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.

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.

Save Big Money with Big Data

Data in data warehouses doubles every 2.5 years. For users, this means more data to analyze, leading to better business outcomes. That’s the good news. The bad news is that this extra storage capacity and computing power comes at a cost. A high cost it turns out.

So what is an enterprise to do?

Keep writing bigger and bigger checks to the data warehouse vendor? At least the business can take advantage of the extra data?

Or should they move some of the lesser-used data to tape? That will save money. But it will also limit business access to this now “off-line” data which may mean missed business opportunities.

What if there was a third option that would preserve the on-line access for the business analysts and control these escalating costs for IT?

Cisco’s new Big Data Warehouse Expansion solution announced this week at Cisco Live provides this third option.

Log in here to access the presentations at Cisco Live on Cisco’s new Big Data Warehouse Expansion.

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.

Components in the solution include:

  • Cisco UCS optimized for big data stores.
  • Cisco Data Virtualization for federating multiple data sources.
  • Appfluent VisibilityTM to deliver analytics on business activity and data usage across Teradata, Oracle / Exadata, IBM DB2, IBM Netezza, IBM® PureData™ for Analytics and Hadoop.
  • Cisco Services methodology for assessing, migrating, virtualizing and operating a logically expanded warehouse.

If you are looking for a solution to your rising enterprise data warehouse costs, look no further than Cisco.

Follow us @CiscoDataVirt to stay up to date on the latest news!

Data Virtualization: Live at Cisco Live! San Francisco

It has been a great year for Data Virtualization at Cisco Live!   Milan, Melbourne, and Toronto were fantastic opportunities to introduce Data Virtualization to Cisco customer and partner audiences.  And we have saved the best for last with multiple activities at Cisco Live! San Francisco.

We kick things off on Monday May 18 with a by-invitation program for Cisco Data Virtualization customers and prospects.  We start the day at 3:00 with a special pass to John Chambers’ keynote address.  This is followed by a reception, data virtualization demo and tour in the World of Solutions hall.  And we close the evening with a dinner at one of San Francisco’s finest restaurants. Participants in this program return on Wednesday night for a special performance by Lenny Kravitz.   If you would like to join us, please contact Paul Torrento at ptorrent@cisco.com.

For those of you attending the full event, Data Virtualization is also featured in two sessions both entitled, Driving Business Outcomes for Big Data Environment.  I will lead a quick summary session on Thursday at 11:15am, with Jim Green providing a deeper-dive technical session from 11:30-12:30 that day.   In these sessions we will address one of the major issues organizations are facing as a consequence of exponential data growth – that is the huge expenses required to upgrade capacity in their enterprise data warehouses. To avoid this spend, customers are looking for lower cost alternatives such as offloading infrequently used data to Hadoop.  In these sessions you will find out about Cisco’s complete solution with Unified Computing System hardware and Data Virtualization software and Services methodology.

Please also stop by the Data Virtualization booth in the Cisco Services pavilion where we can chat about your business outcome objectives and how data virtualization can help.

And if you can’t make it to Cisco Live! San Francisco, then no worries.  Just check out the recording of my colleague Peter Tran’s session, Utilizing Data Virtualization to Create More Business Agility and Better Decision-Making, from Cisco Live! Milan.  It’s a great crash course intro to data virtualization.

Data Virtualization: Achieve Better Business Outcomes, Faster

Bob Eve, Director, Product Management
View Bob Eve’s original post on Cisco Data Center’s Blog

Data, Data Everywhere!

The challenge of making business decisions in a networked world isn’t a lack of data. It’s having data residing in multiple systems, global locations, locked away in spreadsheets, and in people’s heads.

Almost every enterprise faces this data silos challenge to a greater or lesser degree. But how businesses address it makes the difference between becoming a market leader or an “also-ran.” The fact is, better information leads to better decisions and better business outcomes. The Harvard Business Review (Big Data’s Management Revolution, October 2012) stated that data-driven companies are 5 percent more productive and 6 percent more profitable than their competitors.

Being able to easily access and use vast data stores has always been difficult. But in just the past few years, the problem has become 10 times worse. If it was just more data, then more compute and database horsepower could fix it. The bigger issues for businesses are proliferating data silos and ever-expanding distribution.

