Completing the Big Data Picture with Unified Information Access. An Attivio White Paper

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Completing the Big Data Picture with

Unified Information Access

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Introduction: Big Data and “The Next Big Thing”

Jim Collins, author of the 2001 groundbreaking business bestseller Good to Great, observed an intriguing paradox among the most successful companies: they avoided the distractions of technology fads and bandwagons; and yet, they were also typically pioneering leaders in the successful use of new technology. Collins explained that the greatest companies use technology to enhance and accelerate their carefully developed business model. Technology is never used as a replacement of the key components of their business model (right leaders in place, strongly-defined core focus and a motivated, disciplined culture). “We would do well to keep [this] in mind when The Next Big Thing comes rolling around,” Collins added.1

Over a decade later, the current state of many early Big Data projects has validated Jim Collins’ advice once again. Many organizations, fueled by a perceived need to ‘respond’ to Big Data so as to ‘not fall behind,’ have dived headfirst into Big Data infrastructure projects, including “blindly building out Hadoop clusters and collecting new data based on only a vague plan to open up that data store to multiple lines of business in 12 to 24 months.”2 Far too often, hastily building out Big Data technology such as Hadoop has come ahead of defining a viable use case for Big Data to help boost revenue, cost savings or competitiveness.

This white paper will explore the critical need to map the right Big Data technologies to your data and not the other way around, to properly inform the design of Big Data infrastructure to achieve well-defined business goals. Such a disciplined assessment will reveal Big Data integration must be a top priority; this paper will also inform you how a true unified information access platform provides the new level of agile integration essential to leverage Big Data as a powerful new means to enhance and accelerate your business.

Thinking Bigger about Big Data: Resetting Focus from Infrastructure to Analytics

Organizations are eager – even impatient – to achieve new business success and solve vexing problems. Amid that backdrop, “Big Data” first emerged as a new data source, within which insights and innovations were increasingly thought to be buried. Interest in retaining and analyzing Big Data soared alongside innovative infrastructure and storage technologies, particularly Hadoop, offering highly scalable, open source storage and processing of massive data volumes.

Early on, Big Data was commonly defined in terms of “big,” even massive, volumes of data and the technology to manage it. The organizations with the most disappointing Big Data project results appear to still think in such terms. Business intelligence (BI) and analytics author and thought leader Bruno Aziza recently noted how disillusioned technology leaders spanning many industries have told him, “We’ve spent months laying out our Big Data infrastructure [and] yet, we feel we are months away from gaining insights from our data.”3 Many others are even worse off, mired in a “boil-the-ocean” Big Data infrastructure project that “after 24 months of building… has no real value.”4

As Bruno Aziza explains, organizations lacking new business insights despite a huge, ongoing investment in Hadoop or a similar tool (and fitting their data into it) are suffering the consequences of paying

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2 The attention paid to [Big Data] infrastructure over applications is represented in Gartner’s forecasts: the

research firm evaluated that $30 billion was spent on Big Data infrastructure in 2012, [while] the data exploration market accounted for about $7 billion.

But Analytics is where you and your team have the most leverage on Big Data. Analytics is what business users work with… So, if you are working on a “Big Data” project today, make sure you prepare your “Analytics Plan” and make sure that it is part of your infrastructure solution early on – you’ll avoid some major disillusion.5

Clearly, Big Data business success requires a resetting of organizational focus:

 First… devote collective efforts on particular business challenges and the Big Data analytic insights essential to solving them;

 And only then… assess and determine the right Big Data technologies capable of achieving those well-defined business goals.

Jim Kaskade, CEO of InfoChimps, recently said in agreement, “You're going to learn much more tackling five [specific] use cases than you would learn after 24 months of building out a platform that has no real usage.”6 Mark Smith, CEO and Chief Research Officer of Ventana Research, also commented, “Selecting the right approach to big data integration is difficult when organizations lack knowledge of the functional requirements and best practices relevant to their industries, lines of business and IT.”7

Big Data

Variety

: The Spice of New Business Life

The disappointing results of many recent Big Data projects were actually predicted by Gartner’s Big Data analysis in April 2011. Technology professionals, Gartner reported, often delve into a Big Data challenge, only to discover that it is more complex than they realized: volume of data represents only one aspect of the problem. The Gartner research also noted that “the term Big Data puts an inordinate focus on the issue of information volume” and “the increasing velocity, variety and complexity of data also pose a challenge... IT leaders must recognize when they face extreme information management challenges.”8

Today, Big Data is often defined even more flexibly as “data which cannot be handled by traditional technologies.”9 However, thinking of Big Data in Gartner’s often-quoted primary Big Data attributes,

particularly variety, leads naturally to recognizing a critical need for integration to make essential new Big Data analytic insights a reality:

