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There’s a Knowledge Gap in the Market
he Middle East & Africa Banking and Finance industry is still in the early adoption stage when it comes to the use of Big Data. Mapping customer insights across the enterprise more effectively, Big Data enables a shorter analysis-to-decision cycle, offering greater revenue generation opportunities and competitive advantage. There’s a knowledge gap in the market on the implementation of big data; data architects and managers are struggling to find answers to cost implications, resource requirements, expectations management, and when and where to execute in their enterprise. Big Data and Analytics in Banking & Finance Conference serves the purpose to fill this gap. Over two days, the event will provide its participants the opportunity to learn, benchmark and network with over 100 industry leaders and experts. These essential new contacts and insights are aimed at ensuring delegates return to their organisation better informed on the best practices, real life strategies and with a brand new set of potential business partners. The conference has an unrivalled line-up of international and regional speakers from Barclays, Emirates NBD, HSBC Bank PLC, Kuwait Finance and Investment Company, London Stock Exchange, Master Data Management, National Bank of Fujairah, National Commercial Bank Saudi Arabia, Old Mutual Life Assurance Company, Royal Bank of Scotland, and Splunk. To further facilitate networking and end user engagement, delegates will take part in the exclusive Speed Networking feature on day one, allowing them to go back to the office with as many business cards as they can carry! And that’s not all, the Round Table sessions are designed to answer key questions, provide hard facts, and discuss strategies to create the perfect business case for future investment in big data projects. We wish all participants a successful conference and trust they will take away valuable opportunities that will benefit you and your business in years to come. ë
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Big Data for BANKING
Deriving value from Big Data Big data and analytics is increasingly proving to be a game-changer for the banking institutions operating out of the Middle East and Africa. It not only helps them gain better customer insights but also allows streamlining of operations, adding new revenue streams, and ultimately, scoring over the competition. n Photo: shutterstock
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he banking sector in the Middle East region is increasingly embracing big data and analytics, serving as a bellwether for consumer facing industries eager to create a single view of each customer, serve and retain them, attract additional business, better manage risk, and mine new revenue streams. For years, banking institutions have collected reams of information on their customers – be it the transactions, account activity, loan portfolios and credit card balances that are their lifeblood. And they convert much of this data into monthly, quarterly and annual reports for use by their customers, risk managers and auditors. This sector is currently starting to look towards big data solutions in order to maintain their customer base (via things like real-time customer experience management), increase their profitability and real time fraud management solutions. “Banks are very optimistic about big data. There is strong credit demand in the Middle East and it is bound to increase the data by many folds. There is a very strong influence from social media on brand reputation and visibility. Banks today have accumulated volumes of data from the last few years and are looking forward to deriving insights from it using big data technologies. These technologies will allow banks to harness the power of analyzing data across functions to drive its relevance and correlation with their business behavior,” asserts Shashikanth N, Data Practice Specialist, Data Science Technologies. According to Mahmoud El Kordy, Big Data and Analytics Leader, IBM MEA, the Middle East’s financial leaders must approach big data as a sought-after commodity which powers a range of industries. In this case, financial organizations already own much of this new resource in the form of transaction logs, customer histories, and performance records across existing products and services. The main challenge is implementing the technical systems and processes to convert existing data into insights that can inform how banks and service providers go about their business.
Current level of adoption Big data and analytics have started drawing investments in the MEA region. Apparently, there have been success stories demonstrating the benefits of big data within banking institutions. “Investment has started, under no uncertain terms. Banking institutions have already deployed, in varying degrees of complexity and size, big data solutions, but more importantly, there is a distinct interest from key decision makers in such technologies, as big data projects
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have started to reach the boardroom as strategic initiatives,” says Stephan Geyer, Regional Sales Manager, Software AG. Mario Gay, General Manager, Mindware, adds, “Big Data is becoming a growing trend in the market from the perspective of data analytics and predictive analytics. And these analytics have to be driven not only by ERP type of data that are available in our systems but need to be integrated with external data that can be retrieved from multiple sources. There is definitely an increase in the adoption rate in the MEA region. It is being highly driven by storage availability and exponential growth of information on a daily basis.” However, Raj Wanniappa, General Manager – Big Data, Dimension Data Middle East and Africa, is quick to point out here that the banking sector in the MEA region has acknowledged the benefits of big data practices but is yet to invest significantly in its application. Both large and small banks as well as micro-lenders are considering or have implemented big data projects to increase revenue and decrease operational costs. And it is not only the large banks that are forging ahead in this direction, even the local banking institutions are in the race of adopting big data and analytics. Smaller banks are looking at strong use cases to start adoption but will not lag behind given that computing power and cloud environment are very much affordable. “Whilst MNC banks have made quite important strides towards big data-related investment at a global level, both large and local banks in the MEA region have pretty much stood close together in terms of adoption. This balance between local banks and large multinational banks is particular to this region as local banks have as much power and support as larger international banks do due to the wealth of the region. It is also worth noting that local banks in the Middle East stand out for their innovative outlook towards technology, a very important element in the topic of big data adoption,” points out Geyer. Adding further, Wanniappa states that whilst large banks including MNCs have the necessary resources – money and skills, architectural challenges make it difficult to get quality data required for big data analysis including the mashups between structured (customer billing), semi-structured (email) and unstructured data (social media). At this stage, smaller/tier 2 banks and micro-lenders are more likely to benefit quickly from big data technologies especially if deployed in a cloud environment – Big Data as a Service.
