When it comes to your organization, big data implementation is what can make the difference in decision making and profits of the company. The benefits a business can gain from analyzing data can be quite broad. However, business gains so much from enterprise big data analytics. The primary advantage of big data analytic is the business intelligence that translates into high profits. For a company with issues on how to implement big data, the following are best practices.
Step 1: Analyse business requirements
The first step is to find out the operational requirements. When you understand the business requirements, you can align the big data projects to the particular business needs.
Step 2: Make implementation agile
It is important to ensure the implementation is both agile and iterative. Business agility gives the business the capability to respond to changes when necessary.
Step: 3 Business decision-making
Enterprise big data analytics solutions are only viable for business if it was done from a business perspective rather than an engineering perspective. This means that solutions must be tailor-made for the business and not implemented generally.
Step 4: Make use of the data you have
Use the data you already have. Using the existing data gives you an edge in your business decisions you make.
Step 5: take advantage of the legacy system
If you have legacy data systems, it is important to keep them, because the cost of abandoning them can be quite high.
Step 6: Implement the system from bottom-up
It is not possible to implement the big data analytic in the entire organization at once. The best way is to implement gradually.
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