Solving today’s challenges
The backbone of Infocepts success rests with its globally recognized, innovative support model, which is concentrated on aggressively building depth & breadth of expertise within the key components of Data & AI success, which we refer to as ‘Foundational Components’.
Infocepts Foundational Components are supported by 4 world class Centers of excellence, whose sole focus is to serve as a ‘lighthouse’, guiding both our Clients & our Foundational Components teams. This unique system of balance ensures that – at all times – our clients & our associates have available to them, the most well-versed understanding of today, while also being able to ‘see into the future’ and plan for what’s coming tomorrow.
Centers of Excellence
Cloud & Data
Engineering
Create large scale data platforms and applications using modern cloud-native tools combined with engineering skills
Business
Consulting
Connect your transformative goals using consultative, domain, digital, data science & advisory capabilities
Analytics & Data
Management
End-to-end expertise to build next-gen data & analytics solutions using proven best of breed platforms
Service
Management
Transform large scale D&A initiatives using strong program governance practices & agile-at-scale principles
Foundational Components

Business Value Discovery
Measure the business value realised from your data & analytics programs
How it helps?
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Best practices to estimate and articulate business value from D&A initiatives
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Pre-built assessment questionnaire & templates to identify value drivers
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Business Analysis framework templatized by domain & business functions that help unearth the real problems
Why?
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Measure & communicate ROI from D&A initiatives
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Help prioritize use cases objectively
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Empower stakeholders to take better, informed, & faster investment decisions

Master Data Management
Build single version of truth for critical data domains like customer, product, partner from multiple data sources using modern AI powered MDM platforms.
How it helps?
- Build an effective business case for MDM
- Evaluate fit-for-purpose platforms choices
- Accelerate and de-risk enterprise implementations with reusable components
Why?
- Standardisation of data across processes, applications, and systems
- Simplified data architecture and navigation for easy data accessibility
- Efficient collaboration and data sharing between teams
- Improve trust on the critical data domains

Modern Data Platforms
Next-gen data platforms that go beyond the incremental improvements to eliminate all-too-common silos in data, applications, and teams—and facilitate organizational change
How it helps?
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Assessment & roadmap definition leveraging proven frameworks and pre-built reference architectures
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Automations such as CTL, RTDS and best practices to implement the platform at speed
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Automated migration for a wide variety of data formats & sources
Why?
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Delivers an agile, flexible & scalable data platform
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Unified & simple platform governance
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Cost effective & security compliant
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Reduced management overhead & increased productivity of D&A teams

Data Modeling
Combine knowledge of business context, data characteristics & modern design paradigms to create scalable data models that optimizes performance & minimizes maintenance efforts
How it helps?
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Reusable Logical Data Model (LDM) templates for common domains and functions
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LDM for non-functional requirements such as traceability, auditability, security, quality
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Performance benchmarks for data access and data ingestion
Why?
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Scales with data volume and velocity
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Minimizes maintenance efforts with data variety and variability
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Optimizes performance for data access and ingestion
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Supports data trust – quality, timeliness, traceability, auditability and security
Data Pipelines
Unify & convert data from different sources into usable format in the fastest way possible
How it helps?
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Makes data available as events happen (in real-time)
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Comprehensive support for common file & databases
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Easily extendable
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Supports CDC, Query & API-based ingestion approaches
Why?
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Rapid on-boarding of new data source
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Quick Insights – Maximize returns on your data through automated data pipelines
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Enhanced re-usability through established data ingestion patterns
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One stop solution for homogenous and heterogenous data ingestion

