Connected Intelligence Platform

Accelerate Data and Analytics Initiatives on a Unified Platform

TCS Connected Intelligence Platform (CIP) enables businesses to rapidly harness the value of data from enterprise and external sources through analytics while reducing the cost and complexity of big data. CIP includes everything an organization needs to securely ingest, analyze and gain insight from data from machines, sensors, devices, transactional systems, and more. CIP combines an enterprise-grade Hadoop data lake with machine learning libraries, real-time processing of streaming data, a predictive scoring engine, smart workflow management, data visualization, and enterprise-grade security.

With simplified API integrations, CIP helps data scientists, developers, data engineers and business stakeholders go from idea to deployed solution quickly to out-maneuver competitors. The open-source components and pre-integrated all-in-one approach speeds time to value and reduces TCO. CIP is optimized for complex data ecosystems and is used as the foundation for all TCS Digital Software & Solutions Group products in the Customer Intelligence & Insights family as well as TCS Intelligent Urban Exchange.


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Solution Brief

Data remains a core battleground for winning the unified customer experience…TCS’ Connected Intelligence Platform provides an analytic architecture that blends disparate data sources to deliver contextually relevant experiences.

Sheryl Kingstone, Research Vice President & General Manager- VOCUL

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TCS Connected Intelligence Platform

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The TCS Advantage

The low-code, yet robust CIP end-to-end data management and analytics platform enables businesses such as insurance, utilities, manufacturing, CPG, logistics, hospitality and more, to quickly turn data into actionable insights for better decision making.


Accelerated Data Insights
As a pre-integrated data and analytics solution, CIP consolidates raw data from various sources and transforms them into trusted data and insights. CIP includes a Hadoop data lake with integrated real-time analytics environment, visualization, built-in ML libraries, APIs, security and workflow. CIP delivers integrated streaming analytics to act in real-time with a scalable real-time processing engine and machine learning algorithms.  CIP is built with open-source components to reduce TCO, simplify integrations, and deliver value faster. Businesses can derive predictive and prescriptive insights from large datasets, and automate deployment to deliver insights faster for enterprise consumption.


Lower TCO with an Open Foundation Built for Enterprise Scale
As a fully integrated platform built on open-source components, CIP is fully configured with a patented architecture, security, and the tools developers and data scientists need to take advantage of all their data that are stored within the enterprise environments, captured in transactional systems, sourced from IoT devices and sensors, or available through APIs. Built-in data management and transformation means less time is spent trying to find a way to bring data together and more time spent on deploying differentiating apps.  Enterprise-grade security and control simplify compliance with corporate security and data privacy requirements.


A single unified platform for all your analytics initiatives.
Pre-integrated data lake, analytics, visualization, management, and security, for all your data sources and all your use cases, all in one.

Connected Intelligence Platform Features

Data Modeling – Model and activate data using Excel-based template on highly scalable databases or reverse engineer the model from existing database catalogs

Enterprise-grade Hadoop – Ingest, model, store and manage all data for both operational and analytics data needs using Hadoop data stores and PostgreSQL.

Data Pipeline Processing –  A common drag & drop user interface to design both batch, real-time and analytic data pipeline to ingest, curate, model scoring and load data

Dataset & Services – SQL interface to expose the data from both analytics & operational database through REST API and for data export to other enterprise systems.

Data Visualization – Build reports and dashboards using low-code visualization framework or integrate with the existing data visualization tool.

ML-based Insights – Integrated open source data science notebook to train machine learning models. Multiple options to operationalize analytic models such as PMML based ML model, Python based ML, and deep learning, with batch and real-time scoring.

Decision Management – Configure and automate the decision points using in-built business rules and predictive analytic models scoring engine.

Workflow Automation – Schedule data jobs for periodic execution, manage the jobs, and monitor jobs execution.

Project Workspace – Build and manage multiple projects with controlled user access.

Centralized Administration – Web-based console with integrated user role management, Hadoop management, batch job management, and logs and audit management.




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