Tag Archive | Big Data

How to Capitalize on the Golden Age of IT Innovation

How to capitalize the golden age of IT innovation

We have reached an inflection point within information technology (IT) where the conversation is moving from cost to value. IT is no longer focused on back-office infrastructure. In a digital world, the function has transformed to help unearth valuable data insights and define the future of products. Given the historical and deep knowledge with big data, security and infrastructure, the IT function plays an integral role in delivering delightful customer experiences across all digital platforms.

On a panel addressing how the Marketing and IT relationship has been reinvented, the more important one is the convergence between IT and marketing with the ability to take data capabilities in the IT organization and merge it with marketing aspirations. The Marketing and IT partnership is tighter than ever; both functions are working with synergy to implement and manage digital technology and leverage data insights to provide personalized experiences.

It is an exciting time in IT, from the role the function is playing in developing products and solutions to the new partnerships that are being forged to drive business impact. There are a number of fundamental tenets that will help IT leaders capitalize on the golden age of IT innovation:

  • Shift to a Services Model: IT leaders need to shift their organization from a delivery model to an end-to-end services model. Move from a project management and back-end infrastructure role to taking on the total cost of ownership in developing services that help drive the profits of a company. With this model IT specialists have an ongoing partnership with the business, product, and marketing organizations and are embedded into those teams.
  • Build New Skill Sets: The next generation of IT is re-defining the skill set and competencies of people in the organization. IT Specialists need to have an end-to-end services mindset where they work on smaller teams for longer periods of time and take a “you build it, you run it” approach. IT specialists also need to think more like marketers, as data is deeply embedded in the process of creating, targeting and delivering personalized experiences to customers.
  • Think Like a CEO: The CIO is in the unique position to see the entire spectrum of the company’s operation and business. As CIOs’ influence broadens, they must think like a 21st century CEO having a strong acumen around running a business (P&L), anticipating customers’ needs, innovating experiences, and understanding the competitive environment.
  • Entrust the Business: Leaders need to ensure they are prioritizing the projects that will truly drive business impact. Entrusting projects/initiatives to other groups or vendors is a very smart and strategic decision. By doing so, resources are freed up to focus on IT innovation and initiatives that help drive business revenue.

We should be energized by the opportunities that lie ahead in IT. Never before, the level of partnership and integration across the organization was higher than today. We are breaking down the barriers and silos and forging a new path for the next generation of IT.

Big Data: The Internet of Things


Science fiction? Well, no. All this and much more is feasible today. Internet-enabled white goods and wine coolers, remotely controlled lighting systems, alarms controlled from the internet, health reading devices and so on are all available today. Bringing them all together in a connected world is not the stuff of the future. It is in the here-and-now.

The Internet of Things is THE most exciting trend in the world can affect our daily lives. The trend is termed The Internet of Things (IoT) and it will affect every single human on the planet in time. It will allow connected cities, connected countries, more efficient allocation of resources and fundamentally change the way we live. It may even help us save the planet. It is that fundamental. And, according to one thought leader, 2014 will be the tipping point.

The market impact from the IoT is mind-boggling. Gartner believes that in just 6 short years the economic value-add from internet-enabling devices and delivering a connected world will amount to nearly $2 Trillion.

As it gains momentum the IoT is going to drive a tsunami of data. The growth in data that we have been experiencing in the last decade has largely been fueled by social media and unstructured content, with the proportion of enterprise data growth being relatively limited.

If businesses and governments are already struggling to keep up with data growth, and balancing the opportunities afforded with various cloud architectures, imagine what it is going to be like in 5 years’ time when they’ll be 500 billion connected devices all generating data! Some of this data will be ephemeral of course, but most will need storing, managing and mining.

In the last few years’ data storage as a topic has moved from an IT budget line item into a potential strategic enabler of growth. The CIO is keenly aware of this. However, as the tsunami of data hits, every C-suiter is going to need to understand this. NetApp has long been at the forefront of data storage efficiency technologies (such as snapshotting, de-duplication, compression and thin provisioning) and these will remain the foundation in this new world of IoT. There is no other way to address the need to store the quantity at an affordable cost. But it will also need highly sophisticated data analytics engines and mining applications. SAP Hana, Hadoop, MapR are just the tip of the iceberg. Making these apps effective requires a robust, highly scalable and performant underlying data management platform which can span private, public and hybrid clouds flexibly and transparently. The #1 storage operating system, Data ONTAP has been designed with these goals in mind from day 1. As every Sunday School attendee knows – the wise man built his house upon a rock, and as a every grown up CEO will get to know – the wise CIO builds his data center on a rock-solid data management platform.

