Choosing a big data strategy for an organization is a difficult task requiring trained personnel like data scientists and data architects. Some data clusters may even have to go through Data solution Architecture. Recruiting data architects and data scientists is a big task, but an enterprise will also need proper infrastructure and management to create a big data strategy. But if an enterprise cannot go through so many changes and expenditures, big data strategy consulting would be a better option. All of these services come under the umbrella of big data management.
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The right big data strategy has to be connected to the business objectives. This strategy makes decisions data-driven and well-informed. But to integrate its strategy and business objectives, an organization has to find its KPI. These KPIs contribute directly to your business objectives and needs. Finding data sources that deliver value is an important step; this will be proceeded by identifying use cases. All of these steps will help you formulate a data road map; This data road map will help you define how your data will contribute to the gap between your current state and desired state. This roadmap will iterate the data architecture, technology, and skillsets to be used.
These are steps are explained in detail below.
Identifying business objectives
The first step to formulate a big data strategy is to identify business objectives. The strategy is tailored so that it indicates the completion of the business objectives. This helps in making data-driven and well-informed decisions. If the decisions are data-driven and objective, It could do wonders for the company.
The initial requirement is to make sure all the stakeholders are on board. The process will be smooth if all the stakeholders are on board with the expenses and the infrastructure involved.
Identifying the top talent in every team is another prerequisite. These are the people who will help carry on the process further and deliver high-value results.
Skipping this process could result in low value and unimportant results, only diminishing progress.
Internal obstacles like insufficient workforce, lack of infrastructure, and motivation could hinder this process. Therefore, outsourcing would be a better option.
Identifying data sources and processes
The next step is to identify data sources and the variety of data that the organization will analyze to achieve the business objectives decided in the previous step. These sources will give you an idea of the data to be processed.
The next step would be to assess the current business processes, data sources, data assets, technology assets, capabilities, and policies at the organization. Since data comes in very different formats like spreadsheets, documents, databases, log files, videos, images, and text, among other types.
This assessment would give you an idea of the resources and workforce needed for the processes.
Sometimes data processing can be highly complex and may need a data solution architecture that will require data scientists and architects. Managing them would be another task that would create too much hassle for the organization, Instead big data strategy consulting would be a viable option.
Identify and prioritize use cases
To proceed further, Devise use cases for all the data extracted before these will help you put data to use and visualize how your data can contribute to achieving the business objectives.
Prioritize these use cases and allocate the budget accordingly to get the most out of every dollar. These big decisions need analysis and are deciding factors that could make or break your profits; iterating them would be a good idea.
Use Big data Analytics to uncover insights from correlations and patterns; again, this is a complex task that requires expert assistance.
If you choose an external organization to help you, it will decrease the workload on management and the employees and may result in better insights.
Formulating a roadmap
You have successfully outlined the business objectives, identified the data sources, assessed your resources, and finalized and prioritized the use cases. The next step would be to draft the strategy or outline a basic structure of how the data movement takes place and what the action plan would be.
Stakeholders would play a significant role now as they govern the strategy and allocation of the resources.
The roadmap can evolve further as the process takes place. Start with a basic action plan and iterate as you move ahead. A basic action plan with room for improvements will make your strategy agile and adaptable.
There can be many obstacles, and this step could be very time-consuming as it requires the congregation of all the major talent and top management.
A big data strategy is not something different from your business strategy and its importance cannot be downplayed therefore hiring the best personnel available or outsourcing this process is a must.
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