Data Science

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Data Science involves extracting insights and knowledge from data through various processes, including data analysis, machine learning, and statistical modeling.

Our services supports data science initiatives by providing the necessary infrastructure, tools, and expertise in the following areas;

  • Data Storage Solutions and Data Warehousing
  • Cloud-Based Data Platforms and Serverless Computing
  • Data Integration Services
  • Data Exploration and Visualization
  • Machine Learning Model Development
  • Data Governance and Security: Data Governance Frameworks, and Data Privacy and Compliance
  • Automated Data Processing: Data Pipelines for continuous data ingestion and transformation.
  • Workflow Automation: Implementing tools for automating end-to-end data science workflows.
Our services enable organizations to derive meaningful insights from their data and make informed decisions.

Data Science - Implementation Approach

1. Objective

  • Batch Data Ingestion
  • Business Intelligence
  • Platform Management

2. Discovery

  • Assessment of Enterprise Data Estate
  • Platform Assessment - BW, Power BI, Azure
  • Identified key improvement areas

3. Planning

  • Business Priority driven use cases
  • “Best in Breed” products identified
  • Business Onboarding Plan
  • Well Defined Implementation Plan mitigating S/4 risks

4. Design & Architecture

  • Future Proof Reference Architecture
  • “Fit for Purpose” product POC’s
  • Platform Architecture per Enterprise Standards

5. Development & Delivery

  • Iterative Delivery Model
  • Change Control in place

Data Science - Value Add

Supportability and Scalability

  • Source System Rationalization
  • Reduced No of Ingestions
  • Reduced Integration Patterns

Data Integration & Processing Optimization

  • Data Integration & Processing Optimization
  • Reduced Duplicate Ingestions
  • Increased CDC based Ingestion
  • Faster E2E Performance

Capabilities & Governance

  • Business Glossary Capability
  • Self Service Intelligent Dashboard Visibility on Data Catalog
  • System driven Cost Traceability Centralized Access Management

Cost Optimization

  • Data Integration & Processing Optimization
  • Reduced Duplicate Ingestions
  • Increased CDC based Ingestion
  • Faster E2E Performance