The Structure of the Big Data Framework
The Structure of the Big Data Framework
The Big Data Framework is a structured approach that consists of six core capabilities that organizations need to take into consideration when setting up their Big Data organization. The Big Data Framework consists of six main elements, as can be seen in figure 1 below:
- Big Data Strategy
- Big Data Architecture
- Big Data Algorithms
- Big Data Processes
- Big Data Functions
- Artificial Intelligence
Figure 1: The big data framework
Big Data Strategy
Data has become a strategic asset for most organizations. The capability to analyze large data sets and discern patterns in the data can provide organizations with a competitive advantage. Netflix, for example, looks at user behavior in deciding what movies or series to produce. Alibaba, the Chinese sourcing platform, became one of the global giants by identifying which suppliers to loan money and recommend on their platform. Big Data has become Big Business.
In order to achieve tangible results from investments in Big Data, enterprise organizations need a sound Big Data strategy. How can return on investments be realized, and where to focus effort in Big Data analysis and analytics? The possibilities to analyze are literally endless and organizations can easily get lost in the zettabytes of data. A sound and structured Big Data strategy is the first step to Big Data success.
Big Data Architecture
In order to work with massive data sets, organizations should have the capabilities to store and process large quantities of data. In order to achieve this, the enterprise should have the underlying IT infrastructure to facilitate Big Data analysis. How should enterprises design and set up their architecture to facilitate Big Data? And what are the requirements from a storage and processing perspective?
The Big Data Architecture element of the Big Data Framework the technical capabilities of Big Data environments. It discusses the various roles that are present within a Big Data Architecture and looks at the best practices for design.
Big Data Algorithms
A fundamental capability of working with data is to have a thorough understanding of statistics and algorithms. Big Data professionals therefore need to have a solid background in statistics and algorithms to deduce insights from data. Algorithms are unambiguous specifications of how to solve a class of problems. Algorithms are unambiguous specifications of how to solve a class of problems. Algorithms can perform calculations, data processing and automated reasoning tasks. By applying algorithms to large volumes of data, valuable knowledge and insights can be obtained.
The Big Data algorithms element of the framework focuses on the (technical) capabilities of everyone who aspires to work with Big Data. It aims to build a solid foundation that includes basic statistical operations and provides an introduction to different classes of algorithms.
Big Data Processes
In order to make Big Data successful in enterprise organization, it is necessary to consider more than just the skills and technology. Processes can help enterprises to focus their direction. Processes bring structure, measurable steps and can be effectively managed on a day-to-day basis.
Additionally, processes embed Big Data expertise within the organization by following similar procedures and steps, embedding it as ‘a practice’ of the organization. Analysis become less dependent on individuals and thereby, greatly enhancing the chances of capturing value in the long term.
Big Data Functions
Big Data functions are concerned with the organizational aspects of managing Big Data in enterprises. This element of the Big Data framework addresses how organizations can structure themselves to set up Big Data roles and discusses roles and responsibilities in Big Data organizations. Organizational culture, organizational structures and job roles have a large impact on the success of Big Data initiatives.
The last element of the Big Data Framework addresses Artificial Intelligence (AI). One of the major areas of interest in the world today, AI provides a whole world of potential. In this part of the framework, we address the relation between Big Data and Artificial Intelligence and outline key characteristics of AI.
Many organizations are keen to start Artificial Intelligence projects, but most are unsure where to start their journey. This guide takes a functional view of AI in the context of bringing business benefits to enterprise organizations. The last element of the Big Data Framework has been depicted as a lifecycle on purposes. Artificial Intelligence can start to continuously learn from the Big Data in the organization in order to provide long lasting value.
To learn more about Big Data, visit our Big Data Knowledge Base. For more information, contact us at email@example.com or drop us a message in the chatbox.
Excepteur sint ocaecat cupidas proident sunt culpa quid officia desers mollit sed.
subscribe to newsletter
Receive more Big Data Knowledge article in your inbox: