Enterprise Data Hub (EDH) Setup for Enhanced Data Management

A Case Study on Building a Centralized Data Repository for Comprehensive Business Insights

At a glance

The Enterprise Data Hub (EDH), built with CDH and Elasticsearch, serves as the company’s central data repository. The project aimed to develop a Customer 360 view using EDH data. Elasticsearch powers Kibana dashboards for business reporting, while Hive and Impala support structured reporting and ad-hoc querying. DataCouch optimized the architecture for secure, scalable, real-time data access and analytics.

Implementation

DataCouch helped develop and optimize the Enterprise Data Hub (EDH), ensuring smooth data processing, storage, and analytics while maintaining robust security protocols.

Unified Data Processing

Data Munging/Processing was handled using Spark 2.x DataSet API for efficient handling of large datasets.

Advanced Reporting

Elasticsearch REST API was used to serve real-time data to business analysts, enabling dynamic reporting on Kibana dashboards.
Hive was leveraged for reporting, while Impala supported ad-hoc querying for fast, real-time insights.

Security and Architecture

Highly secure cluster with Kerberos and Sentry, ensuring robust access control and data protection.
Utilized Lambda Architecture for efficient batch and stream processing of data.

Challenges

The company needed a unified, secure platform to manage massive amounts of data and enable real-time analytics. Without a centralized data hub, data processing and reporting were fragmented, leading to inefficiencies in generating insights for business decision-making.

Lack of centralization in data, leading to fragmented reporting.

Inefficient querying and processing of large datasets.

Security concerns in managing sensitive data.

Solutions

DataCouch implemented a unified data platform, optimized for high-performance processing and real-time analytics while ensuring security through advanced protocols.