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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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Learn More

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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The Power of a Complete Data and Analytics Strategy

This week, I’ll join my Cisco colleagues and industry peers at Strata + Hadoop World in San Jose. Participating in conferences such as this is one of my favorite parts of my job, because it gives us an opportunity as an industry to share information, learn from each other, and tackle challenges collectively with creative Data and Analytics solutions.

Cisco created an Analytics 3.0 architecture that enables data and analytics solutions in the Data Center, the Cloud, and at the network edge, and has made substantial investments in each of these areas as a company. As we have the opportunity to meet and collaborate at Strata + Hadoop World, the Cisco team can tell you all about our substantial investments in these areas. More importantly, you will hear about how Cisco is delivering solutions in partnership with innovative companies who are leaders in big data, analytics and business intelligence.

Speaking of innovative partnerships, today, I am excited to share the announcement of a joint Data Warehouse Optimization solution with Informatica. The solution provides a single platform for offloading processing and storage from data warehouses to Hadoop and enables organizations the ability to integrate and analyze more data and types of data. If you are attending the conference this week, I encourage you to visit the Cisco booth (#831) to hear more about this exciting new solution.

By bringing the best software, hardware and services from Cisco together with innovative and market leading capabilities of our partners, Cisco is enabling powerful solutions to the very real data problems our customers are facing. Data Virtualization is a key part of Analytics 3.0, because it allows you to connect multiple different data sources, make all the data appear as if it’s all in one spot, and serve it up with a consistent shape and format to an application and eventually to an end user. Take data from traditional data warehouses, Hadoop clusters, lots of edge places and make it all look to an application like its sitting in the data center in one central data base. This also saves application developers from re-writing applications to take advantage of data that lives at the edge. They can simply write applications as they always have and we can pull that data together wherever it lives – all across the network, in the cloud, and between clouds. Powerful on its own…even more powerful together with our partners.

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Is it Time for a Data Mart Diet?

We’ve all heard the expression, “you can never have too much of a good thing.” But we all know that’s not quite true. For example, a little dessert is good. But too much can be a problem for your waistline.

It seems data marts also fit this pattern. A few data marts can be very helpful, but too many create a huge total cost of ownership (TCO) burden.

Fortunately, with data virtualization, you can turn physical data marts into virtual ones. And when you do, you will never have to worry about having too much of a good thing.

What’s Great about Data Marts

Data marts were developed as a complement to enterprise data warehouses. Typically subject or domain specific, and derivative of the warehouse, they provide a number of benefits including:

  • Focused Content – Narrowing the scope to a specific domain such as finance or sales simplifies reporting and analysis.
  • Query Performance – Offloading workload from the enterprise data warehouse can improve query performance.
  • Data Structure – Certain reporting tools require certain structures, for example star schemas. Data marts can easily be modeled based on these structures as an alternative to the warehouse schema.
  • Local Control – Users find it easier to control and modify data marts than larger warehouses.

Costs Can Outweigh the Benefits

Given the benefits cited above, data marts have proliferated rapidly. Unfortunately, as with deserts, “A moment on the lips can be a lifetime on the hips.” Data mart TCO is huge. Costs include:

  • Development Costs – Each data mart requires a full design, development and deployment effort.
  • Operating Costs – Not only does the data need to be refreshed regularly, all the underlying databases, database servers, ETLs and more must be monitored and tuned.
  • Change Management Costs – Adding new data to respond to business change requires extensive rebuilding of complex data mart schemas and ETL scripts, adding costs and reducing agility.
  • Data Governance and Quality Costs – Because data is physically replicated in each data mart, each mart requires data governance to ensure consistent quality.

Data Virtualization to the Rescue

As an alternative to physical data marts, many organizations now use data virtualization middleware such as the Cisco Data Virtualization Suite, to create virtual data marts. Virtual data marts provide all the benefits listed above with far lower costs.

  • Development Costs – Virtual data marts have far fewer moving parts, which lessen design, development and deployment efforts.
  • Operating Costs – Fewer moving parts also means less infrastructure to maintain.
  • Change Management Costs – Adding new data to respond to business change can be done in minutes or hours via virtualized data sets, rather than days or weeks in the physical data mart world.
  • Data Governance and Quality Costs – With data virtualization, data mart content can be centrally governed to ensure consistent quality wherever that data is used.

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If you agree that it makes sense to lighten up on data marts, the question is how?  In other words, what is the “Data Mart Diet?”

Fortunately Rick van der Lans, data virtualization’s leading independent analyst, has created the perfect Data Mart Diet program in his latest data virtualization white paper, “Migrating to Virtual Data Marts using Data Virtualization.”

This whitepaper include a step-by-step approach for migrating physical data marts to virtual data marts using Cisco Information Server. Steps include:

  1. Recreating Physical Data Marts as Virtual Data Marts
  2. Improving Query Performance on Virtual Data Marts
  3. Identifying Common Specifications Among Virtual Data Marts
  4. Redirecting Reports to Access Virtual Data Marts
  5. Extracting Definitions from the Reporting Tools
  6. Defining Security Rules
  7. Adding External Data to Virtual Data Marts

This guidance, along with the cost-benefit summary included at the start of the paper, make this paper a must read for organizations who are seeking a data mart diet.

