GlobalLogic Data Platform

Accelerate the journey from data silos to generating actionable insights using GlobalLogic’s Inhouse Data Platform Accelerator



Although extracting value from data across an enterprise is a modern-day imperative, many businesses continues to struggle with the challenges of big data architecture, technology stacks, and hosting capabilities required for ramp-up. GlobalLogic Data Platform Accelerator enables businesses to implement a fully functional, end-to-end data platform within a target or greenfield cloud account within days instead of months. Leveraging cloud native PaaS technolgoies, our data platform helps businesses gather enterprise-wide data, transform and enrich it, and deliver it to anaylsts for extracting value and insights.

Supported Platforms

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Industry Agnostic

Technologies/Works well with

Azure: DataBricks, Data Lake, Blob Storage, Data Factory, Spark, Hive
AWS: S3, Glue, Managed Airflow

Business Needs

Eliminate silos of data that create roadblocks in generating insights and value

Implement consistency around the infrastructures, technologies, pipelines & processes used to work on data projects

Provide transparency around available data / adaptors / pipelines to eliminate inconsistences & duplications

Manage the tedious, non-trivial and lengthy process to provision, configure, integrate, setup security, access control

Enable role-based access control across data, data processing, platform configurations and APIs

Accelerate data processing & align with business requirements

Jump-start the data science team's ability to create and experiment with AI/ML models

Create a next-gen data platform and future strategy with limited expertise

Value Proposition

Centralized and unified data lake infrastructure on cloud. Single source of truth for various stakeholders and teams

Standard Architecture leveraging Industry best practices using cloud native PAAS technologies

Modular, flexible and extensible template based framework that allows customisations at run time, enabling easy to create tailored solutions

Effective and efficient discovery of data sources, data component assets and data enabling consistency, standardization, reuse and eliminating inconsistencies and duplications

Centralized role based access control across all data, components and user interfaces including CLI and APIs

Jump-starting the data science team’s ability to create AI/ML models

Headstart with OOB framework, features and subsequent reuse resulting in

  • Effort and cost savings.
  • Faster time to market and Faster value realization

Big Data processing through industry standard Spark based framework


Dpa core capabilities

Core Platform Capabilities

  • Template based data pipeline orchestrator supporting Apache Airflow / Managed Airflow and Azure Data Factory
  • Support of various Data Integration patterns:
    • Structured Batch-Push
    • Structured Batch-Pull
  • Standard data integration zones (raw, staging, refined) and well-scoped Hot and Cold (archive) zones
  • Supports Sophisticated data analytics and AI/ML capabilities powered by AWS Athena, Sagemaker Notebooks or Databricks platform
  • Automated platform installation
Dpa administrative

Data Platform Configuration

  • Data Source Management
    • Manual and automated schema registration
    • Ingress endpoint management
    • Fully-automated resource provisioning
    • Ownership and access control management
  • Project management
    • Specifying source Data Source(s)
    • Egress endpoint(s) management
    • Fully-automated resource provisioning
    • Ownership and access control management
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Administration Capabilities

  • User management
    • User Registration
    • User role assignment
    • Flexible role based access control
  • Job monitoring and management
    • High-level tracking and monitoring of Jobs
    • Self-service analysis and troubleshooting
  • Platform Portal
    • Authorization and Authentication
    • Services Integration Hub
  • Ingress/Egress endpoints
    • API,J/ODBC endpoints enabling ingestion and data usage by external analytics solution