Social Media Analytics



Social Media Analytics

1 0


social-media-proposal


On Github prodaea / social-media-proposal

Social Media Analytics

Node / Mongo and Data

The Premise

  • The Social Media App was an award winning POC
  • Development was abandoned, but hey, let's not let it die
    • Needed some architectural suppport
    • Needed some analytical support

What are we trying accomplish?

  • Connection
  • Transparency
  • Simplicity
  • Leadership

Connection: Who's really doing what they say?

  • Connect real-world data with social inputs to predict social media truthyness

Transparency: Tell users what they'll like and WHY

  • Historical data analytics
  • Social network analyitcs
  • Noise to signal prediction (dark horse trends)

Simplicity: Only deliver what people need, when they need it

  • Development goal is an API Platform
  • Focus on data & analytics
  • Give clients the ability to manage business rules and dashboards

Leadership: Position EPAM as a leader of social analytics

  • Primary source for asset recommendations
  • SaaS and publicly available datapoints
  • Consultants for building relatable content exposure

What technical competencies will we gain?

  • Node.js
  • Mongo DB
  • Social Data APIs
  • Analytics & Big data

What will clients gain?

  • Analytics that engages their users
  • Analytics that informs their decisions
  • Analytics that can be tested and validated

WHAT IS IT GOING TO COST?

Staffing

  • Javascript Engineer/MongoDB Engineers
  • Analytics expert

Scope

  • Limited to movies (finite data set)
  • Real-world data model (Ticket sales data source)
  • Two social data models (Twitter & Facebook)
  • Data validation (testing that demonstrates how accurate conclusions are)
  • Additional publication requirements

Prerequisites

  • Access to a large EPAM hosted Node and Mongo stack

Estimate

  • Assumptions
    • Development will be full time, additional time will be for consultation with analytics dept.
    • Development environment is available
    • 1 FT Javascript Engineer
    • 1 FT MongoDB Engineer
    • Analytics consultation available
    • Scope completed in 2 months
  • Hours
    • JS Engineer: 320 hours
    • MongoDB Engineer: 320 hours
    • Analytics Consultations: 80
    • TOTAL HOURS: 720 Hours
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