 

 

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Where is Cisco Data Virtualization Going in 2015?

Welcome to 2015!

If you are like me, the New Year is a great opportunity to assess where I am at and where I am going.  So let’s do that for Cisco Data Virtualization.

2014 – A Year of Exciting New Products

Before looking ahead at 2015, let’s first take a look at 2014 highlights.

2014 was an incredible year for new Cisco Data Virtualization products:

  • In 2014, we shipped Cisco Information Server (CIS) 7.0, a major release of our flagship data virtualization offering. CIS 7.0 extended data virtualization to new audiences, enabled larger, more-complex deployments and integrated more data sources so our customers can run their businesses more effectively by leveraging all of their data.
  • On the big data front, we announced Cisco Big Data Warehouse Expansion, 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.
  • And with our December 11, 2014, Connected Analytics Portfolio announcement, Cisco added a rich suite of analytics solutions that help organizations capture insights that create new opportunities, simplify business operations, enhance the customer experience, and resolve potential threats.

2014 Adoption Success

2014 was full of amazing Customer Adoption successes as well.  The individuals who drove a number of these successes were recognized with Data Virtualization Leadership Awards at the fifth annual Data Virtualization Day on October 1st at New York’s Waldorf Astoria.

  • Paul Dzacko, Lead Architect, Risk Systems, BMO and James Evans, Architect & Project Manager, Client Portal, HSBC were awarded Data Virtualization Champion Awards in recognition of their leadership in consistently achieving and promoting data virtualization’s value across their organizations and the broader data integration market.
  • Victor Campbell, Principal Architect, Long Island Power Authority (PSEG) received the High Impact Award in recognition of data virtualization leadership in an environment where the result was high impact and critical to the business.
  • Pratima Botcha, Sr. Technical Architect, Information Technology, AT&T Services was given the High Impact Award for her work in enhancing business agility through use of data virtualization technology and methods, rapidly establishing a path for high value across the organization.

2015 Will Be Bigger Than Ever

In 2015 the pace of change across the enterprise data landscape will continue to accelerate, disrupting how organizations compete.

The biggest driver of change is massive messy data everywhere, spanning many sources – cloud, data warehouses, devices – and formats – video, voice, text, and images.  This distributed data landscape increasingly relies on data virtualization to bring order to the chaos.

To meet these needs in 2015 and beyond, Cisco Data Virtualization’s strategy is multi-faceted including:

  • Simplify Use And Adoption – To provide agile data access to today’s self-service business users, Cisco will expand beyond Business Directory, which was data virtualization’s first offering developed exclusively for business users.
  • Expand Data Virtualization’s Core – To address more sources and higher volumes and more, Cisco will continue to broaden our platform to scale reliably for the largest workloads and most complex requirements.
  • Leverage Cisco Technology – Fortunate to be part of Cisco, we will take advantage of a broad range of Cisco offerings including our Nexus interconnect capabilities, UCS servers, software such as Tidal Enterprise Scheduler and more.
  • Bring Data Virtualization’s Benefits to Big Data – Cisco Data Virtualization will continue to strengthen big data deployments with significant data abstraction, federation, directory, delivery, security and governance functions.
  • Enable Intercloud and Internet of Everything (IoE) – As Cisco pioneers new Intercloud and IoE solutions, Cisco Data Virtualization capabilities will expand to meet these new challenges.

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Beyond capability advancements, Cisco will greatly expand our coverage, partnerships, Customer Advisory Community and more as we go to market globally.  Stay tuned to this blog throughout 2015 as we make formal announcements.

Happy New Year!

 

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Cisco Connects Data and Analytics

Billions of devices are changing how organizations compete and disrupting traditional data management and analytics.

This Internet of Everything world presents an exciting new opportunity to discover and take advantage of market, customer, and operational insights. And by making sense of captured data quickly, organizations can take action at that point, in that moment, in ways that differentiate versus competitors and drive significant new business value.   TimeWarnerCable’s intelligent home initiative is one example.

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But all this data is massive, messy, and everywhere, spanning many sources – cloud, data warehouses, devices – and formats – video, voice, text, and images.  To address this challenge, new solutions beyond traditional data warehousing and even big data are required.

Cisco Enters the Data and Analytics Market

When Cisco acquired data virtualization market leader Composite Software in mid 2013, Cisco signaled a clear intent to begin connecting this data via intelligent networking the same way it connected LANs; the Internet; voice and video over IP; and more in it’s 30 year history.

And with our December 11, 2014, Connected Analytics Portfolio announcement, Cisco adds a rich suite of analytics solutions that help organizations capture insights that create new opportunities, simplify business operations, enhance the customer experience, and resolve potential threats.

New Methods for the New Challenges

Today’s analytic solutions need to advance beyond traditional methods that move data to a warehouse or data lake before commencing analysis.  Cisco’s Connected Analytics Portfolio provides analytics with immediate access to data, as well as brings analytics to the data – no matter where the data resides on the network.

Further, Cisco is uniquely qualified to implement analytics at the point of data, because so much of the data worldwide resides on our networks, providing the ideal platform for embedded analytics.  Along with 30 years of networking experience, Cisco now has the data and analytics tools, software, and services to help our customers instantly capture, analyze, and interpret critical data out to the network edge.

 

Learn More

Visit our Data and Analytics website to learn more.

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