The Top 6 Critical Capabilities of a Big Data Framework

big data framework

The Big Data Framework for enterprises comprises a structured approach. It considers the six fundamental capabilities that enterprises need to make the best of Big Data and enjoy long-lasting value. Big Data Framework for enterprises is rooted in high-end technology and provides deep insights into the core components of Big Data.

Why Choose A Big Data Framework?

Frameworks provide structure. The Big Data Framework also plays a similar role. Big Data needs structure and capabilities to offer extended success.

The Big Data Framework was developed to help organizations establish a successful Big Data practice. The Big Data Framework structure makes it easy for organizations to account for all organizational capabilities of a fruitful Big Data practice.

The main benefits of using the Big Data framework are:

  • It provides a structure for organizations looking to launch Big Data or wanting to further improve their Big Data capabilities.
  • It helps in considering all organizational aspects in a Big Data organization.
  • As it is vendor independent, the Big Data framework can be applied to any organization regardless of the technology leveraged or tools used.
  • You get a common reference model to be used across departmental functions.
  • It identifies core and measurable capabilities in every domain that the organization can develop as they progress.

Organizations may have the most advanced computers and processors but will not serve any purpose without the knowledge and skills needed to operate and manage them. The Big Data Framework helps improve the knowledge of those interested in Big Data.

This framework provides a holistic structure while recommending the components that enterprises need for their Big Data organization.

The Big Data Framework Consists of the Following Six Main Elements

Big Data Strategy

Data has emerged as one of the crucial assets for many organizations, so it is vital to analyze large data sets accurately and detect patterns. Organizations that have the capability to analyze large volumes of data gain a competitive edge.

Enterprise organizations must put in place a sound Big Data strategy to achieve concrete results from their Big Data investments. Likewise, they must know the areas to focus on in Big Data analytics, as the options and possibilities are endless. So, a sound and structured Big Data strategy can help organizations make the best use of Big Data.

Big Data Architecture

Growing organizations often deal with colossal volumes of data. Organizations must develop adequate storage capabilities to manage these massive data sets and to store and process them effectively. So, it begins with developing a solid IT infrastructure to facilitate Big Data.

A comprehensive Big Data architecture is imperative for organizations to enable Big Data analysis. Moreover, the key questions that arise in such situations are:

  • What steps must be taken to set up enterprise architecture and simplify Big Data?
  • What are the storage and processing requirements?

The Architecture element of the Big Data Framework takes into account the technical capabilities of Big Data environments. It considers the different roles present within a Big Data Architecture and inspects the best practices for design.

Big Data Algorithms

While working with large volumes of data, it is imperative to have a clear understanding of the statistics and algorithms of data. Big Data professionals must know how to extract insights from data. Algorithms offer explicit requirements for solving a class of problems. They perform calculations, process data, and automate reasoning tasks. Using algorithms on large data volumes allow for great insights.

Big Data Processes

To ensure the success of Big Data in an enterprise organization, Big Data professionals must go beyond skills and technology. They must focus on the processes that can help enterprises move in the right direction. Processes help create solid structures and measurable steps. Additionally, they also infuse Big Data know-how within the organization. The analysis of data is thus less reliant on individuals. It improves the chances of capturing value in the long term.

Big Data Functions

Big Data functions are associated with organizational aspects of Big Data management in enterprises. This component of the Big Data framework helps organizations create the proper structure and set up Big Data roles and responsibilities.

The Big Data Functions part of the Big Data Framework covers the non-technical aspects of Big Data. It provides input about setting up the Big Data Center of Excellence (BDCoE). It also helps understand the factors needed for successfully launching a Big Data project in the organization.

Artificial Intelligence

Artificial Intelligence (AI) is one of the essential elements in the Big Data Framework. The immense potential and capabilities of AI are well-known and extensively documented. So, AI helps create a whole new range of possibilities and potentials.

Organizations know the importance of starting Artificial Intelligence projects, but most are unsure where to begin. The Big Data Framework has a practical approach to AI in terms of creating benefits for organizations. AI is the natural forward-going process for organizations that have developed other capabilities of the Big Data Framework. Also, Artificial Intelligence can gain knowledge and information from Big Data and provide long-lasting value.


The components of a Big Data Framework include the technical aspects of setting up a Big Data architecture and the soft skills needed to set up a Big Data center of excellence. Also, organizations must take a capabilities approach to improve their competencies over time. So, this will help in confidently including the practice of Big Data in the enterprise.