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"Cross-functional partnerships and high-impact targets are keys to success" says IDG Big Data survey - download and Computerworld review

31/7/2014

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"Big Data is getting even bigger, according to the results of a recent IDG Enterprise survey of over 750 IT decision makers. Nearly half of respondents say they're implementing big data projects, or are planning to. This represents a 5% increase over last year.

More than 20% report that their projects have already improved both the quality and speed of decision-making, and 59% said that improving decision-making quality was the top goal for these projects. Some 53% deemed making quicker decisions the primary driver.

That's not to say these projects are without challenges. Nearly 40% cited the skill shortage -- finding the right people -- as a top challenge to their big data initiatives, an issue that stayed the same across all sizes of company. Only 18% currently employ a data scientist, but 27% said they plan to hire for the position over the next 12 to 18 months.

Other key findings include:

20% plan to spend between $1 million and $10 million on big data projects in the next year; another 9% will invest $10 million or more...."

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"Big Data neither "Big" nor about Data" - video and article published in Datanami, Information Age, etc by Mike Fish, CEO BigData4Analytics

30/7/2014

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Click here for the version published in Datanami
Click here for the version published in Information Age
Click here for the 7 minute video version

"Many people ask why there doesn’t seem to be an accepted definition for Big Data in view of the massive press it receives. And given the amount of marketing effort expended by the global IT vendors who are targeting this bandwagon (and the venture-funded start-ups) they can be forgiven for being confused.

Just as most consumer marketing – curiously - is focused on adolescent buyers with a fraction of the purchasing power of their parents and grandparents, so it is with Big Data and its promoters. They shower their traditional customers – the IT departments - with buzzwords, while failing to engage with (or indeed, completely alienating) the business managers who have both the business problems that analytics can solve and direct control over the budgets.

Why is this, and what does it mean for Big Data adoption? The targeting of IT departments stems from both laziness and geekiness. Laziness, in the sense that - with few exceptions - these large vendors got to be large without needing to address directly the concerns of business managers – the IT departments they deal with have until now performed this translation task for them. Geekiness, in the sense that the smaller specialist vendors are often managed by technologists, and so their market messages - for reasons of background - also tend to focus on “speeds and feeds” rather than on solving practical business problems."


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'Big data must operate within data protection law,' says UK watchdog 'and here's how' - download report - ZDNet

30/7/2014

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"According to the Wikipedia definition, big data "is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process". The Information Commissioner's Office (ICO) also believes that big data is a large and difficult area — but for a reason other than its sheer size.

In its first report on big data (PDF), the UK's data watchdog sets out "how big data can — and must — operate within data protection law".

In particular, the report explains how the law applies when big data systems make use of personal information, with the aim of showing "which aspects of the law organisations need to particularly consider" while helping companies "stay on... the right side of the law and still innovate".

The ICO's 50-page report tries to tackle the key issues around big data and data protection — no mean feat, not least because many people see Big Data as being to a greater, or lesser, extent incompatible with data privacy."

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"When Is Big Data Analytics A Waste Of Time?" - Adrian Bridgwater in Forbes

30/7/2014

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"Industry analysts have predicted that there will be somewhere between 26 and 30 billion Internet of Things (IoT) devices by the year 2020. From personally wearable Fitbit-style activity trackers to electronically empowered fridges, toasters and front door bells… right through to industrial turbine sensors and all manner of corporate monitoring machinery, it’s for sure that we will have a lot of web-connected touchpoints.

More devices logically means more big data captured along the way. But will all that data be valuable data? Is there some way of assessing the inner worth of data so that we can treat it with appropriate worth and gravitas and potentially even trade with it?

Are we capturing some data now (just because we can), but not actually doing anything with it? Should we be recording the entire planet’s every (infinitesimally small) action today, just in case we need to execute some as-yet-uncovered analysis regime upon it tomorrow?

Most of all perhaps, when we do capture huge quantities of big data in a predetermined zone or area, at what point can say that we have reached “enough analytics”, at least for the time being?

The first law of big data usefulness:

"The degree to which we take the exact depth of big data analytics is directly determined by the corresponding level of insight it produces and where we can still say that we gain ‘productive incremental value’ from doing so."

This is the rarely uttered first law of big data usefulness. This law determines the point of diminishing returns where the analytics effort outweighs the potential gain. But enough theorizing already, this somewhat textbook definition is not that hard to grasp if we look at a practical example."
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"Big data tools deliver significant ROI in enterprise fraud prevention efforts"

29/7/2014

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"EY's Vincent Walden explains how to leverage big data analytics to detect fraud and to create a strong anti-corruption program. He also discusses the EY survey "Big risks require big data thinking." 

"In today's regulatory landscape, it is clear that the bar has been raised with respect to regulators' expectations of what constitutes an effective compliance program," write the authors of EY's 2014 Global Forensic Data Analytics Survey. Governments, both foreign and domestic, have access to the same analytical, disruptive technologies that private sector firms do. And they are using big data do their jobs.

A strong forensic data analytics (FDA) program, said EY senior manager Vincent Walden, can help a company not only meet higher regulator expectations for compliance, but also see a significant ROI concerning detection times for fraud and recoveries. It also sends a message, he added, when employees know that meaningful compliance is in place, and the C-suite and the board are watching.

EY's 2014 FDA survey suggests that companies may be playing catch up with their counterparts in regulatory agencies: While 72% of respondents believe that big data can play a role in fraud detection, only 7% could name a specific technology, and a scant 2% are using big data tools in their FDA. In addition, over 60% of respondents say they need to improve their anti-fraud procedures and improve management's awareness of the benefits of FDA."
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"Unlocking the power of 'big data' is the key to business success, says Grant Thornton managing partner Louise Evans"

29/7/2014

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"The pace of business change is moving so fast it has become crucial for managements of companies of all sizes to have the right information to hand at the right time to make those game-changing decisions.