Business benefits Banks need to move from analysis to action. Technology can help banks in their quest to derive genuine strategic insight from big data, and ultimately unlock its true potential. However, big data includes structured, semi-structured, and unstructured data, and not all data is equal in terms of its value or meaning, or how it should be managed. Banks that master this can become leaders in customer service, take steps towards sustainable growth and respond more rapidly to compliance and regulatory demands. Banking sector is increasingly looking to find actionable insights from their data. Many big data projects originate from the need to answer specific business questions such as what customers really think about their brand, and how can they increase the sales intelligence and close more deals. With the right big data analytics platforms in place, banks can boost sales, increase efficiency, and improve operations, customer service and risk management. “If used judiciously, big data can alleviate many of the pressures currently facing the banking sector in the Middle East. Real-time access to customer data and profiles can allow service representatives to tailor their responses and solutions on an individual basis, significantly boosting the levels of trust and efficiency felt by customers. Applying analytics to churn data can similarly help institutions streamline the products and services they offer, pruning less efficient ones while enhancing others. Big data’s potential dividends, however, go far beyond efficiency gains for existing operations. Data could very well transform the way financial transactions are conducted and sustained throughout the Middle East – as it has already begun to do elsewhere in the world,” explains El Kordy. Furthermore, Shashikanth adds, “Banks need to make decisions every minute, from making decisions to make a targeted marketing offer to underwriting risk of an applicant, approving a credit over limit for a credit card user & address collection risks. It is virtually impossible to make these decisions in traditional ways. Banks can now use Big Data technology to deeply understand consumer behavior and gain insights into patterns depicting spending, profiling, travel, shopping and brand preferences associated with specific profiles. Apart from this, technology allows the institutions to better interact with their consumers, maintain a healthy margin on products and enhance the overall experience of banking. It also allows to them continuously monitor their asset quality and external influences on asset risk, thus allowing lower provisioning and enhanced liquidity.”
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T IN EA
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Data Practice Specialist, Data Science Technologies
Mahmoud El Kordy
Big Data and Analytics Leader, IBM MEA
Stephan Geyer Regional Sales Manager, Software AG
“Banks today have “For many CFOs, the accumulated volumes of question now is how data from the last few years exactly to harvest and and are looking forward leverage big data in their to deriving insights from it using big data technologies” day-to-day business to gain a competitive advantage”
“Banks have harnessed big data in order to get closer, in a more context-aware way, to their customer base, allowing their brand to be better recognized”
stand, in right-time and in context, how to better serve their customers as well as to better reach potential new customers. Being able to react to changing customer patterns can mean the chance to reach a customer with a time-limited, location aware, and context aware offer, but also to stop a fraudulent transaction from taking place. Additionally, banking institutions can also leverage big data and analytics to get informed on delinquent accounts, recovery of bad debt, and at the same time, reduce costs. Shashikanth too believes that banks can today predict the likely hood of someone going default by matching patterns based on the profiles’ past behavior. This allows the bank to proactively manage probability of default for an account. Analytics will assist banks in identifying these customs upfront to a reasonable level of accuracy with which they then can design new strategies to address these accounts ahead of them going delinquent. Also, we can design as to what are the low cost channels to reach out to these customers and ensure that genuine customers do not get called, thereby saving costs. New or revised regulatory requirements, accounting standards and risk management
practices can now be automated and streamlined, thereby reducing or eliminating cost and administrative burdens. Fraud detection and supply chain improvements can also benefit from prescriptive analytics-driven programs. Automated decision making and other analytics-driven competencies have a track record of generating higher revenues in a faster time frame and at a lower cost. These tangible results are opening the eyes of even the most conservative executives, who are prying open their vaults for additional investments in big data that can positively affect financial performance. “Banks can combine internal client data such as credit history, income patterns and more with external unstructured data such as their clients’ activities in social media, to get a more holistic view of their credit worthiness. By using predictive analytics, lending institutions can pre-empt clients from defaulting through instituting appropriate interventions. Once bad debt has incurred, prescriptive analytics can be used to guide debt collectors on the cost benefits of proceeding with the debt collection process,” highlights Wanniappa. In addition to the significant benefits big data
