NextGen Data Platform

A cloud-native solution that enables real-time data analytics and serves as a foundational service for artificial intelligence solutions

100% available, including consulting services for the assessment of business use cases, architecture customization, migration, and enterprise support.


Next-Gen Cloud Architecture

Converts expensive, outdated infrastructure into a modern fully managed data platform


Near Real-Time Processing

Minimize batch processing by pushing as much data as possible into streams


Cost Efficiency

On average, customers see a 30% reductions of costs after migration from legacy infrastructure


Streaming Data Lake

Big Data meets Streaming. Reliable and consistent ingestion provides governance for downstream data lake


Streaming Data Warehouse

Sink materialized views into Redshift or Snowflake data warehouse and plug into traditional analytics tools


Open Source and License Free

Built with native cloud services combined with open source components and best practices of running distributed data platforms at scale

01. Cloud migration

Migrate from an aging on-premise platform to the cloud

Scale your IT requirements to align with the business needs of your organization

Reduce operational costs while improving IT processes across your organization

Easily integrate with 3rd-party services and tools to achieve agility and flexibility organization-wide

02. Optimization for big data

Handle growing data volume and velocity

Achieve optimization for the Big Data V’s — Volume, Velocity, and Variety

Shorten the window for data processing and handle growing amounts of data in real-time

Transform into a data-driven organization to empower decision-makers with insights

03. Data lake

Implement a data lake with robust data pipelines and analytics

Utilize a data lake’s flexibility to store information in its native form for easier data analysis, more efficient auditing, and compliance

Eliminate data silos and simplify access to data through a single data management platform

Extract value from data quickly to enable cross-organizational enterprise reporting

04. Real-time analytics

Adjust traditional analytics to meet real-time needs

Gain critical insights into customer behavior and the sales process to boost revenue, or prevent potential damage

Dramatically improve service quality by finding and eliminating operational problems instantly

Optimize the way your IT approach analytics — from on-request reporting to real-time reports across your organization

05. Data pipelines re-architecture

Fix disjointed architecture for more efficient data pipelines

Enable a smooth and automated flow of big amounts of data across your organization

Near-instantly access data from multiple streams for analysis and visualization

Take advantage of flexible schemas to transport data as-is to avoid source conflicts, duplicates, etc.

06. AI & ML initiatives

Enhance and re-architect infrastructure to pursue AI & ML initiatives

Combine and capture data from multiple streams to generate insights from large volumes of streaming data in real-time

Scale data integration across your organization through continuous, scalable streams and build advanced real-time applications

Empower your Data Science teams by letting them work on handling data, building and training models, and moving them to production instead of doing DevOps work

Optimize cost of ownership
for existing data processing
and storage infrastructure

Migrate legacy Hadoop
(Cloudera, Hortonworks, MapR)
infrastructure to the cloud

Migrate legacy ESB
(Tibco, Informatica) to state
of the art architecture

Scale, optimize, and reduce
cost of DWH
(Redshift or Snowflake)

Build a Data
Lake Foundation

Plan Machine
Learning initiatives

Combine disjointed data silos into consistent and accessible solution for business stakeholders, analysts, product managers, and engineers


NextGen Data Platform

Baked into your organization in 5-6 months to drive your business performance

Implementation Phases


State of the Art Data Platform

  • Data ingestion, enrichment,
    processing, cheap storage,
    realtime and analytical query APIs
  • Legacy jobs and pipelines migrated and optimized

DWH experience

  • Ad-hoc analytics API
  • Reporting API

Streaming experience

  • Change data capture
  • Consistent processing
    and enrichment

Data Lake experience

  • Metadata-rich Data Catalogue
  • Cheap storage for data at rest
    decoupled from compute
  • SQL interface for ad-hoc queries

Foundation for Machine Learning

  • Feature Store
  • Consistent, versioned datasets
  • In-stream inferencing
    of ML models


  • Complete CI/CD infrastructure
  • Infrastructure as code for all
    the components of the platform
  • Monitoring and alerts based
    on the industry best practices


Take a closer look at
NextGen Data Platform on AWS

Download Solution Brief

How It Works on AWS


Start your implementation journey


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