The decisions I’m talking about here are those that will take any business forward and give it the best chance of succeeding in a world where possessing the competitive edge is key to growth and prosperity. And that’s a challenge for us all.

And at the very heart of those decisions, and the information required for managements to make the right call, is something that will become ever more important in the day-to-day lives of every business – Big Data!

Many companies will already have that data in their systems, without realising just how useful it could be to them in deciding what products and services to sell and to whom; how to win new markets; how best to innovate and forge new business development channels and, just as importantly, who not to do business with."
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"Big data and mapping – a potent combination"

28/7/2014

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"Businesses and organisations are learning the power of bringing together data and geographical context.

The emergence of Location Analytics tools is driving desire for the ability to discover location-based patterns and relationships from data that may exist in many disparate places, streams or web logs. Enabling us to visualise and analyse big data to reveal patterns and trends that would previously have remained hidden.

Bringing together maps and multiple data layers let you see the story behind your data. Retailers can see where promotions are most effective and where the competition is. In financial services, credit card companies are mapping data from transactional systems (RDBMS), customer information (CRM) and social media streams, to build more complete profiles of card users and their behaviours, to help shape outbound marketing strategies and fraud detection. Climate change scientists can see the impact of shifting weather patterns.

Spatially-enabled big data on a map allows you to answer questions and ask new ones. Where are disease outbreaks occurring? Where is the insurance risk greatest given recently updated census data? And by putting social media data on a map you can track dynamic behaviour and sentiment in real-time. The map becomes so much more than just a visual representation of your data."

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"The New Maths: Bringing Predictive Analytics into the Mainstream"

28/7/2014

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"How can banks predict and thwart complex fraud schemes involving dispersed participants? How can retailers correctly price products in real-time to target the preferences of select customers? How can companies predict the outcome of multi-faceted events such as merger and acquisition activity? And how can public health officials more accurately predict the progression and outcome of a disease? Proponents of predictive analytics say their discipline can provide the answers to these and many other questions for a range of industries, each eager for state-of-the-art tools to aid in decision-making and strategic risk management.

Predictive analytics is a practice that applies statistics, advanced mathematics and a mix of technologies to analyze large quantities of data and past events to identify patterns and build forecasts about future events. While only 13% of companies had a predictive analytics system in place in 2012, research firm Gartner projects that 70% of the most profitable companies will employ either predictive analytics or more real-time collaboration techniques to ensure competitive advantage by 2016.

Risk management teams are particularly seeking out these capabilities. A global survey conducted by the IBM Institute for Business Value found that 47% of organizations across industries now use predictive analytics to support business insight for risk purposes. “I was personally impressed with how many are using predictive analytics for risk management,” said IBM strategy and analytics expert Karen Butner."

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"Digital engagement and the market of one" - Financial Times

25/7/2014

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"In 2011, global software company Adobe had one of the most visited sites on the internet with more than 35m unique visitors per week. However, the company was not benefiting. Customers were directed elsewhere to purchase products, and visitors’ experiences depended entirely on their ability to navigate the screens.

Then Adobe built an integrated marketing and ecommerce site that could personalise product recommendations, promotions and content for each customer based on past actions and purchases, navigation profile and context, for example the customer’s physical location and device, such as smartphone or in-store kiosk, they are using.

The results? By 2013, Adobe’s online revenue had increased 39 per cent. Checkout conversions increased 16 per cent, with a 48 per cent increase in lead conversion and increased revenue per visit, according to Deloitte Tech Trends 2014.
Whether a company’s products and services are digitally based or not, direct interaction with customers is increasing, across platforms both digital and physical. And customers are increasingly willing to surrender more information to companies they choose, but they expect relevant and useful content, products and services in return.
After years of talking about monetising data, the relatively low cost of data capture, storage and analytics combined with the multi-platform, mobile experience of consumers and enterprise customers has finally provided both more data and the ability to do something valuable with it."


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"The rise of data and the death of politics" - The Guardian

25/7/2014

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"Tech pioneers in the US are advocating a new data-based approach to governance – 'algorithmic regulation'. But if technology provides the answers to society's problems, what happens to governments?

As both cars and roads get "smart," they promise nearly perfect, real-time law enforcement. Instead of waiting for drivers to break the law, authorities can simply prevent the crime. Thus, a 50-mile stretch of the A14 between Felixstowe and Rugby is to be equipped with numerous sensors that would monitor traffic by sending signals to and from mobile phones in moving vehicles. The telecoms watchdog Ofcom envisions that such smart roads connected to a centrally controlled traffic system could automatically impose variable speed limits to smooth the flow of traffic but also direct the cars "along diverted routes to avoid the congestion and even [manage] their speed".

Other gadgets – from smartphones to smart glasses – promise even more security and safety. In April, Apple patented technology that deploys sensors inside the smartphone to analyse if the car is moving and if the person using the phone is driving; if both conditions are met, it simply blocks the phone's texting feature. Intel and Ford are working on Project Mobil – a face recognition system that, should it fail to recognise the face of the driver, would not only prevent the car being started but also send the picture to the car's owner (bad news for teenagers).

The car is emblematic of transformations in many other domains, from smart environments for "ambient assisted living" where carpets and walls detect that someone has fallen, to various masterplans for the smart city, where municipal services dispatch resources only to those areas that need them. Thanks to sensors and internet connectivity, the most banal everyday objects have acquired tremendous power to regulate behaviour."


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