be used for formulating new rice strains in Africa or for comparison with tulip genomes in Holland.[read more]

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Little Data: The 25 KPIs Everyone Must Understand

August 12, 2014 by Bernard Marr

The Big Data Guru column.

Without good KPIs it is difficult to create good big data initiatives. I spend my work life helping companies around the world with their big data and KPI initiatives and have developed a list of top level metrics I consider global best practice examples.[read more]

How Big Data Can Help the Sales Team

August 11, 2014 by MIKE20 Governance Association

Sales.

There is still much progress to be made for sales teams looking to make use of big data. The potential is there, and those that have taken advantage of it are already seeing the great results. With a more effective sales team, businesses will prosper and be more productive, gaining new customers all the time while keeping the customers they already have.[read more]

3 Ways to Become a Data Scientist

August 8, 2014 by Linda Burtch
1

Data scientist.

To become a data scientist, you don’t need to have postgraduate degrees, or 20 years experience, or be proficient with every data-related technique and tool under the sun. What you need is to have enough baseline knowledge and experience, and the skill to constantly adapt and learn. Bootcamps, in our opinion, are the perfect medium for making the transition.[read more]

We Need an "Internet of Not Only Customers"

August 8, 2014 by Peter Perera

Internet for not only customers. 

The enduring purpose of a business is indisputably to create and keep customers. That bedrock was first famously laid down by Peter Drucker and Theodore Levitt sometime around the 1960s or ‘70s. Accordingly, CRM software vendors promote fixating on customers. SalesForce, for example, says create an “Internet of Customers” and become a “Customer Company.”[read more]

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The Latest Technological Phase and What IT Pros Should Do About It [INFOGRAPHIC]

August 7, 2014 by Rick Delgado

Big data architect.

In order to take advantage of the big data analytics mentioned above, there has been an increasing demand for data scientists who can make up a big data dream team. Members of this team perform different functions, but they all work together to run and use big data technology.[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]