Combining its server, storage and networking hardware with open source and partner software, and professional services, Dell is shaping up to be an IT heavyweight in the big data space.
We tapped Dell VP of sales for financial services Bob Barris to explain the company’s offering, and he responded that it’s as easy as ABC … and D.
Q: Dell is transforming from a major hardware product company into one focused on delivering solutions. How is it organised to address (a) the needs of financial markets participants (b) customers’ big data initiatives, and (c) the convergence of the two?
A: Dell has a long history of activity in the financial markets going back to our very beginning in the 1980s. Our hardware products, Dell servers, desktops and notebooks, have always had a prominent place on Wall Street. However, more recently, Dell has transformed itself to an end-to-end technology provider, offering IT solutions designed to solve customer technology pain points based on various industry challenges.
After thoroughly measuring our competitive advantages and strengths against the most salient trends within the financial services industry, we decided that one of the IT pain points we’d like to address is big data analytics. One of those pain points is the need for big data analytics. Today, with data being bigger, faster, and far more unstructured and complex than ever before, there is a competitive need to help financial institution better manage and analyse data.
To help our financial services customers address these pain points, Dell has people dedicated to the financial markets in all three regions around the globe. We also have focal points within our various product groups who understand the financial markets and spend time with our customers. Additionally, we have a services focused team specifically for financial services who focus on major application areas as well as infrastructure services. To coordinate our efforts globally we have created organisational alignments and use a great deal of information sharing, including rigorous use of customer relationship tools and social media.
Q: There is a lot of reality related to big data, but also an awful amount of hype. Where would you place its importance to the business community as a whole, and to Dell’s technology response?
A: At Dell, we believe there is far more reality to big data than hype. As you know, the financial services industry has long been at the forefront of innovative big data techniques. Notably, banks and capital market firms have excelled at leveraging large and cumbersome workloads of data to pinpoint trading opportunities, better understand a customer and more efficiently manage fraud.
Today, big data is even more critical for financial services firms than ever as the sector is currently experiencing an acute spike in new data types and sources, creating exploding volumes of multi-structured data that cannot be simply and cost-effectively stored in conventional data collection systems. More importantly, these increasingly voluminous, varied and complex data stores encumber insightful data processing and analysis using orthodox tools. And, the larger business community is experiencing the same trend.
As a result, big data has already become a critical and immediate driver of IT spend, with financial services, once again, leading other industries in early technology adoption and spend. An October 2012 Gartner report (titled Big Data Drives Rapid Changes in Infrastructure and $232 Billion in IT Spending Through 2016) estimated global big data-related IT spend to be $232 Billion from 2011-2016, the bulk of which is already being spent on adapting traditional tools to big data demands. Similarly, some analysts forecasted 2012 to be the year when securities firms begin to employ big data techniques to address problems in risk management, regulatory compliance, and portfolio analytics.
So, big data is certainly more than hype. It’s the past, present and future, embodying a new information age in which advanced data analytics and insights will prove the difference maker in business. Our technology response is to help our customers fulfill the promise of enhanced big data analytics to stay ahead of market conditions, regulators and competitors.
There are two major challenges: 1) how to efficiently ingest and store the growing data; and 2) how to get relevant insights from the data that’s being collected. The economics here are very important since overspending on data management can lead to less money to invest in getting the right answers at the right time. We offer the highest performance systems on which to run analytics. If the end goal is real time portfolio analysis for risk management, there is no better platform than Dell servers and storage along with the partnerships that we bring to market.
Q: You’ve made a number of product and partner announcements related to delivering big data capabilities of all kinds. Can you describe each of them briefly, and fit them into your vision for meeting the overall big data challenges of companies?
A: In July, we announced our partnership with ParAccel to help our customers build out massively parallel grids for big data analytics using the Dell-ParAccel Analytic Platform, which supports open, interactive and complex analytics on vast and diverse datasets. Deployed as part of optimised data centre architecture, the ParAccel Analytic Platform – combined with Dell’s portfolio of server, storage, and networking solutions – delivers a powerful and flexible analytic infrastructure that maximises business and IT agility, minimises TCO, and delivers ROI at scale all while fundamentally transforming the way customers do business.
Also in the summer of 2012, in partnership with RainStor, we introduced a new Big Data Retention solution that helps our customers significantly reduce the cost of retaining big data while improving data management for easy retrieval and analysis. The Big Data Retention solution combines Dell storage, including the DX Object Storage Platform, and RainStor database technology, to help reduce the cost of retaining big data through data reduction, simplified data management and near-perfect scalability, which can provide easy access to the data by standard SQL BI/analytics tools. The solution also includes Dell professional services to help customers enhance their current big data environment or create a new one that can scale to company demands and data growth.
Also in 2012, in partnership with Kove and Kx Systems, we launched the High-Performance Database Solution, which helps our customers simultaneously execute algorithmic trades while back-testing that same data without performance interruption. This enables our customers to execute their trading models quicker, optimise revenues, and reduce the associated credit, market and operational risks. Holding world records for latency, IOPS, and bandwidth, it is built on KX Systems’ kdb+ 2.7 database with Kove’s XPD L2 storage disk and controller co-located on a Dell PowerEdge server for faster caching. The solution accelerates faster than flash, spinning-disk or solid-state technologies, achieving the highest performance ranking ever in 14 out of 17 Securities Technology Analysis Center (STAC)-M3 benchmarks. It also performs at 12x the speed of the next best Market Snapshot benchmark, 5x the speed of the next best Theoretical P&L benchmark and 4x the speed of the next best VWAB-Day and Week Hi Bid benchmarks.
