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.

Learn More

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

Join the Conversation

Follow us @CiscoDataVirt.

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.

Learn More

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 http://www.enterprisemanagement.com.

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.

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.

Join the Conversation

Follow us @CiscoDataVirt #DVDNYC

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.

How Data Abstraction Works Part 1

Organizations today understand that better access to information assets can improve their bottom-line.

But they struggle with the variety of enterprise, cloud and big data sources, and all their associated access mechanisms, syntax, security, etc.  Further, few data sources are structured properly for business user or application consumption, let alone reuse.  And often the data is incomplete or duplicated.

Read More

Data Virtualization’s Logical Role in the Logical Data Warehouse

I have been closely following Gartner’s Logical Data Warehouse (LDW) strategy for the past year and a half.

Read More

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.
Read More

What Is Your Strategy for Responsive Enterprise-wide Data Sharing?

Sharing Data Is Difficult, Yet Important

Large enterprises learned long ago that effective sharing of data across lines of business was a critical success factor. But achieving this objective in large organizations has been especially complex due to:

  • Thousands of information consumers with varied roles and responsibilities;
  • A range of analysis and reporting applications addressing different business problems;
  • Multiple approaches to access, combine, and deliver data to these applications; and
  • Extreme data source volumes, variety, velocity and complexity.

Read More

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