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Data Engineering

Discover fresh insights and make them actionable
with our data-engineering-as-a-service.

 
 

Overview

The retail industry generates 15 petabytes of data on a daily basis. The challenge is no longer just the complexity of data but also the “order of magnitude” of data, data type, and data from disparate systems created over generations. Intelliswift offers a Data Engineering-as-a-Service solution to assess the maturity of the current state and assists in building the appropriate Data Engineering Platform for our customers.

Intelliswift is committed to helping businesses accelerate the integration of analytics into business processes and discover new ways to simplify data and amplify its power.

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Our Services

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End-to-end Data
Pipelines

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Data
Transformations

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Data
Integrity

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Data
Models

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Data
Analytics

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Data
Ingestion

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Data
Cleansing

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ETL/ELT
Jobs

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Data
Tuning

Data Acquisition & Ingestion Framework

Our AI/ML/NLU engine applies artificial intelligence and machine learning to analyze relevant named entity recognition
patterns and extract fields of interest from template/format agnostic and multiple sources of dark data

Ingestion Framework
Ingestion Framework

Reports expect the global big data and data engineering services market to grow up to USD 77.37 billion by 2023 – mainly contributed by the phenomenal growth of interconnected devices and social media.

Data Lake Management Framework

Our Data Lake Framework helps you build, assess, and leverage data lake environments with utmost efficiency
& enhanced data capabilities, keeping the data trusted and secure all along.

Management Framework
Management Framework
Management Framework
Management Framework
Management Framework
Management Framework

Key Capabilities

Data Lake Foundations

  • Data Ingestion
  • Metadata and lifecycle pilots
  • Security models
  • Trusted data treatments and publishing
  • Secure export and transport to external platforms for analytics, etc.
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Data Lake Architectures

  • Organizational & Governance models
  • Metadata and data management
  • Security, authentication and auditing
  • Smart suggestions for data access and provisioning
  • Cluster configuration and performance optimization
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Data Lake Analytics

  • Modeling, materialization and preparation for BI tools
  • Event-based analytics
  • Discovery and exploratory analytics
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Technology Stack

Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
Technology Stack
How may I help you?