Moreover, analytics-enabled banks are seizing on a golden opportunity by using structured (existing customer and account profile data), semi-structured (social media content) and unstructured (customer support audio files, customer transactions) data to generate incremental business, reverse attrition trends, meet stringent regulatory requirements and establish more meaningful customer relationships. Enhancement of customer experience Besides leveraging traditional predictive analytics, many of the banks in the MEA region have started to eagerly tap into big data and predictive analytics to improve the customer experience, bolster incremental revenue or better manage risk. For banking analytics to be truly effective, it should help banks operate horizontally across the enterprise, rather than narrowly, viewing one business unit at a time. This is often difficult because infrastructures were designed to work vertically. The 360-degree view of customers that analytics enable is essential for meaningful customer relationships and business growth. Geyer is of the view that big data technologies are already being used to find behavioral patterns in their markets allowing them to better under-
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General Manager – Big Data, Dimension Data Middle East and Africa
General Manager, Mindware
brings to the customer experience, this technology can also be used to generate cross-organizational efficiencies. For example, many banks use analytics to construct and implement a thorough compliance management program. Competitive advantages By adopting big data and analytics, banking institutions do get many competitive advantages. While putting a check on the attrition rate of the customers, banks can also convince them to prefer their products rather than those of competition. And on the basis of the customers’ feedback, the banks can come up with innovative offerings catering to the market requirements. “Banks across our reference spectrum have harnessed big data in order to get closer, in a more context-aware way, to their customer base, allowing their brand to be better recognized. Also, banks have the opportunity to explore potential revenue-generating streams that they were not looking into. It allows banks to broaden their horizons beyond traditional markets,” says Geyer. Meanwhile, big data and analytics not only helps CFOs in managing their day-to-day
operations but also in dealing with investments in the market as well. The areas where the technology will come in handy for CFOs include management of cash flow, budget planning, and investment choices in treasury and external market instruments. Also, the technology allows them to gain market insights, which in turn, helps in taking decisions according to prevailing conditions and better scenario planning. And not only the external factors, banks can improve their internal performance as well and accordingly take proactive decisions. “For many CFOs, the question now is how exactly to harvest and leverage big data in their day-to-day business to gain a competitive advantage. Banks that can harness big data in the form of transactions, real-time market feeds, customer-service records, correspondence and social media posts, can derive more insight about their business than ever before and build competitive advantage,” mentions El Kordy. Challenges in dealing with Big Data Despite deriving numerous benefits as well as gaining competitive advantage with the
“There is definitely an “Both large and small increase in the adoption banks as well as microrate of big data in the MEA lenders are considering or region, which is being have implemented big data highly driven by storage projects to increase revenue availability and exponential and decrease operational growth of information on a cost” daily basis”
deployment of big data and analytics within their premises, banking institutions still face certain challenges while dealing with this technological advancement. Both the technology vendors and service providers are quick to point out here some of the issues being faced by the banks in the MEA region. According to El Kordy, the main challenge is implementing the technical systems and processes to convert existing data into insights that can inform how banks and service providers go about their business. Dealing with larger amounts of unstructured data, such as social media and written customer service reports, continues to be a challenge for banks. Similarly, Geyer believes that the first challenge that banking institutions face is the paradigm change that big data requires, as it forces decision makers in banks to look outside of the traditional banking means of penetrating markets in order to step ahead of the pack. This change in paradigm usually translates into a difficulty to calculate the ROI in rolling out these solutions. The second big challenge is in-house expertise and training. For Wanniappa, large banking institutions’ IT architectures do not readily allow for the easy access of data sets for analysis. The data models across various applications (e.g. transactional products vs. credit) are very diverse making it difficult to do proper predictive or prescriptive analytics. While those issues are being addressed, banks can focus on using big data for cost optimization by analyzing their entire value chain across their banking products. Echoing his views on the same, Shashikanth quickly points out that data sources are disparate, data is not standardized and legacy systems are not capable of holding complex analytical data marts. Also, skilled resources will be another challenge that banks will face to keep up the pace. Finally… Big data initiatives are likely to grow within the banking sector, as they seek better, more costeffective ways to derive meaning from big data. While some banks are primed for success and will utilize data to develop more sophisticated analytical tools, those who are left behind are very likely to miss valuable insights about their customers, and ultimately lose revenue. To move forward, banks should transform their approach to data and analytics from traditional, product-focused marketing programs to a 360-degree customer-focused approach. They should also strive to break down longstanding silos, invest in state-of-the-art IT systems, hire business-savvy quantitative analysts and data scientists, and integrate their operations to see the real potential in data. ë
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case study William Ruh
vice president and corporate officer of the center, GE.
“As a global hub in terms of the economy, commerce, tourism and more, Dubai has an unmatched infrastructure that will only be enhanced with the added convenience that comes with mGovernment applications.”
