Data Abstraction: The Lingua Franca for Data Silos

Enterprises are seeking ways to improve their overall profitability, cut costs, reduce risk and more through better leverage of their data assets.

Significant volumes of complex, diverse data spread across various technology and application silos make it difficult for organizations to achieve these business outcomes. To further complicate matters, there is a range of problems such as

  • Separate access mechanisms, syntax, and security for each source
  • Lack of proper structure for business user or application consumption and reuse
  • Incomplete or duplicate data
  • And a mixture of latency issues

Data abstraction overcomes these challenges by transforming data from its native structure and syntax into views and data services that are much easier for business intelligence and analytics developers to use when creating new decision-making applications.

Enterprises can approach data abstraction three ways:

  • Manual data abstraction
  • Data warehouse schemas
  • Data virtualization

Of the three approaches, data virtualization is the superior solution for data abstraction because it enables the most flexibility and agility when you need to provide simple, consistent, business–formatted data from different data locations and sources.

As a complement to Cisco’s Data Virtualization software and services, Cisco also provides data abstraction best practices that help you accelerate your data abstraction activities. Composed of three distinct layers (application layer, business layer and physical layer), these best practices support a data reference architecture that rationalizes multiple, diverse data silos for a range of BI and analytic applications. The architecture aligns closely with analyst best practices mapped out by both Forrester and Gartner on the topic of data virtualization. Using these best practices will enable your company to access the right data for the business, gain agility and efficiency, maintain end-to-end control, and increase security of your data across all your data silos.

To learn more about data abstraction best practices using Cisco Data Virtualization, check out our white paper.

Call for Nominations: 2014 Data Virtualization Leadership Awards

The Data Virtualization Leadership Awards recognize organizations for data virtualization initiatives with significant business impact, agility and innovation.

  • Has your organization executed a data initiative with significant business impact, agility or innovation that should be celebrated?
  • Do you know a champion whose efforts have driven data virtualization success in your organization and beyond?

If so, please submit a nomination for the 2014 Data Virtualization Leadership Awards.

The deadline to submit is only 3 weeks away on July 9 so don’t delay.

Award Categories

  • High Impact Award: Recognizing the depth and breadth of the data virtualization impact on the business and to IT.
  • Agility Award: Recognizing speed and flexibility in applying data virtualization for improved business agility.
  • Innovative Solutions Award: Recognizing innovation in executing demanding data integration projects in complex environments.
  • Data Virtualization Champion Award: Recognizing promotion of data virtualization’s value across their organization and in the broader business and IT community.
  • Peter Green 3-3-3 Award: Superior usage and outcomes in practice of the 3-3-3 data virtualization use pattern.

Winners Recognition

  • Industry recognition of the Organization, Project and Project Leader
  • Participation in the award ceremony, held at the 2014 Data Virtualization Day in New York City
  • Engraved glass sculpture commemorating the achievement
  • Opportunities to speak at a Data Virtualization Day or other events

Rules of Entry

  • You must submit your nominee via e-mail to dvla_nominee@cisco.com by July 9, 2014.
  • Your email must include name, title, company, award, and a paragraph justifying your nomination.
  • Individual companies may nominate themselves in up to two categories. However, it’s best to create tailored versions for each category submitted.
  • Prior year’s winners may apply if they submit a new application for a new or significantly enhanced project.

Learn More

To learn more about Cisco Data Virtualization, check out our Data Virtualization Video Portal.

Active Archiving with Big Data

Historical data is now an essential tool for businesses as they struggle to meet increasingly stringent regulatory requirements, manage risk and perform predictive analytics that help improve business outcomes. While recent data is readily accessible in operational systems and some summarized historical data available in the data warehouse, the traditional practice of archiving older, detail-level data on tape makes analysis of that data challenging, if not impossible.

Active Archiving Uses Hadoop Instead of Tape

What if the historical data on tape was loaded into a similar low cost, yet accessible, storage option, such as Hadoop?  And then data virtualization applied to access and combine this data along with the operational and data warehouse data, in essence intelligently partitioning data access across hot, warm and cold storage options.  Would it work?

Yes it would!  And in fact does every day at one of our largest global banking customers.  Here’s how:

Adding Historical Data Reduces Risk

The bank uses complex analytics to measure risk exposure in their fixed income trading business by industry, region, credit rating and other parameters.  To reduce risk, while making more profitable credit and bond derivative trading decisions, the bank wanted to identify risk trends using five years of fixed income market data rather than the one month (400 million records) they currently stored on line.  This longer time frame would allow them to better evaluate trends, and use that information to build a solid foundation for smarter, lower-risk trading decisions.

As a first step, the bank installed Hadoop and loaded five years of historical data that had previously been archived using tape.  Next they installed Cisco Data Virtualization to integrate the data sets, providing a common SQL access approach that made it easy for the analysts to integrate the data.  Third the analysts extended their risk management analytics to cover five years.   Up and running in just a few months, the bank was able to use this long term data to better manage fixed income trading risk.

Archiving with Big Data_BankTo learn more about Cisco Data Virtualization, check out our Data Virtualization Video Portal.

Cisco Enters the Data Virtualization Market

The purpose of the Data Virtualization Leadership Blog is to provide data virtualization adopters with high quality insights informed by the most relevant data management trends, most innovative data virtualization use cases and the latest data virtualization solution offerings.

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Comparing Data Virtualization and Enterprise Application Integration (EAI)

Given my prior role as CTO at webMethods, I am often asked to compare data virtualization and EAI offerings. Here is what I typically say.

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A Look Under the Data Virtualization Hood – Part 1

How Data Virtualization Works

Data virtualization is a data integration approach and technology used by innovative organizations to achieve greater business agility and reduce costs.

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Ten Mistakes to Avoid When Virtualizing Data – Part 2

In my prior blog post, I revisited mistakes one through five from my November 2008 Virtualization Journal cover article entitled Ten Mistakes to Avoid When Virtualizing Data.  In this post I will address mistakes six through ten and summarize what has changed since 2008.
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A Roadmap for Federal Agency Adoption of Data Virtualization (Part 2)

This is the second of three blog posts that guide federal agencies in the successful adoption of data virtualization to meet numerous critical information challenges. In this blog posts, I will cover step three ina five step approach that agencies can use to drive successful data virtualization adoption.

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Is Data Discovery the Answer to the Zettabyte Problem? Part 1

Data Data Everywhere! 

IDC’s June 2011 report Extracting Value from Chaos, estimates the amount of information currently stored by the end of 2011 will be 1.8 zettabytes.  That’s 1.8 trillion gigabytes.  IDC believes this data has grown by a factor of nine in the past five years.

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The Third “Wave” in Information-as-a-Service

And so it begins.  Forrester Research analysts Noel Yuhanna and Mike Gilpin recently commenced research on the third generation of their seminal Information-as-a-Service (IaaS) Forrester Wave™.

Read More

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