Data Virtualization to the Rescue

Industry-leading businesses are addressing the challenge with data virtualization. Data virtualization is an agile data integration approach that organizations use to:

  • Gain more insight from their data
  • Respond faster to accelerating analytics and business intelligence requirements
  • Reduce costs by 50 to 75 percent compared to data replication and consolidation approaches
  • Data virtualization abstracts data from multiple sources and transparently brings it together to give users a unified, friendly view of the data that they need.

Data Virtualization Presents a Unified View

Armed with quick and easy access to critical data, users can analyze it with their favorite business intelligence and analytic tools to drive a wide range of business outcomes. For example, they can increase customer profitability. Bring products to market faster. Reduce costs. And lower risk.

To read more about what Data Virtualization might mean to your enterprise, check out our new white paper Data Virtualization: Achieve Better Business Outcomes, Faster.

The Fourth V in Big Data

Bob Eve, Director, Product Management

View Bob Eve’s original post on Cisco Data Center’s Blog

At Cisco Live! Melbourne, I was invited to speak at the Executive Symposium to nearly 100 of Cisco’s top customers in the Australia and New Zealand region. In mytalk, Gaining Insight from the Big Data Avalanche, I covered big data business opportunities and technology challenges.

To level set at the start, I opened with a definition of big data, including the typical velocity, volume, and variety seem to be the three V’s everyone hears when it comes to big data. But then I challenged the audience to consider the fourth and in fact most important V, holding back on identifying it so the audience could consider what was missing.

After an appropriate pause, I told them the most important V was value. Value is the only reason to work on big data. This value must be seen in better business outcomes such as:

  • Higher Customer Profitability
  • Faster Time to Market
  • Reduced Cost
  • Improved Risk Management
  • Better Compliance
  • Greater Business & IT Agility

It is interesting how people get knocked off guard by the big data buzzwords. So go back to the basics. Start by getting your business case in order. Once the value to the business is understood, juggling higher data velocity, volume and/or variety becomes an engineering problem. Certainly, a new class of engineering problem, requiring new technologies and skills, but it is a fully solvable engineering problem nonetheless.

For IT, big data is as much an organizational change challenge, as a technology challenge. Practical first steps that seem to work well include:

  • Experiment with a smaller, “SWOT” team on a selected set of projects. This is a great way to introduce something new.
  • Go for some quick and easy wins, rather than boiling the ocean with large-scale initiatives. That is a proven technique for gaining momentum.
  • Implement a solution with revenue impact, such a next-best offer analytic to improve upsell performance or a predictive churn analytic that helps reduce customer defection. These high visibility projects will ease business funding challenges and improve executive visibility / sponsorship.

 

Big Data Analytics – Better with Data Virtualization

Big Data Analytics Make Business Sense

Big data analytic opportunities are abundant, with business value the driver. According to the Professors Andrew McAfee and Erik Brynjolfsson of MIT:

“Companies that inject big data and analytics into their operations show productivity rates and profitability that are 5% to 6% higher than those of their peers.”

Read More

Archiving with Big Data = Better Business Results

Business Value from Mixing Current and Historical 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 decisions.And while recent data may be available in from operational systems and some summarized historical data available in the data warehouse, the traditional practice of archiving older, detail-level data offsite on tape makes business analytics challenging, if not impossible, because the historical information needed is simply unavailable.

Read More

Counting Down to Data Virtualization Day 2013

Take Big Advantage of Your Data with Composite and Cisco

Today, the difference between business leaders and also-rans is how well they leverage their data.
And with big data and cloud causing data to be more distributed than ever, world-class data virtualization and networking technology have become critical to this success.

With the acquisition of Composite Software, only Cisco provides this powerful combination.

Read More

Pacific Northwest BI Summit 2013

A Unique Industry Event

For the past twelve years, Humphrey Strategic Communications has hosted the Pacific Northwest BI Summit, a unique, invitation-only executive networking event brings together leading BI industry influencers, vendors and press in a low-key, relaxed setting to discuss the current and future directions of BI.

More Participants This Year

This is the sixth time I have joined in this event, with 2013 having the largest set of participants.

Read More

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