Big Data Analytics

An organization business decision lies on an ability to analyze the data, irrespective of its source, size or type. Technologies like data warehouse, business intelligence and analytics, data visualization in real-time have taken decision-making processes of a business to a whole new level.

Big Data Analytics solutions can be seamlessly integrated with legacy systems to deliver smart, advanced, real-time analytics for speedy decision making.

Our consultants are proficient in executing a thorough analysis and providing solutions which are just right for our clients. We perform end to end implementations for designing, creating, and maintaining powerful Business Intelligence solutions. Our services are aimed to offer insight into competitive markets by leveraging Hadoop and MongoDB solutions and augmenting their existing systems. SrinSoft has successfully deployed Hadoop clusters and MongoDB data manipulation platforms to myriad of industry verticals in achieving their business specific goals.

Possibilities using Big Data

Business Intelligence
  • Reports and dashboards
  • Alerts and notifications
  • Metrics and scorecards
  • Mobile BI
  • Budgeting, planning, and forecasting
  • EPM& CPM
  • OLAP
  • (Relational/Multi-dimensional/Hybrid)

Supportive Tools: IBM Cognos TM1, SEQUEL

Data Visualization
  • Self-service and collaborative BI
  • Visual querying and augmented BI
  • Geospatial visualization
  • Dynamic data and data in motion
  • Data discovery
  • What-if-modeling
  • Self-learning
  • Big data visualization
Big Data design, architecture and development
  • Helping to define the applicable business use case(s)
  • Technology assessment and determination of right platform to integrate
  • Evaluation and definition of the architecture
  • Proof of concept and prototyping development
  • Benchmarking for performance
  • Development on databases, cloud apps, data warehouse and appliances, and hardware
  • Automation tool development for deployments, admin tasks and performance monitoring
  • From scratch app engineering for new big data platforms implementations
  • Building of distributed systems to ensure scaling
  • Algorithm development to handle custom processes
  • Re-engineering of apps for map-reduce and NoSQL platforms

Supportive Tools: Hadoop, Mongo DB