The amount of info generated by users is increasing day by day. Currently, Internet users generate nearly 2.5 quintillion dataset every day. This puts enterprises in the position to collect, analyze, and derive insights from this dataset. However, what’s lacking is structure and organization in the way big data operations are carried out. Enterprises lack the means to collect and analyze dataset effectively. A big data framework can help enterprises to build seamless business processes around data.
Need for big data framework
The benefits are clear to businesses. However, many organizations struggle to realize the benefits of data or fail to build an effective big data practice in their organization. Its framework provides companies an effective approach that incorporates all organizational capabilities to build a successful data practice.
Benefits of a framework
A framework is a systematic approach to attain the desired goal. The following are a few benefits that can help companies achieve their info-related goals.
- It provides a structure for organizations to start their big data processes and build their capabilities.
- Such frameworks are vendor-independent and can be used regardless of the technology and tools used by an organization.
- It provides a common reference model that can be used across departments and countries.
- Identifies key areas of organization competencies (mentioned below) that companies can develop over time.
Big data demands a lot of skills. Even with the most advanced tools and technologies available globally, companies will be unsuccessful without requisite skills and knowledge. A framework seeks to address the skills gap by helping companies increase everyone’s knowledge in the big data industry.
Using a framework helps companies follow a holistic approach toward big data. It helps companies see various components that they should consider while setting up their information processes.
Big data frameworks provide a holistic structure for information. It looks at the various components that enterprises should consider while setting up their organization. Each element of such a framework should have equal importance, and organizations can develop only if they pay equal attention and effort to all aspects of the framework.
Structure of a big data framework
Such frameworks define six areas that companies need to consider while setting up their operations. The following are six areas:
Strategy
Big data is a strategic priority for global companies. It is a key area that can provide a competitive advantage to companies. The capability to analyze large sets of information and find out patterns in information gives companies an upper hand in the market. For instance, Netflix uses big data to suggest content to users and even produce shows and tv series. Similarly, Alibaba uses such technology to find out companies that it can loan money to and recommend on their platform.
Big data requires a huge investment. Thus, companies need a robust such strategy that answers how companies can achieve tangible results, key areas that it should focus on, and key roles and responsibilities required to achieve them.
Architecture
It can amount to zettabytes of data. To store and analyze such a large amount of data, companies require large infrastructure. Enterprises and companies should have an infrastructure that can manage and scale operations as the number of information increases and facilitate convenient data processing and analysis.
This part of the framework essentially answers: how should companies design their infrastructure? What are the requirements for storing and processing such a huge amount of information?
Algorithms
Knowledge of algorithms is essential to build data processes. Algorithms are derived from statistics and mathematics. So, knowledge of statistics and mathematics is crucial to excelling in such technology. Algorithms can automate tasks, process reasoning, and derive insights from analysis.
The algorithm part of the framework focuses on equipping talent with the right statistical knowledge and knowledge of different algorithms.
Processes
For companies to succeed in such a tech field, they need more than technology and skills. They require processes that add structure within companies and allow companies to focus on one goal. Processes create structure within a company, add measurable steps, and turn every operation into manageable work. Information storage, processing, and analysis become less dependent on the individual, creating long term value for companies.
Functions
Big data function deals with managing a team and building a holistic, information operation. This part of the framework shows how companies can set up their dataset function, define roles and responsibilities within the function, and set up culture. This part covers the non-technical part of setting up a center. Learning to set up a center of excellence is the major takeaway from this part.
Conclusion
Big data presents an enormous opportunity for companies to increase their productivity, efficiency, and even profitability. Its framework works as a comprehensive resource that allows companies to navigate the data operations and build effective processes around it, which is often challenging, saving it from failing.