How GE is Building Big Data, Software and Analytics In 2012, GE CEO Jeffrey Immelt announced that the company would commit $1 billion to its analytics and software center over four years. That would put the company in the top 9% of our survey sample in Big Data and
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eneral Electric Co. (GE) is known for making what it refers to as ‘big swings’ –large bets to grab the lead in emerging markets with enormous potential. The $145 billion manufacturer of jet engines, power plants, and locomotives believes Big Data and analytics is one of these markets. How big an opportunity GE sees with Big Data, how much and where it is investing, and how it’s marshalling its expertise to provide lessons for many companies, even much smaller ones. In 2011, the Fairfield, Connecticut-based industrial giant announced the launch of a global software center and a $1 billion investment to build
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software and expertise for GE’s version of Big Data analytics. “What we’ve done is centralized what I would call the real rocket science of Big Data,” says William Ruh, vice president and corporate officer of the center. “These are people with deep expertise and experience. We use them to develop the very most complex capabilities and reusable components.” GE brought in Ruh from Cisco Systems in 2011 to lead the center, located in San Ramon, California. That’s a short drive from Silicon Valley, an emerging epicenter of Big Data startups and established technology companies. Ruh’s charter is to build a center that powers up software development and data science capabilities in GE’s Big Data domain of interest – a niche it refers to as ‘the industrial Internet’. By this, the company means the torrent of digital data emanating from sensors and other digital devices embedded in machines such as GE’s jet engines, turbines, trains, and hospital MRI equipment. Revenue of those GE businesses totalled $94 billion in 2011, nearly two-thirds of total sales. Harnessing such data would enable GE to help customers identify maintenance problems before they occur, improve fuel efficiency, and make other operational improvements that could add up to trillions of dollars in savings. To put it succinctly, it’s about “making machines more intelligent and getting data to right people in real-time,” as Ruh explains. The digital data that GE could collect through such sensors would be gigantic. Ruh says a typical GE gas turbine generates 500 gigabytes of data daily. With 12,000 of them in service, that “certainly becomes Big Data,” he explains. GE’s gas turbines and other utility power equipment power a quarter of the world’s electricity. But that isn’t the only sensor data the company has in mind. GE is designing its next wave of airline jet engines to eventually capture information on engine performance for every flight. This will result in GE gathering a huge amount of aircraft engine information – in fact, more in one year than in the 96-year history of its aircraft engine business. With this and other data it plans to collect and analyze, the word “Big” may be an understatement when GE says “Big Data.”
Where GE Sees the Payback In 2012, GE CEO Jeffrey Immelt announced
that the company would commit $1 billion to its analytics and software center over four years. That would put the company in the top 9% of our survey sample in Big Data and analytics investments2. While a sizable amount, it’s a small down payment on what GE envisions as a $30 trillion opportunity by 2030. Using what it believes to be a conservative 1% savings in five sectors that buy its machinery (aviation, power, healthcare, rail, and oil and gas), a GE report3 estimates the savings from an industrial Internet for these sectors alone could be nearly $300 billion in the next 15 years. Take the aviation industry. A 1% boost in fuel efficiency would put $2 billion a year into airlines’ coffers. A growing percentage of GE’s business is services that support its industrial products –services that help customers use GE’s machines more effectively and efficiently. Providing insights based on Big Data will be one more service offering. “We believe this is a foundational change, in the same way that the consumer Internet has remade consumer industries in the past decade,” Ruh told us. “Who does Walmart view as its competitor? Amazon? Who does American Express see as its competitor? PayPal. In the next 10 years, the changes that we saw in the consumer Internet will happen in the industrial world.”
Why GE Has Centralized Big Data and Analytics Today the center has a staff of about 300, up from just two people (Ruh and his executive assistant) in late 2011. Not all of them are in San Ramon, however. Ruh has employees located around the globe – Bangalore, New York and Cambridge– who report into the center. The company plans to staff up to about 1,000 people at the San Ramon facility, which is between San Francisco and
Silicon Valley. Their work will support the efforts of another 9,000 GE software engineers who operate in its various product businesses globally. Of the 300 currently in San Ramon, there are a number of ’hardcore data scientists’ as Ruh refers to them. Why centralize these people? Ruh said it came down to three factors: An acute shortage of talent. “The first reason for centralization is that there is only a limited amount of talent – and I actually mean extraordinarily limited,” said Ruh, who added that his center hires less than 5% of job applicants. “You can find a lot of people who are subject matter experts, basically analysts. You can find a lot of people who do business intelligence. You can find programmers. But the fact is that you’re still probably not getting a whole lot out of your data other than reporting. The in-depth data science and deep analytics capabilities are held by such a small number of people.” Employee retention. Data scientists at GE will need a career path if they’re to stay for long. “They need to feel coupled and placed into a leadership program where they can get promoted based on their capabilities. When you put them in the businesses, their ability to grow, get promoted, and take on increasingly bigger roles is limited in many ways by the hierarchal structure of those businesses.” Reusability in technology. “We need to build high-end capabilities [in solving deep technical problems],” Ruh said. “That cannot be built by each group over and over again. The reason is you can’t find the talent, you can’t maintain it, and so on. We believe this idea of reuse is going to differentiate the winners from the losers.” The center has begun to organize employees into disciplines such as machine learning, statistics and operations research. “They are very different approaches, and there isn’t one approach that solves every problem,” Ruh said. The keys to success for GE software and analytics? Ruh boils it down to this: continually bringing a new portfolio of compelling service offerings. To be attractive to the market, those services must help airlines, electric utilities, hospitals and other customers tap GE’s Big Data expertise and generate big savings and other improvements. “In the end, our service offerings must foundationally improve how our customers manage, operate and maintain these big machines,” Ruh concluded. “If we do that, we will be a leader in helping bring about this industrial Internet.” ë
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Simplifying Compliance in the Big Data Era The world generated more than one zettabyte (ZB), or one million petabytes (PBs), of data in 2010. This year, the growth is predicted to reach 72 ZBs a year, fueled in part by the rapid rise of machine-generated data.
