N4Mative
Building the Next Generation Data Model

Amidst architecting business solutions for clients in his career, Kevin Gungiah was exposed to the data challenges in the market that created the opportunity to establish N4Mative, driving innovation with Big Data solutions. “We add value to our customer’s environment by architecting, designing and building the next generation data model for them,” says Gungiah, CEO, N4Mative. The Georgia-based N4Mative is a solutions provider, integrator and services company that focuses on building services around three main categories—Cloud services, Big Data and infrastructure.

N4Mative works with clients by understanding their existing use cases or building new use cases and charting the framework on strategy, execution and delivery, providing an end-to-end solution. The company’s data scientists and infrastructure architects help to build Big Data frameworks and supporting workflows. The solutions and services create new revenue streams, provide more efficiency to client environments and better leverage the intrinsic value of customer data. To ensure success, N4Mative partners with key solution providers for a timely cost effective execution.

Organizations are trending towards outgrowing their earlier relational databases, and are looking at ways to be more efficient, competitive, deliver products faster to market and have agile development environments. Early adopters and visionaries have embraced software products of the recent years such as Hadoop to address these challenges. N4Mative is built from the ground up to deliver solutions for variable, high velocity and high volume data using Hadoop and its eco-system across verticals and varying customer use cases.

To meet the client’s most demanding workloads, N4Mative’s infrastructure solutions provide secure, scalable and resilient environments on the cloud. Expert consulting and solution delivery helps customers to step up in their service maturity model.

N4Mative’s expertise and skill sets span the entire workflow from data ingestion to analytics, to present a solution based approach to use-cases built on Big Data Platforms

N4Mative’s “as a service” solutions automate and deliver services to the end user which are built on private and public infrastructure. As a strategic partner for NetApp, N4Mative’s certified NetApp engineers maximize the client investment with NetApp technology. Experienced engineers facilitate the automation of data storage functions to make processes repeatable, tested and error free. A detailed analysis of the data storage environment aligned to best practices in data governance and compliance ensures an effective storage audit.

The company helps customers to execute strategies that address business challenges making them competitive in the marketplace. N4Mative’s consultants are currently working with enterprise level customers that span multiple verticals (Financial, Web, Healthcare, Retail, and Hospitality). N4Mative has been building use-cases for these customers over the last two years giving them an edge over some of their competitors who have just started their Big Data practices. “We collaborate with customers to understand or create use cases and their value proposition to the business.

Then we plan, design, build and deliver on the Big Data platform and take that into production,” says Gungiah. N4mative has successfully delivered on some of the following use-cases:

• Implementation at a web property, their search engine took 4 seconds to answer a query whereas N4Mative’s consultants were able to reduce the time to 1 second using a low cost Big Data platform resulting in added business value.
• Web Log Ingest and Analytics
• NoSQL big data frameworks
• Logical data warehouses
• Multi-format Ingest platforms
• Streaming and Auditing of data

The Big Data ecosystem is getting crowded with new products and offerings from the many players. “At N4Mative, our continued focus is to innovate, research and develop on these new innovations and re-product them to accelerate the adoption rate as well as reduce POC times that clients go through to pick the right technology stack for their use-cases. The strategy for the following years is to develop next generation data models, logical data warehouses, “as a service models” to suit our customer base,” says Gungiah.