Big Data architecture is a mix of data models, policies, standards and rules that govern which data is to be collated, how it will be stored, arranged, integrated, and leveraged in data systems. There is no “one size that fits all” when it comes to the architecture, it has to be designed according to the needs of the business. With the help of cutting edge technology and expertise at Parkar we have been providing unique Data architecture Patterns customized as per business requirements. Each portion of the architecture has alternatives that work out with its own advantages and disadvantages. We start with a smaller subset of the known patterns in the architecture, and as we begin to realize the value for obtaining insight to key business outcomes we expand the extent of use. Big Data architecture is a structured and a systematic approach to ultimately achieving the overall big data objective. It is important to assess whether a business case is a big data problem, or not and then proceed whether it has to be considered or not.
End To End Architecture
At Parkar Big data architecture comprises of the process of designing the logical and/or physical structure of the bigways in which big data will be stored, accessed and managed in a big data or an IT environment. We logically define how the big data solution will work, the core components (hardware, database, software, and storage) will be put to use, and what will be the flow of information, data and information security, and much more. This is a critical step where our team studies the existing architecture and the overall landscape.
The project plan consists of documenting the tasks and activities along with the timelines and necessary approvals. During this project planning phase, weperform Product Stack Evaluation. We plan if the solution should be implemented on-premises, Cloud and using which Big Data Open-source technologies. The next thing is to identify Architecture alternatives, benchmarks, SLAs, etc.
Proof Of Concepts
In this phase, we demonstrate the business value of your data using the data technologies and analytics. We build and chalk out the actual Implementation Roadmap. While doing so, we also propose appropriate Environments required for implementation.
Layout Building Blocks
There are eight building blocks that we have identified in most of our projects. First is the vision, followed by Strategy, Values and metrics, Governance & Trust policy, Resources and the Organization, Data sources, Data management and lastly Data Analytics and Visualization.