Big Data Management Challenges
About the Author:
Allen Mitchell is the Regional Pre Sales Manager at Commvault MEA. He is an experienced Senior PreSales Consultant with a proven track record built over 20 years in the industry. His experience includes +14 years focused on Data and Information Management issues and solutions for enterprise business.
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A relentless explosion of Big Data continues to ignite pervasive and persistent problems as organizations grapple with how best to retain, access, discover and ultimately delete content in compliance with evolving regulations. Growth is being impacted by evolving data retention requirements, and industry regulations, which necessitate that some types of data be kept for anywhere from a few years to indefinitely. Big Data plagues many stakeholders, from IT to Legal. While IT departments grapple with how to support complex Big Data environments, legal teams are tasked with making accommodations for Big Data in the already expensive eDiscovery process. The world generated more than one zettabyte (ZB), or one million petabytes (PBs), of data in 2010. This year, the growth is predicted to reach 72 ZBs a year, fueled in part by the rapid rise of machine-generated data. Structured data (e.g., data records from programmed trading and financial transaction systems, intelligent meters, call-detail records for smartphones and tablets, etc.), unstructured data (e.g., images, audio or video files) as well as semi-structured data (e.g., emails, logs, etc.) add yet another layer of management complexity, especially when determining the most efficient and reliable way to ingest, protect, organize, access, preserve and
defensibly delete all this vital information. In sifting through voluminous Big Data to find responsive information, organizations can spend millions of dollars to isolate relevant Electronically Stored Information (ESI) and even more to review it. Simply put, the Big Data problem brings new meaning to the phrase, “looking for a needle in a haystack.” Companies can begin to view data backups and archives more strategically while leveraging integrated solutions for lowering storage costs and compliance risks. Technology solutions need to meet the demands of the business with a flexible and adaptable strategy that best reflects the needs of the business as it evolves.
Crossing Big Data’s Backup and Archive Chasm For many organizations, backup and archive functions are deployed and maintained as separate “silos” within an overall information management strategy. Multiple, disparate hardware and software products typically manage these data silos, which leads to duplicate copies of information that must be protected and preserved. Additionally, legal pressure to find and preserve data typically causes yet more silos or a worst-case scenario— indefinitely extended retention of information assets because of
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inadequate visibility into what an organization is keeping. Storage and backup administrators oversee data protection and are heavily focused on the impact Big Data has on backup windows, recovery SLAs and infrastructure costs. While information management buyers are fixated on how Big Data affects data retention, discovery and information governance policies, and often operate without regard to the operational impact of these policies. As a result, a chasm exists between these two critical constituents in ongoing Big Data conversations. According to Gartner , backup complements archive and vice versa - yet most tools and technologies address either one or the other of these disciplines. Gartner, among others, predicts that being able to look at backup and archive holistically promises significant cost reduction and risk management benefits. The convergence of backup and archive is an emerging concept that’s gaining traction as organizations seek solutions to reduce the number of copies created for backup and archiving while more closely aligning data access policies for both.
Taking a United Front on Data Convergence One way to accomplish this is the unification of backup and archive, but it requires cross functional teaming, ensuring that the needs of the business are met for every stakeholder. This starts with developing a better understanding of how applications, users and critical business processes need to access data throughout its lifecycle. As part of this process, many of the hurdles thwarting streamlined access to individual and corporate data across the enterprise will be uncovered while at the same time, areas will be identified where limited visibility into vital information assets has created undue exposure to compliance and information governance risks. The notion of a single data repository that eliminates redundancies and separate silos is compelling on many levels. A holistic approach that captures data once and then repurposes it for data protection and preservation is key to getting the right data into the hands of the right people so they can turn it into something more meaningful and actionable for the business. Moreover, the ability to leverage a single-query data repository enables legal teams to obtain the most comprehensive results to an eDiscovery request in the least amount of time. Having a single collection ensures that all data sources are accounted for in a discovery effort, ensuring all case critical data has been collected, preserved and is ready for review. Also, a central place to
delete data also reduces both the cost and risk of inadvertently storing multiple copies. Understanding large data pools well enough to extract and collect relevant subsets for both reactive and proactive eDiscovery can prove to be a huge cost and risk reduction exercise. Converged data protection and retention strategy allows for centralized reporting that enables business and IT leaders to make more informed decisions with their data while bolstering analytical skills. Organizations can extend their view into the business with embedded intelligence and analytical tools that provide granular insights into the ever-evolving role data can, and should play, in driving business direction. Most important, companies can maintain a balance between capturing too much data or not enough as both scenarios pose potentially serious business risks. Armed with appropriate insight and tools, it’s possible to verify whether all data sources have been collected across the enterprise. With robust reporting and predictive tools, it’s much easier to forecast, analyze and budget properly for the ongoing onslaught of Big Data. Reporting can be used as a tool in the eDiscovery process to effectively defend methodologies of a data collection and preservation effort of an organization responding to litigation, regulatory request or an internal investigation.
