Big Data is assisting companies to harness their data and derive better insights for making smarter, real-time and fact-based decisions leading to more efficient business operations with improved productivity and increased profit margins. However, deployment of big data in any organization requires careful planning with efficient data management, smart deployment policies and choosing the right approach.
Let’s take a look at how organizations can make the shift to big data using some of the information that we’ve shared below.
Top things to know for assessing your enterprise’s big data deployment readiness
Organizations need to build solid partnerships with core business leaders to find big data opportunities and move ahead with their support. The full adoption of big data requires an understanding of how big data will culturally influence your organization, skillsets that need to be acquired and identify technology requirements. Here are a few key factors which organizations need to consider before going ahead with the big data initiative:
Type of decision- using big data making model and organizational culture of the company
According to the research done by the Economic Intelligence Unit by PWC, almost 30% of the senior managers take decisions based on their expertise and intuition. Almost 28% of them listen to their employees, whereas only 29% depend on data for the purpose of analysis. But the new age data analysis tools can be used effectively in organizations that work based on the culture of decisions made using facts and free exchange of information and not restricted by the hierarchy.
Flexibility of business model and its core processes
It may not be as easy to introduce new methods of analysis within the organization as there might be some modifications which may have to made into the organization’s functioning. There could be financial, regulatory or cultural barriers which may exist in an organization that may make the new process completely ineffective. Before taking the big data initiative, it’s important to assess if your company can manage the transformation of its business model and key processes.
Business objectives to be achieved
Every organization has different purposes and reasons for using Big Data and hence it’s important to have a clear idea about your business goals and objectives. The data does not produce any results unless it is used for achieving key business objectives by keeping the existing business conditions in mind. For this, you need to be clear about the expectations and requirements and how your resources can be utilized effectively for deployment of data.
Decision making driven by best big data practices
The main purpose of data is to drive decision makers to take the best decisions based on data and factual information which has been made easy with the evolution of new technologies in the areas of data collection and integration. In this regard, it may be imperative to get to know some of the best big data practices and equip your staff with the required knowledge.
Key considerations while making the shift towards big data
Aligning big data initiatives to meet stakeholder’s requirements
Only when the stakeholders clearly specify their requirements for their big data initiative, it can be called as ready for production. The criteria set for production readiness must meet the requirements of the stakeholders which is again dependent on the use cases and applications they would like to have using Big Data. The Service Level Agreements for performance, availability, governance, compliance, auditing and monitoring will depend on the specifics of every big data application, according to the priority and criticality assigned to these tasks by the organization.
Re-engineer data management and IT analytical processes
It’s imperative that the organization should be able to provide efficient, seamless and reliable user training, trouble response and other support functions for the existing operations. Big Data users need to have access to a single platform which can take care of all maintenance, support and service related issues. Organizations must be able to offer support for consulting for planning, deployment, integration, customization, and management of the key big data initiatives. Big Data support functions need to be automated as much as possible.
Boosting skillsets in big data among the enterprise
Data-driven enterprises need to bring in the expertise of data scientists as consultants who can help in identifying requirements, planning the roadmap and assist in the development, deployment, and management of big data initiatives for the organization. It’s important to connect your team with the community of big data users so that they can learn about the best practices and emerging trends in big data.
Focus on scalability and building technology stacks
It’s important to architect your environment for greater scalability so that it can keep pace with the data growth of your organization. In short, you must be able to add, re-allocate new storage and improve network capacity in the existing system in a fast and cost-effective manner to meet the new requirements. Databases, middleware, tools, and applications which comprise of the big data technology stack need to be hardened so that they can address the entire scope of SLA’s related to the main use cases.
Conclusion
Big data can have a real and positive impact in the way in which organizations can make use of their data but the cost of deployment of such systems can be quite high. Hence, it’s imperative for organizations to evaluate all the technological, management, and material competencies before deciding to go ahead with it.