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Innovation Distinguishes Between a Leader and a Follower

Steve Jobs is arguably the most amazing innovator of our times.  I recently read some of his thoughts on innovation. His statement “Innovation distinguishes between a leader and a follower,” caused me to reflect upon my eight-year association with data virtualization, and consider who in the IT analyst community have been the innovative leaders.

Since 2006, I have worked with over one hundred IT analysts to define and advance the data virtualization market.  I even teamed up with one, Judith Davis, to co-author the first book on data virtualization, Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility.

Others such as Rick van der Lans, author of data virtualization’s second book, Data Virtualization for Business Intelligence Systems: Revolutionizing Data Integration for Data Warehouses and the seminal article, The Network is the Database, have contributed mightily to the market’s understanding of data virtualization’s capabilities, advantages and benefits.

The role call of top analysts doing innovative work continues with Noel Yuhanna of Forrester who wrote the analyst community’s first research paper on data virtualization in January 2006, Information Fabric: Enterprise Data Virtualization.

Gartner’s Ted Friedman and Mark A. Beyer, and more recently Merv Adrian, Roxane Edjlali, Mei Selvage, Svetlana Sicular and Eric Thoo, have been both descriptive and proscriptive about the use of data virtualization as a data integration delivery method, a data service enabler and a key component in what Gartner calls the Logical Data Warehouse.

Dave Wells, author of TDWI’s Data Virtualization Course, Data Virtualization: Solving Complex Data Integration Challenges, helped bring data virtualization into the mainstream.    As did Boulder BI Brain Trust members Claudia Imhoff, Colin White, John O’Brien, Ralph Hughes, John Myers and more who I recently wrote about in Rocky Mountains High On Data Virtualization.

Further, there have been myriad analysts who have amazing contributions.

  • The learned trio of Dr. Barry Devlin, Dr. Robin Bloor, and Dr. Richard Hackathorn have pushed the art of the possible.
  • While analyst / practitioners such as Jill Dyche, Mike Ferguson, Rick Sherman, Steve Dine, Evan Levy, David Loshin and William McKnight, via their hands-on client work, have “kept data virtualization grounded on reality street,” to quote Mike Ferguson.
  • And let’s not forget the Massachusetts’ Waynes — Wayne Eckerson formerly of TDWI and Wayne Kernochan, author of the eponymous Thoughts From a Software IT Analyst blog.  Their voices and insights have proven invaluable.

To quote Gene Rodenberry, “It isn’t all over; everything has not been invented; the human adventure is just beginning.”  The same is true for data virtualization.  So I look forward to more great insights from these innovators, as well as a new generation led by Puni Rajah of Canalys and Vernon Turner of IDC.

To see Rick van der Lans and Barry Devlin on stage and gain even more insights from the 2014 Data Virtualization Leadership Award winners, join us at Data Virtualization Day 2014 on October 1 in New York City.

Watch for a sneak peek of Data Virtualization Day 2014.

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To learn more about Cisco Data Virtualization, check out our page

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Rocky Mountains High On Data Virtualization

I recently returned from my seventh annual Boulder BI Brain Trust presentation. The BBBT as everyone likes to call it, is unique in the business intelligence, data and analytics industry.

Since 2006, the BBBT has advanced this industry by organizing half-day vendor presentations to their over 140 members.  During these presentations, vendors such as the Cisco’s Data and Analytics organization, update BBBT members on new strategies, evolving technologies, customer adoption and more.  In return the vendors get valuable feedback from the BBBT’s global network of analysts, consultants and academics.

Cisco’s Expanded Data and Analytics Portfolio

Mike Flannagan, General Manager of Cisco’s Data and Analytics Business Group, led off this year by identifying four key trends creating new business opportunities for our customers, as well as disrupting their traditional data management approaches.

  1. Increased speed of business and rising customer expectations
  2. Data is the new competitive battlefield
  3. Data is increasingly distributed
  4. Data at the edge volumes are extreme

Mike then discussed the coming together of Cisco’s data and analytics portfolio over the past year in order to comprehensively address these trends. These solutions include:

  • Cisco Data Virtualization, added to the portfolio a year ago when Cisco acquired Composite Software.
  • Cisco Prime Analytics, the former Truviso products.
  • Cisco Data In Motion, from the TigerMe acquisition.
  • Cisco Connected Analytics, a set of packaged analytics applications targeted for specific market segments including retail, healthcare, service provider, city infrastructure, call center, and more.

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Billions of Devices Generating Even Bigger Data

Following Mike, Jim Green, CTO for Mike’s group, discussed the data and analytic implications that will result as 30 billion additional devices connect over the network within then next five years.

The business outcome and analytics opportunities from these devices are endless.  However the data volumes generated will make even today’s big data seem small. And how all these come together in an already complex data landscape is an Internet of Everything challenge everyone will soon face.