Senior Technical Account Manager, CommVault Systems
“In sifting through voluminous Big Data to find responsive information, organizations can spend millions of dollars to isolate relevant Electronically Stored Information (ESI) and even more to review it.” Forward-thinking companies, which embrace a unified approach for managing both backups and archives, will be able to take full advantage of a future-proof solution that elevates overall information management while providing appropriate access to business-critical information as it ages. ë
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Intel Advances Next Phase of Big Data Intelligence
Big data and the Internet of Things (IoT) are providing enormous opportunities for many organizations to grow as they create revenuegenerating services from the information they are able to derive.
o help companies in a variety of industries from retail and healthcare to banking and transportation turn data into actionable insights, Intel Corporation today introduced the Intel Xeon processor E7 v2 family. Using analytics enables businesses to make decisions that improve top-line and bottom-line results. The Intel Xeon processor E7 v2 family delivers new capabilities to process and analyze large, diverse amounts of data to unlock information that was previously inaccessible. “Organizations that leverage data to accelerate business insights will have a tremendous edge in this economy,” said Diane Bryant, senior vice president and general manager of Intel’s Data Center Group. “The advanced performance, memory capacity and reliability of the Intel Xeon processor E7 v2 family enable IT organizations to deliver real-time analysis of large data sets to spot and capitalize on trends, create new services and deliver business efficiency.” Big data and the Internet of Things (IoT) are providing enormous opportunities for many organizations to grow as they create revenuegenerating services from the information they are able to derive. The big data technology and services market is expected to grow 27 percent annually through 2017 to reach $32.4 billion4. A leading driver of this growth is the immense amount of data coming from connected devices making up the IoT, which is projected to grow to 30 billion devices by 20205. Investments in the highest performing technologies and analysis solutions can also deliver significant cost savings.
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For example, Intel’s IT organization expects to achieve cost savings and increased bottom-line revenue of nearly half a billion dollars through use of analytics solutions by 2016. New Big Data Processing and Analytics Capabilities with Relentless Reliability The Intel Xeon processor E7 v2 family has triple the memory capacity of the previous generation processor family, allowing much faster and thorough data analysis. In-memory analytics places and analyzes an entire data set – such as an organization’s entire customer database – in the system memory rather than on traditional disk drives. This method is gaining in popularity due to the increased need for more complex analytics. Industry analyst firm Gartner expects 35 percent6 of mid- to large-sized companies will adopt in-memory analytics by 2015, up from 10 percent in 2012 and predicts at least 50 percent of Global 2000 companies will use in-memory computing to deliver significant additional benefits from investments in enterprise resource planning (ERP). eBay, one of the world’s largest and most complex online marketplaces, handles massive data sets of more than 50 petabytes (PB) for more than 100 million users. Based on initial testing of the new Intel Xeon processor E7 v2 and SAP’s HANA* in-memory analytics software, eBay has seen greater performance7 and understanding of larger data sets that will help drive additional revenue opportunities for its customers. Built for up to 32-socket8 servers, with
senior vice president and general manager of Intel’s Data Center Group
“Organizations that leverage data to accelerate business insights will have a tremendous edge in this economy,” configurations supporting up to 15 processing cores and up to 1.5 terabytes (TB) of memory per socket, the new processor family achieves twice the average performance of the previous generation3. These enhancements help businesses that run mission critical applications including business support systems (BSS), customer relationship management (CRM), and ERP to operate more efficiently, at lower cost and with faster response times2. For example, a sales team with these capabilities can maximize revenue by pinpointing the best time to sell a product, or let an oil and gas company better predict when its platforms require preventative maintenance. To reduce data bottlenecks, the Intel Xeon Processor E7 v2 family features Intel Integrated I/O, Intel Data Direct I/O and support for PCIe 3.0, achieving up to four times the I/O bandwidth over the previous generation9 and providing extra capacity for storage and networking connections. System uptime and reliability also remains a key requirement for mission critical applications. The Intel Xeon Processor E7 v2 family continues Intel’s tradition of delivering world-class reliability, availability and serviceability (RAS). Intel Run Sure Technology10 is designed for “five nines” solutions essential for business-critical data by reducing the frequency and cost of planned and unplanned downtime. ë
big data & Analytics
GE Healthcare leverages the power of Big Data By drawing on big data, GE Healthcare aims to enhance care for more patients through scheduling efficiencies, faster data entry, proactive asset management, clinical decision support and financial gains that allow for expansion.
