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Three Big Data Integration Plays to Drive More Value from Big Data

Big data and analytics are changing the competitive playing field. Winners will find ways to turn unprecedented growth and complexity of big data, cloud, IoT devices and more into competitive advantage.

The Value of Big Data Integration

Big data itself can provide significant insight, impact and advantage. These outcomes can be multiplied when big data is combined with existing enterprise data or even other big data. These insights can lead to enriched customer engagement, faster new product innovation, higher returns on capital and more. The possibilities are endless. And your competition has the same objectives.

As a result, integrating big data intelligently is a challenge on nearly everyone’s short list. Three patterns of integration have formed around big data integration.

Cisco Data Virtualization is proving a key enabler, delivering many of the capabilities required. With Cisco UCS and key partners including Appfluent, Cloudera, Hortonworks, Informatica and MapR providing additional value add.

Integration Pattern 1 – Hadoop to Hadoop Integration 

The Cisco Hadoop-to-Hadoop Data Integration solution provides a more agile and faster way to access and query multiple Hadoop clusters. This solution enables even “bigger” big data analytics for greater insights and business impacts.

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Integration Pattern 2 – Hadoop to Enterprise Integration 

The Cisco Hadoop-to-Enterprise Data Integration solution provides a more agile and faster way to bring together traditional enterprise data with the new world of big data. Accessing and querying both Hadoop and enterprise data enriches the analytic opportunities and results in better business decisions.

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Integration Pattern 3 – Data Warehouse Optimization Integration

With data warehouse data doubling every two years, data warehouse costs are skyrocketing. To reduce these ever-growing warehouse management costs Cisco and Informatica recently announced a joint Data Warehouse Optimization solution.

This offering combines the hardware, software and services required to successfully offload processing and storage from data warehouses to Hadoop. Not only does it significantly reduce costs, the solution also help organizations integrate and analyze more data and types of data, and thus drive greater business impacts.

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At Strata + Hadoop World last week, I discussed this new solution with Jim McHugh, VP of UCS & Data Center Solutions Marketing at Cisco.

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To learn more about these solutions and how Cisco’s rich portfolio of big data and analytics solutions can help you unlock the value of your big data, check out these two on-demand seminars:

Unlock Your Competitive Edge with Cisco Big Data and Analytics Solutions

Analytics Solutions for Driving Better Business Outcomes

 

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Learn More from My Colleagues

Check out the blogs of Mala AnandMike Flannagan and Nicola Villa to learn more.

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New Research Identifies How to Accelerate Data Virtualization Adoption

The challenges of data management are getting exponentially harder. These ever-increasing data quantities, diversity and distribution are revolutionizing data management, opening the door for new solutions such as data virtualization.

Data virtualization fulfills a range of business demands for data, supports high iteration and fast response times, all while saving significant IT costs.

Radiant Advisors is a leading strategic research and advisory firm that helps transform today’s organizations into tomorrow’s data-driven industry leaders.  They recently teamed with Cisco to better understand the barriers experienced by companies considering data virtualization and see how companies that have already adopted data virtualization overcame them.

The Data Virtualization Adoption Dilemma

Data virtualization is an advanced technology with nearly every major research and consulting firm provides architectural blueprints that include a logical business semantic layer.

Yet only some companies have it, leaving data virtualization an often-missed opportunity for business and IT to keep pace with today’s volatile data landscape.

To achieve the benefits of data virtualization, companies need to take the leap.

Unique Research Formula

To better understand data virtualization adoption barriers, Radiant Advisors’ Research Director, Lindy Ryan, interviewed a broad, pre-adopter community to understand their perceptions and concerns.  These top-of-mind issues were then posited to companies that have already adopted data virtualization, who then anonymously shared the insights, best practices, and lessons they learned in overcoming barriers to data virtualization adoption.

The resulting research report, Overcoming Barriers to Data Virtualization Adoption, consolidated these findings into clear counsel intended to guide potential adopters to overcome perceived barriers.

Read The Research

Download Overcoming Barriers to Data Virtualization Adoption here.

 

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Analytics for an IoE World

I recently wrote about how Cisco is helping customers more effective manage massive amounts of data, types of data and unprecedented distribution of data. This will be one of the toughest challenges brought on by the Internet of Everything (IoE) and, with solutions such as Data Virtualization and Big Data Warehouse Expansion, Cisco is enabling our customers to meet the challenge head on of bringing all of this data together in ways that are meaningful to business users.