50 years ago this week Isaac Asimov presented his vision of what the world might be like in 2014. Back in 1964 he outlined his predictions in an article for the New York Times. Asimov was a science fiction author and chemist, and although I don’t suppose anyone would have understood the term back then, he could well labelled a “futurologist” in today’s parlance. He was surprisingly accurate in those predictions. In some of them he was half-right and obviously he missed some completely, but in the main, he called a lot right. He may not have got the terminology completely correct but he essentially predicted the ubiquity of smart phones, the fledgling nature of robotics, the role of nuclear power and the advances in 3-D technology amongst many others. He predicted a world of wireless devices. By that he meant they would not use a conventional electrical cord and get power from a grid, but actually be powered by nuclear-charged long-lived batteries. Well he got those details a little wrong, but a world of internet-enabled wireless connected devices is precisely what we are talking about with the IoT. Read his predictions here. Given the rate of change in technology in the last decade, it would be pretty challenging to try and predict what the world might be like in 2064, so hats off to Asimov for his perspicuity.

WalmartLabs keeps getting smarter with Inkiru acquisition

 big data - data analysis

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Inkiru has developed an active learning system that combines real-time predictive intelligence, big data analytics and a customizable decision engine to inform and streamline business decisions

Predictive intelligence bought by WalmartLabs

Inkiru‘s predictive analytics platform will enable us to further accelerate the big data capabilities that @WalmartLabs has propelled forward at scale…including site personalization, search, fraud prevention and marketing. Walmart’s data scientists will now be able to work with big data directly and create impact faster than ever before.

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Walmart Labs Inkiru – A Funny Name for Serious Analytics (SiliconANGLE)

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By Derrick Harris (courtesy GigaOm)
Summary:WalmartLabs has acquired a predictive analytics startup called Inkiru to bolster its ability to create better customer experiences through data. The division of Walmart was created in 2011 on a foundation of big data.
Walmart, it seems, will not go gently into that good night when it comes to the company’s fight against e-commerce giant Amazon. It offered more evidence of its longevity on Monday, as WalmartLabs, the company’s division dedicated to developing new technologies for the web and mobile worlds, acquired a predictive analytics startup called Inkiru.

Inkiru, which has created software for real-time predictive analytics for things like customer targeting and credit risk, seems like a fine fit with the WalmartLabs mission. On mobile devices, for example, being able to deliver deals to customers at the right time and the right place is critical. Here’s how WalmartLabs characterized the fit in a press…

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Big data: barriers to its adoption


Underdelivering on expectations

IT and business leaders nearly universally believe in the value of big data, but many current projects are underdelivering on expectations, a survey indicates.

The survey by IDG Research and big data solution provider Kapow Software suggests that companies are having trouble gathering actionable business insights from big data fast enough.

The research also suggests the emergence of a new technology trend – the consumerization of big data.

Hopes and realities

While only one in three respondents have implemented a big data solution at present, nearly nine in ten agree that there’s huge value to be had from big data. And the pace of adoption is expected to double over the next 12 months.

IT leaders agree that the value of big data is its ability to help make intelligent business decisions and foster a data-driven organization.

Around 80% consider big data to be critical or very important for making informed business decisions. Almost as many believe big data is key to increasing competitive advantage, while 68% cite improving customer satisfaction.

Other popular uses for big data include increasing end-user productivity, improving information security and creating new products and services.

But of the companies that have adopted big data, more than 50% report having only lukewarm success.

The research suggests that big data projects are taking too long, costing too much and underdelivering on ROI. Most respondents believe that big data requires a prohibitively expensive investment in infrastructure.

Partly for this reason, big data projects typically take 18 months or more to complete, an eternity in the IT world.

Faced with these delays, employees from multiple parts of the business are taking it on themselves to attempt to mine insights from big data solutions. More than 80% of survey respondents report that manual data aggregation is being conducted in their business, with IT being tasked to try to automate these internal efforts.


Time and money aren’t the only barriers to big data adoption. Nearly half (43%) of IT leaders also report finding it difficult to find, access and integrate the right information among the piles of data needed. The data they require is often unstructured and spread across a wide range of internal and external sources.

A lack of awareness of the technology’s potential is considered the biggest barrier to big data success.

Furthermore, businesses are finding it difficult to wring value from big data without the presence of expensive data scientists or consultants.

Big data is mostly useless without employees with special training, and specialists are in short supply. Business leaders at the forefront of a big data project are often having to wait for their IT teams to extract insight using the complicated tools available today.

Demand is therefore springing up for simple but effective big data tools that can break down the barriers preventing big data from becoming a business rather than IT endeavor.

With consumerization transforming enterprise IT, users want the same user-centric approach to transform the tools they use, to help address the complexity barriers to big data utilization. More than half of IT leaders consider this a chance to become a business partner.

Tools with the ability to deliver insights in an accessible, easy-to-consume format have the potential to be more cost effective, to be deployed more rapidly and to avoid the expense and headache of a lengthy infrastructure rollout.

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Big data: data analysis revolution for when?


Keys data on Big Data summits

On Big Data, there are some summits every month in town from United States, Uk, Ireland, Germany and India.
In all of each, there are:
1. 80+ Industry Speakers,
2. 1000+ attendees,
3. 25+ hours of information given,
4. 50+ case studies proposed.

The last event in San Fransisco

The last conference in April 2013 gathered some of the greatest minds in the space; from Facebook , to LinkedIn , to Google , to Citibank, to the NYSE and eBay.

