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customer360

Hadoop based Customer 360 Demo

Design

Design Flow

Data Ingestion -> Data Pre-processing (Cleansing, Enrichment) -> Data Processing (Co-relation, Aggregation, Transformation etc) -> Predictive Analytics -> Visualization

Tools used

  • Data - Sample data is used from the data generators
  • Data Ingestion - NiFi on the edge node ingests the data from local disk and pushed to HDFS
  • Pre-Processing - Data from External 'Raw' tables is moved to the 'Staging' area
  • Processing - Data is correlated based on fields that can be used to join the data set. Data is pushed into Solr
  • Visualization - Silk AKA BananaUI

Datasets

  • Customer - ID, Name, Address, Gender, Age, Customer Since, social media handle
  • Social Media - handle, message, timestamp,
  • Clickstream - standard
  • Transactions - timestamp, product id, amount etc;
  • Chat History - timestamp, customer service rep id, chat blob

Goal for MVP

There could be future enhancement to this demo but in initial version, we should set the foundation with at least 2-3 datasets, some hive processing, at least 1 model and at least 1 index in Solr.

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Hadoop based Customer 360 Demo

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