E Healthcare is introducing its transformational Industrial Internet mission to the Middle East, which leverages the potential of big data to strengthen the productivity and operational efficiency of the region’s healthcare infrastructure. The Industrial Internet approach of linking big data with advanced technology is estimated to enable the global healthcare industry to save US$20 billion annually through increased productivity. Maher Abouzeid, President and CEO of GE Healthcare for the Middle East and Pakistan, said: “Through GE Healthcare’s Industrial Internet mission, we aim to deliver outcome-based offerings and solutions for customers to enhance the productivity and efficiency of the hospital infrastructure. This is of great significance to the Middle East region, where healthcare costs are increasing, in line with the increasing incidence of lifestyle diseases and growth in population.” He added: “By identifying, liberating and analyzing the data captured by software and technology, caregivers will have the information they need when they need it to help enable them to prevent, diagnose, treat and cure. This will also enable healthcare practitioners to further sharpen their diagnostic and treatment capabilities by benefiting from the most relevant data for accurate and faster care. While healthcare
has always relied on big data, our focus is to use this information effectively by providing the right technology that enable physicians to make the right diagnosis and match it with the right treatment.” GE Healthcare’s Industrial Internet approach delivers actionable insights to practitioners by connecting data from multiple sources to help them derive conclusions that contribute to better patient care. The company continues to invest in developing and delivering software that connects caregivers to systems to aid in better-informed diagnosis and enhanced care. By drawing on big data, GE Healthcare aims to enhance care for more patients through scheduling efficiencies, faster data entry, proactive asset management, clinical decision support and financial gains that allow for expansion. It also potentially reduces costs by optimizing workflow in care delivery, minimizing payment cycles, maximizing reimbursement rates and eliminating unnecessary waste. The third key benefit is in minimizing rework and redundancies by enhancing collaboration.
Technologies powering the Industrial Internet Enterprise Imaging -- GE Healthcare is presenting its expanded suite of Enterprise Imaging Solutions to help lower IT costs, improve clini-
President and CEO of GE Healthcare for the Middle East and Pakistan
“Through GE Healthcare’s Industrial Internet mission, we aim to deliver outcome-based offerings and solutions for customers to enhance the productivity and efficiency of the hospital infrastructure.” cian productivity, expand networks of care, and improve workflows. GE Healthcare’s Enterprise Imaging Solutions include Centricity PACS with Universal Viewer and Centricity Clinical Archive solution. IHS recently ranked Centricity Clinical Archive as the #1 vendor neutral archive in the world with a 49% share of images stored. “Overall, GE Healthcare’s upgraded solution set is in perfect alignment with evolving end-user demands and the various directions taken by imaging providers in the U.S.,” announced Frost & Sullivan in a release recognizing GE Healthcare with the 2013 North American Frost & Sullivan Company of the Year Award for innovation in radiology informatics. “Combining top-quality service, high performance and technology innovation, GE Healthcare’s Centricity imaging solutions have enabled providers to lower costs of ownership while preparing for the challenges of the future.” ë
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big data & Analytics
Big Data Will Lead to Better Decision Making 45% have achieved a competitive advantage as a result of Big Data analytics technology and 67% believe that industries that succeed will be the same ones using such tools.
MC Corporation today released the findings of a survey that asked 237 IT decision makers in the United Arab Emirates (UAE) for their perspective on the challenges and opportunities that Big Data and IT transformation – and related skills – can present to their companies. The UAE results will be added to the thirty-six country-level survey results being collected through EMC Forum events taking place around the world between June and November 2013. Visit EMC Forum 2013: Transforming I.T. Study for a closer look at the UAE survey results and those of other countries as they become available. The series will conclude with an announcement of the global results in December.
Key Findings: In the UAE, Big Data is giving rise to markedly improved decision making and is having a significant impact on companies’ competitive differentiation and ability to avert risk. • 87% of respondents in the UAE reported that decisions in their organization could be improved with a better use of data, and 67% agree that their senior teams trust Big Data insights to make truly transformative business decisions. • 45% have achieved a competitive advantage as a result of Big Data analytics technology and 67% believe that industries that succeed will be
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the same ones using such tools. • 67% of respondents agree that Big Data technology will prove vital in identifying and protecting against cyber-attacks – which could be crucial as only 66% of respondents in the UAE are confident that they could fully recover all their data should they need to.
However, in the UAE: • 27% of companies surveyed have no current plans for implementing Big Data technology. • While budget (64%) was the most important factor for overall business decision making, the most common reason cited as the inhibitor to Big Data adoption was the lack of a clear business case or proven ROI (57%). As companies in the UAE continue to look to IT innovation to compete locally and on the global stage: • The business priorities driving IT transformation in the UAE are most commonly business process/operational efficiencies (55%) and improved governance and compliance (34%). • 86% report their business sees technology investment as a strategic way of achieving its goals. • 79% believe it will be a challenge to have these skills keep pace with IT innovation over the next three years. • 79% of respondents in the UAE believe their organization has the right level of skills
and knowledge to complete business priorities successfully. • 75% of respondents in the UAE agree that the biggest barrier to coping with business priorities is cultural. Said Akar, District Manager South Gulf, EMC, said, “This research shows that companies in the UAE are increasingly seeing the transformative benefits that are achievable with Big Data analytics technology. Not only are senior management executives engaging with the idea of Big Data analytics but the majority of businesses are aware of the huge competitive advantages the technology brings as well as the security benefits. This is a core part of IT transformation, a process which UAE businesses are well underway with. The majority of businesses in the region have already set out to virtualize and create cloud-enabled businesses and even more incredibly, some have created a fully software defined infrastructure. This approach, combined with Big Data analytics will see the agility and competitiveness of UAE businesses increase massively.”
