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Get Your IT Infrastructure Ready for Big Data, Part 1: Modeling the “As Is” State

“How should my IT architecture change to take advantage of new Big Data technologies? How should I prepare, and what should I prioritize?”

 

These are typical questions that IT managers are asking us when they’re considering a Big Data initiative.To help answer these questions, HP has developed a Transformation Workshop that will help frame the conversation and determine key initiative points and action items.

 

The basics of a transformation start with a description of the “As Is” and “To Be” models.

 

How is the IT Infrastructure designed today when it comes to data, and what are the critical aspects that need consideration? In order to effectively evaluate the current state (As Is) of a data-related IT Infrastructure environment, certain critical aspects need to be assessed. These typically can be described as follows:

  • Information is: managed in efficient silos; separated by type of data; and separated by process.
  • Typical transaction data are generated by business applications like SAP that use a very structured RDBMS as a way to store information and operate the business.
  • Business information collected from different application systems and different structured data sources is currently stored in a central data warehouse used for business intelligence and analytical purposes.
  • Some silos of information are collected and stored, while others are completely or partially deleted.
  • Some silos have information that resides in the cloud.
  • EACH information silo has its own governance operation and security policy tools and processes in place.

 

The consequences of this architecture include the following:

  1. Most of the data is not collected.
  2. Possible relevant data is resident in different silos and is difficult to access .
  3. Operation Governance and Security are very focused and optimized for each silo.
  4. Actual data store technologies are limited when it comes to dealing with large volumes of data.
  5. Unstructured data is typically not managed.

We can represent the actual AS IS status using the following model.

Big Data TEW As is  v0.4.png

This can be considered a high level IT architecture model, as it refers to the data infrastructure organization inside the IT infrastructure.

 

The question is: how can we deal with the different ”V’s” of Big Data (like Volume, Velocity, Variety or Voracity) and what are the possible impacts on “As Is” IT architecture?

 

I’ll tackle those questions in an upcoming blog. Keep watching this space!

 

Learn how the HP Big Data Strategy Workshop can help you refine and define your path to Big Data.

 

Read how HP Big Data Consulting can help you create greater business value from your data.

 

Update, 12.5.12: This week at HP Discover in Frankfurt, HP announced new services that can help your organization plan, deploy and support a Big Data environment. Click here to learn more about one-day workshops that focus on your Big Data infrastructure strategy, analytics infrastructure or storage platforms; and to learn how the new HP Proactive Care for SAP can help you speed up the analysis of large amounts of enterprise data.

 

 

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About the Author
I’m a Global Strategist, a certified (PMI) Project Manager, specializing in business to IT alignment, agility consulting, Infrastructure Tra...


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