 Effective management of the wide varietyof enterprise information sources was recognized long before the Big Data movement. First, organizations must eliminate enterprise information silos that separate databases and content repositories. A recent Ventana Research Big Data survey revealed the greatest barrier to success is data spread across too many apps and systems (67%).10

Technology analysts have also agreed for years that it is vital to incorporate unstructured content in business analytics to properly understand and act upon organizational challenges and opportunities:

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3 The data in your structured databases is not enough to fully understand your business performance. With the volume of unstructured [content] on pace to overwhelm traditional, structured data, it’s critical to develop capabilities that leverage the unstructured content that inundates you on a daily basis. [Unstructured content] provides a depth of understanding that traditional data simply can’t.

You need to capture it and exploit it, or fall behind.11

“Fall behind,” indeed: A recent Aberdeen survey revealed 80% of the highest performing “Best-in-Class” companies actively use significant amounts of unstructured data, compared with 46% of all other companies.12

 Datavelocityis the extent to which data is streaming into the enterprise. If an organization has very fast data that needs analyzing immediately, neither Hadoop nor traditional platforms is useful; you will need a non-traditional complex event processing (CEP) engine.13 How, when and where the events generated by a CEP engine are to be integrated with other sources must also be addressed –

expanding variety and complexity challenges even further…

 Business success increasingly hinges on the ability to freely correlate all relevant information sources – structured and unstructured, internal and external – a dramatic increase in the complexity of

correlating (JOINing) data sources, regardless of data type or original source. A recent survey by Infochimps revealed the top two reasons why Big Data projects fail: a lack of business context around the data and an inability to ‘connect the dots’ between data sources.14

Taming the Big Data Integration Beast with

Unified Information Access

Aberdeen found the highest performing companies can integrate new data sources six times faster than average performing companies and 15 times faster (!) than underperformers.15 Clearly, companies that implement a Big Data strategy that addresses the vital need for integration across the full spectrum of structured and unstructured enterprise information sources will successfully facilitate new Big Data analytics and new business-building insights for lasting competitive advantage.

Unified information access technologyvery effectively fulfills the critical challenge of Big Data integration, essential for business success.

Attivio’s Active Intelligence Engine® (AIE®), built from the ground up to combine and link all data and content without restriction, is a true unified information access platform enabling Big Data innovation.

 Schema-less, universal indexing; no data modeling. AIE ingests all data and content into its universal index. AIE does not require relationships between any data or content to be defined in advance. By eliminating the need to build or constantly update a data model to join and present information, AIE serves as an agile information management and development platform with exceptionally fast time-to-value – more important than ever in today’s challenging economic climate.

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4  Attivio’s Active Security framework provides real-time security and permissioning, regardless of what

information the end user is accessing (data and/or content) or how they are accessing it. While this is a standard expectation in the structured data world, it is breakthrough capability for unstructured content sources.

 Advanced text analytics. Prior to indexing, AIE enriches and adds structure to documents and other unstructured content to maximize findability and joinability with related data and content from other sources. This includes a wide variety of built-in multi-language natural language processing (NLP); text extraction; entity extraction and normalization; key phrase extraction; all-important customer

sentiment analysis (at the document and entity level) and behavioral analytics.

 Patented ad hoc query-time JOIN of all related data and content. AIE performs ad hoc relational JOINs of all related data and content matching a given query, again with no advance data modeling required with full security.This groundbreaking functionality was conceived and developed by Attivio.  Support for business intelligence (BI) tools to access all customer data and content indexed within AIE

via ODBC/JDBC connectivity and full SQL support, for in-depth business intelligence by customer, demographics, location, business unit, and more.

Fortune 100 and innovative startups alike are utilizing unified information access, led by Attivio’s Active intelligence Engine, to rapidly combine and present a wide variety of information sources for a new world of analytics and insights.

A 360-Degree View of Private Banking Customers

The private banking division of a leading global financial services organization wanted to improve customer service and engagement, increase up-sell/cross-sell revenue and expand its customer base. The private bank selected Attivio AIE to power a dashboard providing private bankers with a complete, immediately actionable 360-degree view of each high net worth client. This 360-degree view unifies such previously siloed structured and unstructured data sources, including:

 Account transactions and trends  Demographic data

 Details of all available investment products  Investment research content

 News related to the client’s investments – and even about the clients themselves… and more Thousands of private bankers around the world can get a comprehensive view of their clients using an iPad application. A complex security model is applied to all of these sources of information, which Attivio AIE enforces in real-time. In the near future, the private bank will also provide clients direct access to its 360 degree views– which Attivio AIE will easily support with its unified information access agility.

