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Proof of Value Services

See how EPSoft can help you reduce the Implementation time of Big Data Project and reduce the cost.

Proof of Value Services:

Architecture Review

3 Weeks

Review existing systems and architecture
Review use cases
Review related technologies
Development of high level roadmap including technology recommendations based upon current and future user cases

Data Integration

5 Weeks

Set-up of one data ingestion tool.
3 data sources
2 destinations

Typical architecture tools used Flume, Scoop, Nifi and Kafka with Storm
Automation of system deployments, alerting and monitoring will require additional time.

Data Driven Marketing/Advertising Assessment

5 Weeks

Identify marketing goals
Interview the identified stakeholders
High level review of one system architecture and integration
Create a high level roadmap based on your goals
Additional week if an implementation plan desired
Typical marketing assessments include 360 degree view of customer, prospect/lead databases, unified customer messaging, cross channel campaign analysis, customer segmentation, 3rd party data integration and user tracking from pixels/beacons

Real-time data ingestion

5 Weeks

Creation of real-time data pipeline to ingest user behavior, logs, lot sensor data for reporting, analytics and/or storage
Production setup of data pipeline
3 data streams from up to 2 different systems
If more than one data format is used for the streams it will require additional time to develop the solution
We’ve built this on open source technologies including Netty, Kafka, and Storm

Package Offerings

Security Audit

3 Weeks

Security audit of your Big Data platform and integration
Focused on your specific platform or data access security concerns
Review of your existing security policies and configuration
Based on what we find, we’ll give you a summary of findings, recommendations, and implementation plans

Architecture Review

4 Weeks

Overall Assessment
Tuning of one of existing systems or looking doing a query engine system comparison
Often optimizing performance will require data format/layout changes and therefore require data migrations which make take additional time