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Big Data as a Service architecture

amosferrari on ‎06-18-2014 09:44 AM

Amos-Ferrari_Badge_vertical_3.pngWhat architecture do you need for Big Data services?


In a previous blog, I wrote about the concept of Big Data services; here I will expand on HP HAVEn (the HP Big Data Solution platform) and the architecture that will enable Big Data as a service.


Tomorrow’s integrated Big Data context requires the introduction of an integrated Big Data Platform that, by linking all data sources with internal transaction data, and by enabling real-time processing and consumption of all types of data, will generate value to the business.


Over the past several years, virtualization and cloud computing have drastically impacted data center infrastructures, leading to new architectures. However, on-premises big data solutions are not typically virtualized, and essentially have the opposite impact of virtualization: A big data workload (i.e., Hadoop) is typically spread across several physical servers, versus multiple workloads consolidated to one physical server.


When it comes to specific on-premises implementations of Big Data technologies, HP has reference architectures for the different distributions of Hadoop, as well as reference architectures for HP Vertica and HP Autonomy.


What are the functionalities we have to consider that will drive different choices when it comes to technology design for Big Data as a service? The following model represents the Big Data IT service architecture.



big data service.png


What are the key elements?


  1.       Your Big Data Services architecture – with catalog, portal, and metering and chargeback – as an expression of what services can be orchestrated and delivered, because this will clearly outline your Big Data strategy and responsibilities when acting as a broker between the business, the consumer and the other data providers.
  2.       The Policies and Procedures that define governance for your big data services. This should be an extension of the approach used to govern all of your enterprise data. At a minimum, data governance embraces privacy, security, compliance, data quality, metadata management, master data management, and the business glossary that communicates definitions and context to the business community.
  3.       Your Big Data Infrastructure, Platform and Applications. These will enable you to create and support all big data services provided, including management of all physical and virtual resources. 


Big Data technology standards: HP HAVEn technical mapping

Expanding the representation of the HP HAVEn offering into the Big Data architecture module will enable us to better understand and position each technology as it relates to the functionalities expressed above.


tech mapping.png


HP is and will be able to provide a full coverage of needs leveraging partnerships and open sources.


I would like to stimulate a discussion around this concept and the catalog as keys to the transformation of IT infrastructure to Big Data Services. What do you think? Please drop a comment in the box below.


Key Takeaways

A service model for IT needs to be considered when adopting Big Data technologies. HP has reference architecture modules that will enable acceleration of Big Data adoption. And with our new HP Enterprise Planning for HAVEn Service, HP can help customers quickly move into their IT transformation.


With the HP Big Data Infrastructure Transformation Workshop along with the HP Enterprise Planning for HAVEn Service, you can choose the best service to start planning your big data journey. The Workshop can help you build a roadmap for your Big Data infrastructure strategy, while reducing risk and accelerating decision-making.

About the Author


I’m a Global Strategist, a certified (PMI) Project Manager, specializing in business to IT alignment, agility consulting, Infrastructure Transformation and Strategic Architecture for Big Data, Mobility, Private Cloud, Unified Communications and Collaboration. I drive the strategy, vision and content of strategic consulting services in the Big Data IT Infrastructure services area at HP. As part of this, I meet with senior level customers to understand their challenges, conduct workshops to determine future vision and roadmaps as well as presenting at industry and analyst events.

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