Big Data
Indivar provides an automated way for companies to convert a large amount of complex and disparate data into a ready-to- use business model and data store, by using the Big Data Analytics. This empowers owners to quickly and easily visualize, analyze and report data across various sources, without relying much on IT.
Indivar’s approach for Big Data Analytics Project
Our team of Big Data experts at Indivar, proceeds in a comprehensive way to provide the best results to the business owners.
StrategyBig Data is trending these days, and like any new technology, it too requires an effective strategy. By determining the use cases for Big Data services, we can help in crafting an appropriate strategy in collaboration with the key stakeholders of your organization.
ArchitectureIt is important to have an architecture that works well for the primary set of applications, after defining a clear strategy and using big data services. Our consultants possess great experience as big data service provider and guide in the best way that works as per your company’s needs and help in future proofing the applications.
Data WarehouseEnterprises spend a lot of money to maintain their data warehouses and licenses for a proprietary data warehouse are very high priced. With the use of open source platforms of big data solutions like Apache Hadoop, we help customers enhance their warehouses at a much lower cost.
Proof of ConceptIt is good to develop a POC application, that shows that the proposed big data solution and technology stack will serve your requirements. The application’s small scale version or a specific module is tested and implemented in this phase. The goals are set, measured, implemented and as well as the outcomes are evaluated of the POC.
Data ScienceDesigning effective big data solutions includes the process of defining the architecture for your big data, implementing that to the store and retrieving the data. Our team of data analysts possesses great experience in dealing with the analytical models for issues like customer churn prediction, fraud detection, etc.
