Big data is driving the development of applications in today’s connected world. Organizations now need immediate support for instream processing of data using modern analytics platforms to develop use cases like fraud detection, health care services, and weather forecasts, among others. Earlier, the requirements were not demanding and the app development process was reactive as fewer sources generated data, which was then analyzed and processed to take actions.
Traditional technologies like relational databases and methodologies like waterfall development have been the default ways to build apps for many decades. But these techniques are being pushed beyond their limits to keep up with the growth in data sources and user loads, coupled with the way applications are built and run today. The business needs to go faster — running in real-time — and today's demands exceed what is possible with 30+ year old technology. Relational databases do not support horizontal scaling and lack of performance in a distributed environment.
The need for data modernization
To meet the new data modernization requirements, applications should be able to process both structured and unstructured data from various sources and address the four Vs of data – Volume, Velocity, Variety, and Veracity. Digital-native competitors are disrupting established markets and out-innovating the incumbents by doing away with legacy processes and technology. Forward-looking organizations are moving towards NoSQL database environment to be able to process large volumes of data even in a distributed hybrid cloud environment.
Modernization procedures include the following steps:
A toolkit to make the data modernization task easier
An effective data modernization toolkit will help project teams to migrate from relational databases to NoSQL databases like MongoDB.
This modernization toolkit should have the following capabilities:
Wipro has collaborated with MongoDB to develop a data modernization toolkit called DigiTrek, which leverages Informatica PowerCenter and Informatica Intelligent Cloud Suite to help businesses automate the migration of data workloads from legacy systems to MongoDB.
This modernization toolkit includes:
Modernizing with MongoDB, enterprises are becoming more and more intelligent by building new business functionality 3-5 times faster, scaling to millions of users wherever they are, and cutting costs by at least 70%. Read here about how we are helping organizations across the globe in their journey to become Intelligent Enterprises, leveraging data, analytics, and artificial intelligence (AI).
Global Senior Partner Manager for Technology Partnerships at MongoDB.
She works closely with product management, engineering, and sales teams to ensure the success of technical integrations as part of joint customer solutions. In her previous roles, Dana worked at early-stage startups, learning how technology is a fundamental component in modern organizations.
Rama Chandra Murthy
Practice Leader and Lead Architect for the Data Analytics and Artificial Intelligence practice at Wipro.
He works closely with client architects, project delivery teams, and consulting teams to ensure the success of technical integrations as part of joint customer solutions. In his previous role, he worked as Practice Head for the Data Virtualization practice at Wipro.