In addition to these partnerships, we have made several acquisitions in the server and storage technology space that enable our current and future offerings. We recently launched a processor acceleration technology to help our customers accelerate clock speeds within processors while eliminating jitter running standard servers. For single-threaded applications, we have the best open solution available. In the storage space, we have made several acquisitions over the years to provide the cost effective, high performance solutions needed to handle big data challenges.
Q: Specific to the financial markets, where do you see your big data vision and offerings fit in? Are there specific requirements in the financial markets that you are addressing, specific applications that you’re looking to support?
A: Beyond simply maximising profits and improving business processes, financial services firms face the additional regulatory incentive to drive insightful data analytics. In response to the Great Recession of 2007-2012, regulators now obligate financial services firms to provide increased transparency and risk mitigation to allay concerns about the safety of capital.
Hence, one of the biggest IT pain points that financial services firms face today is the need to tame this big data conundrum – i.e. by better processing and analysing ballooning volumes of multi-structured data at various speeds – to comply with a bevy of more rigorous regulations like Dodd-Frank (i.e. the OTC Regulations) and Basel III. As a result, analysts forecasted 2012 to be the year when capital markets firms start deploying big data technologies to address problems in risk management, regulatory compliance, and portfolio analytics.
At Dell, we believe it’s not just about big data; it’s also about big insights. So, our big data vision is to help organisations of all sizes turn their data into a competitive advantage. We call it an ABCD framework:
“A” stands for Analytics and BI software; to help our clients glean the key insights. So, for example, open source solutions with value-added deployment tools, such as the Dell-Hadoop Big Data Solution. “B” is for Bandwidth; to help our clients move volumes of data rapidly. In this category, we have high bandwidth networking switches with Dell Force10. “C” stands for Compute solutions, which help our clients crunch and manipulate big data using compute-intensive scale-out platforms. And, finally, “D” is for our Data Storage and Integration solutions with PowerEdge-C, which store and manage data efficiently, whether it be structured, unstructured, or multi-structured data. We have all the building blocks and our solutions are open and scalable to address the fast advancing technology developments in the marketplace.
Q: How do you see big data approaches and technologies align with cloud technologies and services in the future? And what’s the opportunity in the financial markets?
A: Cloud technologies and services are already very much aligned with big data, and we expect this alignment to grow stronger in the future. Cloud (private, public and hybrid) serves as a natural enabler for big data analytics and infrastructure (i.e. storage). The opportunity at the intersection of cloud and big data in the financial markets is substantial.
More than ever, financial services firms are currently experiencing an acute spike in new data types and sources, creating exploding volumes of multi-structured data that cannot be simply and cost-effectively stored in conventional data collection systems. For financial services firms, the virtual, amorphous, adaptable and flexible nature of cloud architectures makes them especially suitable for parallel processing large and complex data sets (i.e. tick data) at a low cost. And this could be critical to addressing one of the biggest IT pain points facing financial services firms today: how to process, analyse and derive insights from ballooning volumes of multi-structured data in compliance with more rigorous regulations like Dodd-Frank and Basel III.
One of the fastest-growing cloud-based big data analytics solutions being deployed in the financial markets today is Hadoop, which is offered directly from the cloud by Cloudera, Amazon and other such mediums. Another notable trend is that BI and analytics firms are increasingly making their big data analytics solutions available to financial services firms across the private, public and hybrid cloud. In an April 2011 report (Sizing the Cloud), Forrester Research forecasted the global market for cloud computing to grow from $40.7 billion in 2011 to more than $241 billion in 2020. We expect a sizeable portion of this IT spend to be deployed within financial services to tackle big data challenges.
Q: Finally, what challenges need to be overcome with current big data technologies in order for them to be adopted more fully in the financial markets?
A: According to the McKinsey Global Institute, one of the biggest hindrances to big data technology adoption is a skills shortage. Given the accelerated adoption of big data technologies, across all industries, McKinsey predicts a 60% shortfall in associated big data talent. And this paucity of talent is especially noticeable within the financial services industry, which has steadily been one of the earliest adopters of cutting-edge big data technologies driven by a recent acute spike in new data types and sources, creating exploding volumes of multi-structured data that cannot be simply and cost-effectively stored in conventional data collection systems.
The financial services industry has always been one of the strongest magnets for big data talent. However, for a variety of reasons, even it is faced with this talent shortage today. Not unlike other industries, the financial services sector is currently witnessing increasingly voluminous, varied and complex data stores encumbering insightful data processing and analysis using orthodox legacy tools.
Such has been the severity of this problem that new and vastly different big data technologies and analytics techniques (i.e. Hadoop, in-memory DBMS, NoSQL databases) emerged to address it, hence the talent gap. If they are to more fully adopt big data technologies, financial services firms must hire more skilled individuals who understand these new technologies and who can handle both the analysis and infrastructure management aspects of their adoption.
Technologies and new players also need to be reviewed, tested and taken as partners to solve the problems. This change takes some time, but is underway. The big data space cannot afford the profit pools of legacy server, storage and network technologies. These systems must be faster, open, more scalable (build as you grow) and affordable. This is why Dell is the best choice on which to build out infrastructure and to provide the right services and right partners at the right time.
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