New Insight into Product Performance “Beyond the Numbers”

A leading global diversified manufacturing firm wanted to become much more proactive in the monitoring of their customers’ usage of the company’s engines and improve responsiveness, resulting in increased customer

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5 satisfaction. Doing so required going “beyond the numbers” of engine diagnostic data sourced from engine sensors and manufacturing quality metrics maintained in an existing data warehouse.

The company turned to Attivio AIE to complete its informational picture by also integrating and correlating critical unstructureddata, including:

 Customer case management notes

 Engine maintenance system notes containing service technician notes and comments  Engine performance exception data produced by a complex processing engine

AIE ingested the above text-based information, applying text analytics including entity extraction and key phrase extraction to enrich and normalize the content. AIE’s capabilities include entity and key phrase extraction, with the ability to normalize terms, synonym expansion, spelling correction and more. AIE’s text analytics serve to maximize the analytical value of all unstructured content and enable its findability and ad hoc JOINability with data and/or content from other sources.

Managers and directors can now explore and discover new correlations between changes in key metrics and recurring key phrases from service notes describing observed engine conditions and service work performed, using the company’s BI dashboard tool of choice – in this case, TIBCO Spotfire.

Instead of merely observing instances of favorable and unfavorable performance metrics without any context, decision makers are now presented with those metrics, plus the context necessary to explain the underlying causes behind those performance trends, to take informed action. The resulting BI dashboards are

unquestionably agile, yielding tangible new levels of business agility.

Unified Information Access Puts Big Data to Work as a

Business Accelerator

Referring back to Jim Collins’ original quote, Big Data is not merely “The Next Big Thing” unless an organization unwittingly treats it as such by responding in a reactive manner, focusing on Big Data infrastructures instead of Big Data analytics. High performing “Good to Great” organizations will always begin with their core business model – which has been built based on a deep, “root-level” understanding of their business – and utilize new technologies as accelerators to more effectively achieve that business model as well as deepen understanding of their customers and their business. Building out Big Data infrastructures comes after determining use cases that will put Big Data to work to solve business problems and create new business value.

Such a “Good to Great” process inevitably leads to recognizing the vital need for a new, deeper level of enterprise data integration across a wider than ever variety of information sources – structured and unstructured, internal and external. Unified information access, led by Attivio’s Active Intelligence Engine, provides this integration, through a universal, schema-less index of all data and content, coupled with the ability to perform ad hoc JOINs of related data and/or content at query time with no data modeling in advance.

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About Attivio

Attivio’s Active Intelligence Engine® (AIE), redefines the business impact of our customers’ information assets, so they can quickly seize opportunities, solve critical challenges and fulfill their strategic vision. AIE is an “Analyze Everything” platform that brings together structured data and unstructured content for agile BI:

 Integrate and correlate all your data and content silos – with no advance data modeling required  Advanced text analytics

 Intuitive, Google®-like search for BI

 Seamlessly integrates with your preferred BI tools

Attivio correlates disparate silos of structured data and unstructured content in ways never before possible. Offering both intuitive search capabilities and the power of SQL, AIE seamlessly integrates with existing BI and big data tools to reveal insight that matters, through the access method that best suits each user’s technical skills and priorities. Please visit us at www.attivio.com.

Footnotes

1_{Jim Collins, JimCollins.com,}_{How Great Companies Tame Technology}_{(August 9, 2002).} 2

Doug Henschen, InformationWeek, Vague Goals Seed Big Data Failures (January 28, 2013).

3

Bruno Aziza, SmartData Collective, Is Big Data Failing? (February 22, 2013).

4_{Doug Henschen, InformationWeek,}_{Vague Goals Seed Big Data Failures}_{(January 28, 2013).} 5

Aziza (emphasis added).

6

Henschen.

7_{Mark Smith, SmartData Collective,}_{Big Data Without Integration Is Broken}_{(February 23, 2013).} 8

Mark A. Beyer et al, Gartner, 'Big Data' Is Only the Beginning of Extreme Information Management (April 7, 2011)

9

Udayan Banerjee, Technology Trend Analysis, What is the Definition of Big Data? (December 21, 2012).

10

Mark Smith, SmartData Collective, Big Data Without Integration Is Broken (February 23, 2013).

11

Jane Griffin, Information Management, Seven Principles of Sustainable Analytics (March/April 2011, emphasis added).

12_{Nathaniel Rowe, Aberdeen,}_{Data Management for BI: Getting Accurate Decisions from Big Data}_{(January 2013).} 13

Robin Bloor, Inside Analysis, Big Data, Huge Hype (May 24, 2012).

14

Infochimps, CIOs & Big Data: What your IT Team wants you to Know (2013).

15_Rowe.

Completing the Big Data Picture with Unified Information Access. An Attivio White Paper