After the business can access and view all of this data, however, the question becomes…now what? The next challenge is to extract insights from the data to make better business decisions.  After all, more data is only good if you use it to make better decisions than you would have made otherwise.

The rules of customer and business relationships are constantly changing due to technological innovation and consumption patterns. Analytics can reveal patterns in customer data that affect business processes and outcomes. Advanced analytics is different than reporting because it prescribes what to do, or predicts what is likely to happen, instead of just reporting what has already happened.

Utilizing the network to securely connect data throughout the IoE, whether in motion (streaming) or at rest (historical), is the future of advanced analytics.  For a retailer, it will give them the opportunity to take intelligent actions to engage customers directly at the point of purchase and in real-time. But it’s so much more than that. What can real-time analytics in retail tell us about how to serve customers more effectively?  What can real-time analytics in manufacturing tell us about how to make the workplace safer?  What can real-time analytics in healthcare tell us about how to better treat cancer patients?

When our customers can accurately predict outcomes by combining years of historical data with real-time information, they can drive better decisions…better outcomes.

 

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Interested in hearing how Cisco is paving the way to the future of analytics? Please join us for a webcast at 9 AM Pacific time on October 21st entitled ‘Unlock Your Competitive Edge with Cisco Big Data and Analytics Solutions.’ #UnlockBigData

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Aligning Solutions to Meet our Customers’ Data Challenges

In our previous big data blogs, my Cisco associates have focused on the topic of building the best infrastructure for long-term success with big data. I’d like to start a new chapter in the series, focusing on building the right data strategy and analytics solutions.

Today, people, process, data and things function together through a combination of machine-to-machine, person-to-machine and person-to-person connections. We call this the Internet of Everything (IoE). While the IoE is making us all smarter, it is also creating more data, more types of data and in more places.

This wealth of data comes with major challenges but also has the potential for amazing opportunities. At Cisco, we’re all about helping our customers turn these challenges into opportunities. The first step begins with proper management of the massive amounts and types of data in multiple locations. From a solutions perspective, that first step is our agile data integration software, Cisco Data Virtualization. It abstracts data users need from multiple different sources and brings it together to give users a unified, friendly view of the data.

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By leveraging this technology with additional solutions, our customers can access data across the IoE and use that data to respond quickly to change, make better decisions and gain a competitive advantage. Driven by the massive amounts of data in today’s IT environment, customers are facing huge expenses to add capacity to their existing enterprise data warehouses (EDW), the place where data is traditionally stored.

We help customers tackle the challenge of increasing enterprise data warehouse costs with Cisco Big Data Warehouse Expansion (BDWE). BDWE identifies infrequently used data and provides a methodology and tools to offload the data onto Hadoop, avoiding additional capacity costs and extending the life of the data warehouse.

I spoke with a customer recently who shared that one terabyte (TB) of data in an EDW costs $100,000 per year to maintain. That exact same amount of data for the same amount of time in Hadoop only costs $1,000 to maintain. This is a significant difference. By implementing an ongoing strategy to offload data from the primary system to Hadoop, our solution frees up resources to be utilized in more strategic ways. Additionally, we deploy Data Virtualization to act as a ‘virtual database,’ to access data regardless if it resides in the original warehouse or the new Hadoop data store. So not only does BDWE significantly lower costs, but the historical data remains easily accessible.

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Our customers gain the business insights and outcomes they seek with a complete suite of software, hardware and services solutions that access and analyze data, no matter where it is stored on the network. After all, the power of data is not just in the ability to access it but to use it to change behavior or the way you run your business.

Not only do we connect more people, processes, data, and things than any other company, we can also bring analytics to data wherever it is—no matter how remote—to turn information into insights almost instantly. More to come in my next blog about Cisco’s analytics portfolio and how its helping tackle the next major IoE challenge, extracting value insight from your data.

 

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To learn more about the benefits of Cisco analytics solutions and the power of our integrated infrastructure for big data, please join us for a webcast at 9 AM Pacific time on October 21st entitled ‘Unlock Your Competitive Edge with Cisco Big Data and Analytics Solutions.’ #UnlockBigData

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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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