Big Data
IEMS automates the process of converting large amount of disparate and complex data into a user-ready business model and data store. This empowers analysts and business owners to easily analyze, visualize and report data across various sources without relying on IT. We gather data from multiple sources like large data warehouses, web clickstreams and social media to build a 360 degree view of a business. IEMS supports many leading Big Data sources such as Hadoop, Spark, Hbase, Flumes, Map Reduce, Cassandra and more. Our sole aim is to transform your complex data sets into intuitive & effective reports, dashboards and visualizations with the help of big data analytic services so that business owners can have insights into their businesses. We help determine the use cases for Big Data services & further craft a good strategy for your organization. The entire strategy is built in close collaboration with the key stakeholders of your company. This ensures that their requirements are fulfilled & are aligned with big data and analytic solutions.
Architecture
Our consultants possess immense experience as big data service provider. They work closely with customers and provide them integrated big data solutions, which encompasses unstructured & structured data and various other transactional data sources. We also suggest big data and analytic solutions that will work the best as per your needs.
Data Warehouse
We help our customers enhance their warehouses with open source platforms of big data solutions like Apache Hadoop. By aptly designing big data and analytics solution, which meets SLAs, our data architecture experts promise improved performance and reduced cost while augmenting analytical capabilities.
Proof of Concept
At IEMS we work with customers to develop PoC/PoTThe proof of concept is a prototype, which shows that the proposed big data solution and technology stack will serve your requirements. In such phase, the application’s small scale version or a specific module is tested and implemented. We set goals, measure, implement and as well as evaluate the outcomes of POC.
Data Science & Analytics
We have a team of astute data analysts, who possess vast experience in dealing with the analytical models for issues like fraud detection, customer churn prediction and recommendation engines.