Sreeyan’s Approach of Implementing Big Data:

Big data is still moderately new with numerous associations, and its importance in business procedures and result has been changing each day. Here are some of the key accepted procedures that Sreeyan follows for a successful yet efficient big data implementation.


Gather Business Requirements Before Gathering Data:

Sreeyan initiates big data implementation by first assembling, analyzing and understanding the business necessities. This is the first and most fundamental step in the big data analytics process. Sreeyan’s strong big data team believes in “Align big data ventures with explicit business objectives”.


Implementing Big Data Is A Business Decision Not IT:

You call it a myth or a rumor, but it is true that first time big data implementors think that implementing big data is pure IT thing. Sreeyan does not accept it as we believe that it’s the business that drives the big data implementation not the IT stack. This line wraps up one of the most significant prescribed procedures for implementing big data. Analytical solutions are most successful when drawn closer from a business viewpoint and not from the IT/Engineering end. Sreeyan strong believes that the IT needs to get away from the model of "Build it and they will come" to "Solutions that fit characterized business needs."


Use Agile and Ceaseless Approach to Implementation:

Typically, big data projects start with a case study on a selected dataset. Through the span of implementations, we at Sreeyan, have observed that organization needs grow as they comprehend the information once they touch and feel and start harnessing its potential value. Utilize agile and iterative implementation techniques that deliver speedy solutions based on current needs rather than a big bang application development. When it comes to the implementation of big data analytics, the best practice is to start small by identifying specific, high-value opportunities, while not losing grip of the big picture. We accomplish these goals with our customizable big data framework: Think Big, Act Small.


Assess Data Requirements:

Regardless of whether a business is prepared for big data analytics or not, doing a full assessment of information coming into a business and how it can best be utilized to the business' preferred position is prompted. This procedure as a rule requires contribution from your business partners. We dissect what information should be held, overseen and made open, and what information can be disposed of.


Simplify Skills Shortage with Standards and Governance:

Since big data has such a great amount of potential, there's a developing lack of experts who can oversee and mine data. Short of offering huge signing bonuses, the most ideal approach to beat potential abilities issues is institutionalizing huge information endeavors inside an IT administration program.


Enhance Knowledge Transfer with a Center of Excellence:

Setting up a Center of Excellence to share arrangement information, plan antiques and guarantee oversight for tasks can help minimize errors. Regardless of whether large information is another or extending venture, the delicate and hard expenses can be shared over the undertaking. Another advantage by the CoE approach is that it will keep on driving the enormous information and in general data engineering development in an increasingly organized and systematical way.


Grasp and Plan your Sandbox for Prototype and Performance:

We at Sreeyan, allow data scientists to build their information analyses and models utilizing their favored dialects and programming conditions. At that point, after a fruitful evidence of idea, deliberately reconstruct and additionally reconfigure these usages with an “IT turn-over group”. Sometimes, it might be hard to try and recognize what you are searching for, because the technology is regularly kicking off something new and accomplishing results that were recently marked “isn't possible”.


Sync with the Cloud Operating Model:

Analytical sandboxes ought to be made on-request and asset the executives need to have a control of the whole information stream, from pre-preparing, combination, in-database rundown, post-handling, and diagnostic displaying. A very much arranged private and open cloud provisioning and security technique assumes a vital job in supporting these evolving necessities. Team Sreeyan believes that the benefit of an open cloud is that it tends to be provisioned and scaled up in a flash. In those situations where the affectability of the information permits brisk in-and-out prototyping, this can be powerful.


Combine Big Data with Enterprise Data:

To release the estimation of big data, it should be related with business analytics. Endeavors ought to build up new abilities and influence their earlier interests in foundation, stage, business knowledge and information distribution centers, as opposed to discarding them. Putting resources into incorporation abilities can empower information laborers to connect various sorts and wellsprings of information, to make affiliations, and to make important revelations.


Include Analytics & Decision-Making using Intelligence into Operational Work Process/Schedule

For analytics to be an upper hand, associations need to make "analytics" the way they work together. These days, the upper hand of information driven associations is never again only a decent partner, yet an "unquestionable requirement have" and an "absolute necessity do." The scope of systematic abilities developing with enormous information and the way that organizations can be displayed and determined is turning into a typical practice Analytics need not be left to storehouses of groups, yet rather made a piece of the everyday operational capacity of front-end staff.


Conclusion:

We at Sreeyan has an dedicated team of big data professionals that understands the client’s requirement of big data implementation very well and the secret is to understand the business behind to the core, assess the problems in the day-to-day activities and provide a tailor fit solution that is cost-effective, reliable, scalable with minimal maintenance. If you are looking for a big data solution and want to take your data to the next level, please feel to contact us to book a demo on big data implementation.