4 Benefits of Using Reference Architecture in Big Data Analytics

by December 8, 2015 0 comments

– Siddhesh Nayak, Director Enterprise Business Group, Lenovo India

Big data projects are not all alike. What works for one company, may not work for another. This is where the role of reference architecture solutions for big data analytics comes in.

Reference architecture is a combination of models in various architecture domains. They provide the technical blueprints to simplify complex solutions. A reference architecture therefore brings the much needed value of synergy amongst each of the solution building blocks, with the flexibility needed to meet the user’s requirements.

Siddhesh Nayak Director Enterprise Business Group , Lenovo India

Siddhesh Nayak
Director Enterprise Business Group , Lenovo India

Companies therefore need to find the right combination of building blocks to fit their needs. They include hardware, software and services along with a standardized blueprint that enables companies to quickly deploy cost-effective remedies to analyze data. The solutions are built around a combination of servers and networking equipment so as to enable users to deploy the Big Data solutions quickly.

With reference architecture solutions, companies can address requirements to ensure faster and lower risk implementations and take on a holistic approach.

The four benefits of deploying reference architecture solution are:

Ease of integration: Deployment using a reference architecture helps ensure the new solution works with what companies already have in place and are likely to add later, such as data warehouse, stream compute engines, internal and external storage devices and more.
Flexibility and simplicity: A reference architecture helps strike a cost-effective balance between requirements of the solution and time-to-value, offering flexibility for enterprises to adapt as their big data requirements evolve.
Faster deployment: Reference architecture specifying pre-integrated components can also include an integrated, factory-built and factory-tested cluster solution that companies can roll into their data center and put to work right away. Add to this an optimized software stack that relies on open source code, and users can get the total solution up and running faster with much less trial and error.
Quicker access: Every business is looking for fast time-to value. There is no letup in data volumes, economic pressures or competitive demands. The accelerators and pre-built analytics tools for developers and business users incorporated in the reference architecture mean solutions are working harder sooner.

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