Data Virtualization Advances

Kevin Ott, General Manager of the Data Virtualization Business Unit, and I closed out this year’s BBBT with updates on data virtualization market dynamics, customer adoption trends and our product strategy for maintaining product leadership in this increasingly important foundation technology.  Join us at Data Virtualization Day on October 1, 2014, in New York City where Cisco, our customers and prominent analysts will share more on these topics.  Sign up soon as space is limited. #DVDNYC

Gain a BBBT Insider’s View

Check out these three sources to gain an insider’s view on Cisco’s BBBT presentation:

  • Listen to Mike Flannagan and Jim Green’s podcast with BBBT co-founder Claudia Imhoff.
  • Read acknowledged data warehousing pioneer and BBBT member, Barry Devlin’s blog.
  • Review over 100 tweets from BBBT members by filtering on #BBBT.

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To learn more about Cisco Data Virtualization, check out our page

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Leading Analyst Firm, EMA, Validates Cisco’s Big Data Warehouse Expansion Solution

Enterprise Management Associates (EMA) is a leading industry analyst firm that provides deep insight across the full spectrum of IT and data management technologies. EMA analysts, including Shawn Rogers who guides EMA’s Business Intelligent Research group, leverage a unique combination of practical experience, insight into industry best practices, and in-depth knowledge of current and planned vendor solutions to help their clients achieve their goals.

Shawn recently published an EMA Impact Brief on Cisco Big Data Warehouse Expansion.   In it he examines the impact this solution brings to traditional data warehouse environments by better managing data, system growth and extending the analytic value delivered from a data warehouse investment.

Cisco Big Data Warehouse Expansion is a new offering that combines hardware, software and services to help customers control the costs of their ever-expanding data warehouses by offloading infrequently used data to low-cost big data stores.  Analytics are enriched as more data is retained and all data remains accessible.

BDWE

In his Impact Brief, Shawn makes three important observations about how enterprises can benefit:

Cost Control: A common cost to traditional data warehouse environments is planning for the exponential growth of data. The Cisco solution analyzes the system, identifies data not in use (cold data) and provides a workflow and tools to offload the data onto Hadoop avoiding upgrade costs and extending the life of the data warehouse.

Improved Performance: By implementing an ongoing strategy to offload data from the primary system to Hadoop, the Cisco Big Data Warehouse Expansion solution frees up resources providing for better overall system performance. Additionally, Cisco deploys data virtualization technology that adds a layer of optimization for fast queries and simplified access spanning the original warehouse and the new Hadoop data store. Further, Cisco UCS servers are optimized for Hadoop workloads.

Added Analytic Value: Many companies are forced by the economics of data management to implement aggressive Information Lifecycle Management (ILM) policies removing data from critical systems to avoid costs. The Cisco solution helps customers keep more data online and available for deeper and more insightful analytics, therefore, adding value to the overall environment.”

The report ends with the following conclusion:

“EMA recommends that organizations that manage mature data warehouses investigate offloading as a strategy to expand and extend their data warehouse investment.”

If Shawn’s counsel makes as much sense to you as it does to me, then let’s get started.

Click here to download and read the entire report.

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

To learn more about EMA research, analysis, and consulting services for enterprise line of business users, IT professionals and IT vendors at www.enterprisemanagement.com.

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New Horizons, New Possibilities: Announcing Data Virtualization Day 2014

With Big Data, the Cloud and the Internet of Everything transforming our world, the possibilities are staggering.  And status quo means falling behind.  These truths drive Data Virtualization Day 2014’s theme: New Horizons, New Possibilities.  

This year marks the fifth anniversary of Data Virtualization Day, the premier data virtualization industry event, where IT leaders stay informed of the latest trends and meet fellow innovators.

As host of Data Virtualization Day 2014, I would like to personally invite the entire data virtualization community to come together on October 1st, 2014, at the historic Waldorf Astoria in New York City, New York.

Our objective is to help you explore these new horizons and imagine these new possibilities.  In particular, Data Virtualization Day will address:

  • Why Big Data, the Cloud and the Internet of Everything are transforming business and IT?
  • How is data virtualization advancing to meet these opportunities?
  • What new data virtualization-based solutions are on the horizon?
  • Who is achieving significant business outcomes today?

Maintaining the Data Virtualization Day tradition, the all-day agenda will feature three data virtualization user case studies, presented by those users.  Past speakers have included CTO, CDO, and other executives from Goldman Sachs, Pearson, Comcast, NYSE, Franklin Templeton, Bank of America, Qualcomm, Sky Broadcasting and more.  And we are lining up a power-packed line up again this year to provide you with complete, insiders’ views into their advanced data virtualization deployments including business challenges, organizational transformation, technology adoption, and more.

Watch highlights from our customer presenter at Data Virtualization Day 2013.

Beyond the user speakers, industry analysts and Cisco executives will provide insights into trends and solutions that you can use as you map for your business’s data integration strategy.

And furthering the Data Virtualization Day tradition, winners of the 2014 Data Virtualization Leadership Awards will also be announced.  These are the best of the best.  Enjoy as we celebrate their accomplishments.

So join me, along with data virtualization’s vanguard, to explore these new horizons and imagine these new possibilities.  Registration is easy.  And the event is free.  Register now. 

Learn More

To learn more about Cisco Data Virtualization, check out our page

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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.

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