The event had attracted a fair amount of “Big Data Newbies,” lured by the prospects of a better performance or a better career. Statisticians wanting to get their hands around particular technologies or former database administrators curious about “what the business really cares about” came together to find out what was really hiding behind the “Big Data Hype”.

Big data is not so big

Gartner, In a recent podcast, explains how, despite the emphasis on large datasets, the term “Big” in “Big Data” could actually be irrelevant. “What is Big today, might be normal tomorrow,” Frank concludes. This is quite different from IDC’s definition, which puts the bar at a 100 Terabytes here. Frank’s point is difficult to debate. In fact, it broadens the spectrum for what should fall under the “Big Data” umbrella; and that’s a good thing. As an industry, if we want every company to realize their potential with data, we need to obsess less about the size of their databases, but rather, focus on their assessment of what “Big Data” is for them.

The 3Vs and Big Data: not married!

If you look at the genesis of the term “Big Data,” you’ll find that the industry often refers to the “3 Vs”: Volume, Variety and Velocity. The “3 Vs” have put a lot of emphasis on storage technologies to the detriment of the analytics field. If you look into the evolution of technologies supporting “Big Data,” you’ll find that storage is doing well but that analysis technology isn’t evolving as fast.Between 80s and 2010, Storage has seen a revolution: price divided by 30000 and capacity exponential. Analysis, at best, has seen an evolution but absolutely not revolution at all from now. The future revolution of big data is in its capacity to analyses the data automatically and without knowing completely what’s we search exactly, identify important links in between data and see new data inside big data. This is the challenge of 2010’s decade.

Related articles

1. http://www.forbes.com/sites/ciocentral/2013/04/22/big-data-isnt-about-big/
2. http://theinnovationenterprise.com/summits/big-data-innovation-summit-april-2013-san-francisco

Big Data Enthusiasts: Here’s What You Shouldn’t Ignore !


The analysis firm IDC says the world’s information is doubling every two years. With this rate of data production, it means that some of the data is falling by the wayside when it is not put to immediate use.

What is “Dark Data”?

What is “Dark Data”? It is different for each organization, but it is essentially data that is not being used to get a 360 degree view of a customer. For instance, a bank or retailer, that is only looking at transactional information or CRM database information to target a customer with a promotion — is only seeing part of the picture and understanding a fraction of the preferences of that consumer. The highly valuable data about who these customers are interacting with and what they are saying in social mediums — like how they feel about brands, what they are looking for, where they shop, their personal network, a customer service experience they had as they walked into a bank or store — is left dark.

Before You Maximize “Dark Data”, Know Your Data

Before diving in on how businesses can better harness “Dark Data”, first consider all the different types of data and how they benefit the company.

From the traditional business perspective, there is enterprise resource planning (ERP) that provides businesses with intelligence on how to manage and coordinate all the resources, information, and functions of a business; customer relationship management (CRM) that provides data on employees’ interactions with customers, clients, and sales prospects; and then the data warehouse that serves as a database that can provide historical (often aggregated) structured data, like point of sale (POS) figures, or can be used to help provide forward-looking reports based on trending data.

Next to those datasets, large consumer-centric companies have huge amounts of internal transaction and operations data, such as payments, calls, texts, digital TV activity, etc. This is a goldmine of information, but unfortunately few companies have the knowledge or resources to leverage this wealth of data when it comes to interacting with customers, attracting new customers, and improving relationships with the good ones.

This, combined with unstructured data generated from the web and social media, can hold a wealth of information on a consumer’s browsing preference. For instance, social networks that detail specific consumer preferences, interests and affiliations, and mobile technologies, such as geolocation or mobile wallet applications that when combined, can help businesses target a buyer on-the-go. In essence, there are billions of data points circulating at any given time.

If a business is not able to consolidate and consider data from all of these different fire-hose sources of information, simultaneously, then that business has a very limited and inaccurate view of the consumer. And while “Dark Data” will not entirely thwart business operations, it will cause a number of missed opportunities and leave a gaping hole in providing a 360 degree view of a customer.

How to Avoid Leaving Data in the Dark

As “Dark Data” continues to grow exponentially in every enterprise, here are a few tips to start shedding light on “Dark Data”:

  • Look to invest in a consumer intelligence solution that sits on top of these kinds of databases to search, index and provide real-time assessments of consumer activity. This will help ensure that your organization is getting a 360 view of a customer and acting on that intelligence in real time.
  • If mobile data is not feeding into your company’s overall business intelligence on the consumer, make it happen. Companies should be ‘meeting’ their consumers on their mobile devices and embracing — or at least preparing for a mobile wallet strategy, which is growing in popularity and adoption.
  • Embrace transactions from operational systems and your web traffic as valuable data. Combined with classic enterprise data (i.e. CRM, ERP) and with other Big Data sources (i.e. web traffic, social media), it can often reveal more relevant consumer data to help spur a sale or transaction and ignoring this information is leaving a gap in a true 360 degree view of the customer.

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