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Big Data

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Data Lakes and Network Optimization: What’s Next for Telecommunications and Big Data

March 31, 2015 by Sameer Nori

Telecommunication. 

Relational data warehouses served communications service providers well in the past, but it’s time to start thinking beyond columns and rows. Unstructured data will be the fuel that powers risk management and decision-making in the near future. And to use all sorts of data to its fullest potential, we need new ways of storing, accessing and analyzing that data.[read more]

Why 2015 Will Be Year of Big Data: Oracle's Five Predictions

March 31, 2015 by Jenny Richards

Big data.

Long before the Internet and the inception of “big data,” Oracle has been dealing with big datatype loads through parallel databases. With the growing supremacy of personal and business data globally, many of the world businesses have turned their eyes towards the possible gains to their bottom-line that said data could contribute.[read more]

The Change You Can’t See, or What’s Your Horse Carcass?

March 30, 2015 by MIKE20 Governance Association

Horses.

This year has seen a return to the norm. Some of the hyped technologies like 3-D printing turn out to have more application in business than the home. Freed from looking to consumers, business has renewed confidence to innovate from the ground-up. This, in-turn, has the potential to accelerate innovation and enable disruptive rather than evolutionary trends.[read more]

Big Data Quality: What’s Old is New Again

March 29, 2015 by Gayle Nixon

Big data quality.

So many new applications and platforms offer sophisticated ways to analyze and manipulate Big Data, but they lack capabilities to adequately standardize, enrich and match complex data sets. As a result, organizations realize that they first have to ensure the reliability and quality of data lakes and enterprise data hubs before their contents can be utilized by any downstream applications.[read more]

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The Data Lake Debate: Questioning the Pro

March 27, 2015 by Anne Buff

The Data Lake Debate.

Technology is not the answer for every big data issue (well any data for that matter). I get it - Hadoop and the concept of data lakes are hot topics. However, just because they are trending in the world of technology does not mean that they will solve critical business issues such as taking full advantage of an organization’s data. I stand firm that data storage, data lake or any other type, is not the essential element for an organization to take full advantage of its data.[read more]

From Social Listening and Social Media Analytics to Social Data Intelligence

March 27, 2015 by Julie Hong

Christophe Folschette.

The early adopters who first saw the value of social listening and analytics were all communications specialists and early pioneers in digital marketing. But almost overnight, the sector exploded and went mainstream, across management silos in enterprises large and small, traditional and new. The birth of the digital native confronted corporates with a new set of challenges, and opportunities.[read more]

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Big Data: 6 Things a Data Scientist Can Learn from a Pastry Chef

March 24, 2015 by Bernard Marr

The Big Data Guru column.

Data analysis and chocolate cake? Cookies and data visualization? They don’t seem to have much in common — except that they might both show up at a board room table — but being an effective data scientist and a consummate pastry chef have more in common than you might think.[read more]

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Winning Strategies for Enterprise Mobile App Development

March 24, 2015 by Glenn Johnson

Mobile apps.

Enterprise mobile apps are being commissioned at a hectic pace across all industries, geographies and business processes. Employees see mobile apps as an essential means of resolving issues raised in phone calls, emails and other messages delivered by smartphones and tablets usually while the employee is ‘off site’ and ‘off duty.’[read more]

Awesome Analytics: Are We There Yet?

March 23, 2015 by Timo Elliott

Awesome analytics.

Despite decades of BI investment, executive reliance on gut feel has actually increased. A hot topic of Gartner BI research in the late 1990s was the increasingly large ‘fact gap,’ whereby the amount of data available for decisions was rapidly outstripping the available analytic resources. With some minor modifications, such as changing ‘Terabytes’ to ‘Petabyes’ and ‘Analytic Personnel’ to ‘Data Scientists,’ the picture looks remarkably similar twenty years later.[read more]

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The Data Lake Debate: Pro is Up First

March 20, 2015 by Tamara Dull

The Data Lake Debate column.

To data lake or not to data lake? That is the question du jour, precipitated by the big data tsunami that hit our enterprise shores a few years ago. Unfortunately, the answer to this question is not so cut-and-dried, as we can see by this small sampling of headlines: Gartner says beware of the data lake fallacy. Gartner gets the ‘data lake’ concept all wrong.[read more]

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Book Review: Bernard Marr's "Big Data"

March 20, 2015 by SDC Staff

Bernard Marr's book, Big Data.

This book takes a very complex subject and makes it accessible and easily digestible. It’s essential reading for anyone wanting to understand how data and analytics can improve their business. But it’s also an invaluable guide for data experts who struggle to communicate their knowledge to colleagues in the boardroom.[read more]

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5 Amazing Companies That Use Big Data to Drive Success

March 17, 2015 by Bernard Marr

The Big Data Guru column.

In this post I look at five companies which have emerged on the scene more recently, but which have built business models on big data and analytics. Some are quickly growing into household names, and some are still only known to big data insiders – but the profiles of all of these companies are likely to rise this year.[read more]

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Things You Might Not Know About Big Data [INFOGRAPHIC]

March 17, 2015 by Matthew Zajechowski

Big data.

Big Data comes from the 2.5 quintillion bytes of data that are created daily by everything from photos posted to Instagram to weather balloons, and it includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a reasonable amount of time.[read more]

Data-as-a-Service: Real-Life Examples of Companies Who Are Using DaaS to Boost Revenue

March 14, 2015 by Larisa Bedgood

Data-as-a-Service.

We’ve talked at length recently about the benefits of using Data-as-a-Service (DaaS) to target in-market consumers. DaaS is a process that leverages the modern data ecosystem and real-time data analytics to create a customized “always on” dataset. It is completely changing the game for today’s marketers, fueling customer acquisition and retention strategies for marketers across all industries.[read more]

Analytics and Exponential, Unpredictable Growth

March 13, 2015 by Bill Franks

Analytics.

Perhaps one of the biggest challenges with many sources of big data will be finding ways to take a scenario with exponential growth properties and figuring out how to filter and limit what is captured to transform the scenario into one of far less exponential, if not linear, growth.[read more]