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Case studies

DocCULL

SaaS-based solution for Advanced culling and analytics

  • Development time

    11 Months

  • Resources involved

    4 Professionals

Overview

The client sought a SaaS based solution for documents analytics, email thread analytics, document tagging and custom analytics for their data analytics product suit.

Business Goal

Consolidate the data from different mediums.

Optimize the data extraction and loading process.

Perform data analytics on top of the aggregated data from different sources.

Provide tagging, custom document viewer and data analytics on top of the data.

Challenges

There were multiple challenges while developing the solution like,

Consolidating the data from various sources available in different formats.

Aggregating, cleansing the data and delivering scalable architecture for data analytics solution.

Building the custom document viewer & providing accurate tagging for documents.

Solution

System architecture

  • Our Java Web development team provided end to end data analytics solution with the help of our Big Data development team & Machine learning development team.
  • We analyzed various possible data sources, defined standard data structures and pipeline for data retrieval.
  • Once all possible sources were identified, we developed common schema architecture for the documents in distributed index.
  • We also developed various custom utilities for data extraction and information retrieval.
  • Our Big data development team delivered the solutions for Key phrase, domain analytics as well as Email thread analytics using prominent Big Data tools.
  • Finally we delivered the solution with custom document viewer based on clients requirements and we also delivered training, maintenance support to client organization.

Technologies

Implementation

We divided the solution into multiple deliverable modules across different teams like Big Data, Machine Learning and Java Web Development.

Then we followed an iterative phased approach to implement the solution that included the following phases:

Business requirements analysis.

Architecture design.

POC building & Scaling.

Backend implementation.

Performance tuning.

We followed the above phases iteratively, as we faced challenges and requirement changes while development.

Road map

Requirement Analysis
  • Brainstorm
  • Innovation
  • Research
  • Resource planning
Architecture Planning
  • Architecture Design
  • System Prototyping
  • Documentation
Development
  • Back end development.
  • Front end development.
Quality Testing
  • Quality Assurance.
  • User Acceptance Testing.
Deployment
  • Production
  • Evaluation

Business Benefits

We delivered a sophisticated data analytics solution to our client and as a result our client organization was able to visualize various things from top level. We also provided efficient tagging and document viewer which is the USP of the solution and as a result DocCULL became a part of enterprise search suit of our client.