Big Data Consulting & Delivery Services

Big Data Consulting & Delivery Services

BigDboy’s - Big Data Consulting Services transform organizational knowledge into insights for more informed and timely business decisions with the best possible TCO.

Our Consulting Services go beyond just "business." We know what it takes to deliver value for your business. We seek to create lasting partnerships with our customers by delivering value for money. We leverage extensive industry wide insights to understand and handle our customer’s requirements. Our reputation for effectiveness, efficiency and reliability ensures success for our customers.

Our Consulting Services helps our customers grow with Big Data.

ANALYSIS & RECOMMENDATIONS

We analyze our customer’s business goals, IT infrastructure, and technical staff’s readiness to develop vendor agnostic recommendations and solutions with the best possible TCO.

INFRASTRUCTURE IMPLEMENTATIONS

We work closely with our customers to implement Big Data infrastructures that leverage and extend our customer’s current IT infrastructure with the best possible TCO. Provide deployment services for deployment onsite using customers’ existing Hardware environment using stabilized freeware solutions and do provide technically capable resources to manage the infrastructure, maintain and deliver the KPI as required by customer.

APPLICATIONS, POCS, & DEMOS DEVELOPMENT

We help our customer’s make sense of their Big Data by developing Custom Applications, Proof-of-Concepts, and Demonstrations that showcase the power of Big Data in their own environment, using our skill set and ability

Big Data System Integrations

We bridge the gap for product vendors to provide professional services to ensure seamless integration & assimilation of their products into an enterprise’s ecosystem.

The practices and technologies that close the gap between the data available and the ability to turn that data into business insight is BigData @ Epitome - BigDboys.

Moving beyond a technology-centric view doesn't mean, however, that a bottom-up, technology-led approach to big data strategy won't work. After all, it's often the case that business executives can't see the potential of a technology until they've seen it in action. A bottom-up approach also provides the opportunity to acquire technical skills, and gain an understanding of what needs to be done to integrate new technologies with existing systems (even if it's just at the level of getting the data out - often easier said than done). But a pilot project or proof-of-concept demonstrating the "art of the possible" in a business context is different from implementing a Hadoop cluster and expecting the business side to start asking for projects.

Even with the most business-centric approach, there is still the risk that pilot projects are run in isolation, leading to deployments that may address a specific business issue, but without taking the wider business and technology context into consideration. The inevitable result: another data and application silo. Hence the importance of having a big data strategy. But where to start? And what should be taken into consideration? These are the five key areas that you need to tackle:

Find a balance between bottom-up (tech-led) and top-down (business-led) planning. Both approaches have their merits, but neither can ultimately succeed in isolation. If you find that the dialog between business and technology professionals seems to be conducted in mutually incomprehensible jargon, focus on finding a common language. If you can't, stop your big data initiative - the investment will be wasted.

Recognize that there is no single 'big data' technology. While Hadoop has a key role to play, big data is about much more than Hadoop (however loosely or narrowly defined). As outlined in Holger Kisker's earlier blog post, different scenarios require different big data technologies. The exact combination differs between organizations, depending on requirements as well as existing environments. In our report Strategic Planning For Big Data: Getting It Right, we introduce a simple framework that can help you on your way.

Big data has many different use cases.While certain topics keep bubbling to the surface (e.g. improving the accuracy of marketing campaigns, augmenting fraud detection, reducing downtime), big data techniques and technologies can be leveraged by any part of the organization. Just like there is no single big data technology, there's no single big data starting point. Your big data road map needs to reflect not only what your company wants to achieve, but also take into consideration ongoing initiatives and existing technology investments. Just make sure you always start with a question.

Make sure that your planning is long-term. What you don't want is another set of silos that's difficult to maintain and expensive to integrate. There will be times when you need to make tactical choices; but it should always be clear how these will impact the long-term strategy, and how any such impact will be dealt with. This is also why it's important to

Put in place an agile, flexible big data platform. You should consider doing so sooner rather than later, to make sure you can cater for different data management and analytics scenarios, including more advanced techniques such as predictive modeling, semantic search and geospatial analytics.

N.B. To send your resume to the best IT companies in the world free of cost, please post resume here

To contact the travel agents and the tourists please find here email database India