The Big Data Stack And An Infrastructure Layer

It is great to see that most businesses are beginning to unite around the idea of big data stack and to build reference architectures that are scalable for secure big data systems.

data stack

Dialog has been open and what constitutes the stack is closer to becoming reality. The likelihood of producing repeatable processes that can result in big data success is what we are all striving for.
Many believe that the big data stack’s time has finally arrived. Many are enthusiastic about the ability to deliver big data applications to big organizations. Below is what should be included in the big data stack.

Infrastructure Layer

Your company will require scalable, enterprise-grade computing, storage and networking as you move from the proof-of-concept stage to the production of big data. This transition could be hard for some because in order to have successful big data solutions, there will be a need to scale quickly, and this may place heavy demands on your infrastructure.

Data Layer

This is where your company can manage your data assets and information architecture. New big data solutions will have to cohabitate with any existing systems, so your company can leverage your current investments and then incorporate internal/external data sources. The people, processes and the technology for the data governance will also reside in this data layer, thus ensuring a timely, accurate and complete data so your company can extract maximum value.

Insight Layer

Business information and intelligence applications can be deep-rooted in businesses, and some believe they have clear similarities with their preferred tools. New big data solutions will have to cohabitate with any existing data discovery tools, along with the newer analytics applications, to the full value from data.

Security Layer

This will span all three layers and ensures protection of key corporate data, as well as to monitor, manage, and orchestrate quick scaling on an ongoing basis.

One key business objective with big data is to be able to support the higher data volumes and new data sources. This implies flexibility to be able to add use cases.

By embracing the stack companies will be required to start with a stronger foundation, and to determine if they have the infrastructure and expertise to be able to make everything a reality. Highly secure managed-services model is the best way to deliver infrastructure and analytics applications. This will enable companies to scale rapidly and to make sure there is maximum focus on the applications and to ensure fast and accurate delivery of data driven strategies.

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To learn more about Local Web and what the Data Stack is and the layers of security, visit Layers of Security.

To read more about the data stack and cloud computing, visit Cloud Computing and Data Stack.