Survey Methodology EMC polled a total of 237 businesses including I.T. management and executives, technical architects, data scientists and storage/infrastructure managers from a range of businesses in the UAE who registered to attend the EMC Forum event on September 10. ë
big data & Analytics
District Manager South Gulf, EMC
“This research shows that companies in the UAE are increasingly seeing the transformative benefits that are achievable with Big Data analytics technology.”
Head of Talent Consulting MENA, Aon Hewitt Middle East
Major Yaqoub Y. Al Ahmed
Head Of Operations, Abu Dhabi Police
“Safety and security remain topmost priority in the UAE government’s vision to foster an environment favorable for business opportunities and fair trade. Information Technology remains central to Abu Dhabi Police’s services from emergency field management right down to command and control systems and protocol. Investments in nextgeneration IT infrastructure enable our teams to stay informed, alert and resilient to create an intelligenceled, proactive and responsive security force to ensure the safety of the citizens and residents of the Emirate of Abu Dhabi and the United Arab Emirates. Technologies like cloud computing and virtualization have been instrumental in helping Abu Dhabi Police create a seamlessly integrated, centralized and scalable environment that is designed to perform with effortless efficiency 24/7, 365 days a year ensuring that we are constantly connected to our community and its people and ready to respond to their needs at a moment’s notice.”
“As businesses grow more competitive, there is an increasing demand for a variety of skills from their employees, to drive a significant competitive advantage creating new opportunities for young talent and career advancement of existing employees within the enterprise. This need for education and learning is driven even further by the rapid evolution of the technology landscape and the growing demand for intelligent solutions to enhance performance efficiencies and create new customer experiences. Set against this backdrop and to cater to the increasing demand for a qualified pool of local resources in the country, the UAE continues to witness an increased focus on skills and development through strategic alliances and partnerships between industry leaders and academia, to introduce the student body to technologies like cloud computing, virtualization and big data to create a qualified workforce capable of leading the future of the country and sustaining its growth for years to come.”
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big data & Analytics
42% of IT Leaders Have Invested or Plan to Do So Organizations are undertaking their big data initiatives in a rapidly shifting technological landscape with disruptive forces that produce and demand new data types and new kinds of information processing.
fter a few years of experimentation and early adopter successes, 2013 will be the year of larger scale adoption of big data technologies, according to Gartner, Inc. According to a worldwide Gartner survey of IT leaders, 42 percent of respondents stated they had invested in big data technology, or were planning to do so within a year. “Organizations have increased their understanding of what big data is and how it could transform the business in novel ways. The new key questions have shifted to ‘What are the strategies and skills required?’ and ‘How can we measure and ensure our return on investment?’” said Doug Laney, research vice president at Gartner. “Most organizations are still in the early stages, and few have thought through an enterprise approach or realized the profound impact that big data will have on their infrastructure, organizations and industries.” Organizations are undertaking their big data initiatives in a rapidly shifting technological landscape with disruptive forces that produce and demand new data types and new kinds of information processing. They turn to big data technology for two reasons: necessity and conviction. Organizations are becoming aware that big data initiatives are critical because they have identified obvious or potential business opportunities that cannot be met with traditional data sources, technologies or practices. In addition, media
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hype is often backed with rousing use cases. “This makes IT and business leaders worry that they are behind competitors in launching their big data initiatives. Not to worry, ideas and opportunities at this time are boundless, and some of the biggest big data ideas come from adopting and adapting ideas from other industries,” said Frank Buytendijk, research vice president at Gartner. “Still, this makes it challenging to cut through the hype when evaluating big data technologies, approaches and project alternatives.” Despite these challenges, Gartner predicts that by 2015, 20 percent of Global 1000 organizations will have established a strategic focus on “information infrastructure” equal to that of application management. In anticipation of big data opportunities, organizations across industries are provisionally collecting and storing a burgeoning amount of operational, public, commercial and social data. Yet in most industries — especially government, manufacturing and education — combining these sources with existing underutilized “dark data” such as emails, multimedia and other enterprise content often represents the most immediate opportunity to transform businesses. Gartner believes that by integrating and analyzing a variety of data sources, not just individually, organizations can achieve the most extraordinary business insights, process optimization and, of course, decision making.
research vice president at Gartner
“Most organizations are still in the early stages, and few have thought through an enterprise approach or realized the profound impact that big data will have on their infrastructure, organizations and industries.” Although most of the big data hype is about handling the sheer size and speed of data available, our research shows that the ultimate wins will be from those making sense of the broadening range of data sources. “Business and IT executives regularly say that information is one of their company’s greatest assets,” said Mr. Laney. “Businesses are increasingly managing and deploying information more effectively than ever, but certainly not with the well-honed asset management discipline applied to their traditional material, financial or other intangible assets. The application of formal information valuation models will allow IT, information management and business leaders to make better-informed decisions on information management (IM), enrichment, security, risks, purchasing, collection, usage, bartering, productization and disposal.” ë
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