Augmented Self-Service
Empower users with AI-driven self-service capabilities to derive faster & deeper insights from data
How it helps?
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Assess needs, choices and define self-service roadmap
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Roll-out self-service tools & capabilities to ensure trusted data delivery
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Train your team, establish support and on-going enablement
Why?
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Reduces IT dependency – Users can explore, curate & analyse data on their own
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Eases consumption & improves user experience
Data FinOps
Maximize Biz value by enabling cross-functional teams in making data-driven spending decisions while evolving financial management discipline and cultural practices
How it helps?
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Framework to manage Opex efficiently for D&A Initiatives
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Strike a balance between idle resources and over provisioning
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Provide Insights that help alleviate stakeholder fears on unexpected cost overruns
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Make faster decisions on retirement of Technical Debt (services that do not matter the most)
Why?
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Drives the financial accountability culture by enabling D&A teams to make the right choices considering speed, cost, and quality
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Maximizes value from varying cloud spends – It’s not just about saving costs, as these spends can drive significant incremental revenue

Generative AI
Empower businesses with the strategic use of generative AI and LLMs. We support embedded AI models, chatbot applications, and fine-tuned LLMs to accelerate business value and growth.
How it helps?
- Support Generative AI strategy, roadmap, design, build, operationalize and run
- Advise on responsible uses of the tech and provide latest POVs
- Provide architectural perspectives & best practices
Why?
- Improve the end user experience or help businesses achieve more with less
- Realize 20% (or more) productivity improvement using AI-assisted analysis & development tools
- Operate effectively, efficiently, and in response to business needs

Data Security & Privacy
Deliver trusted customer experience with a holistic and adaptive approach to data security and privacy based on zero trust principles of data protection
How it helps?
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Best practice frameworks & methods to validate security at every stage of data handshake
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Support for local data regulations such as PCI, HIPAA, GDPR etc.
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Supports security in multi cloud/platform scenarios
Why?
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Improves trust amongst partners, customers & other stakeholders
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Stops any type of misuse of PII Data
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Safeguards organizations from regulatory penalties

Augmented Business Analytics
Convert data into user-friendly insights to deliver greater value–for customers, employees, partners, or shareholders–with greater efficiency
How it helps?
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Repeatable discovery-to-delivery approach
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Fully automated suite of tools to enable enterprise-grade apps
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Domain, digital and analytics expertise to create products that meet your business objectives
Why?
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Intelligent business insights apps in days, not weeks
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Responsive, purpose-built solutions that satisfies unmet needs

Machine Learning
Seamless automation across the life cycle of a Data Science program – from advisory, to model development and deployment across platforms
How it helps?
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Adopt mining techniques & feature engineering processes that can automatically engineer new features
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Leverage repository of diverse algorithms that best fits needs
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Build a platform that explains model decisions in human interpretable format
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Automate repetitive, tedious and time-consuming tasks across the model lifecycle
Why?
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Integrate your existing data science capabilities with new-age capabilities
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Free-up data scientists’ time to discover & solve new business problems

Intelligent Automation
Transform your business and customer experience using smarter technologies to drive hyper-productivity, enhance service quality & accelerate digital transformation
How it helps?
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Prioritize and streamline workflows through RPA/ automation techniques
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Standardize to drive efficiency across multiple business processes
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Leverage smarter technologies that are purpose built for automation and can handle scale & variety
Why?
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Drives hyper productivity leading to significant cost savings
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Enhances agility and flexibility with the automated process always ready to perform a task on-Demand 24 x 7
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Improves overall governance with the audit trails driving insights, promoting accountability & demonstrating compliance

DataOps Automation
Continuous improvement to reduce time & effort to convert data into insights in a secure & reliable way
How it helps?
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Automated data profiling, quality checks and discoverability
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Automated data pipeline development
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Framework to authenticate & authorize data access
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Support for data-as-a-service
Why?
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Reduces Manual QA Efforts
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Accelerates Time to Insights
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Reduces Data Silos
Data Quality
Guarantee access to trustworthy data for consumption across entire community of users
How it helps?
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Automated DQ issue detection from source to insights
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Smart data validation rules
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Real time alerting and tracking of data quality issues
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Pre-built dashboards for DQ visibility and to drive improvement actions
Why?
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Improve trust on the data to drive meaningful adoption
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Reduce time to conduct diagnostics and root-cause-analysis
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Present reliable information for downstream analytical applications

Platform Support
Optimize D&A investments through continuous improvement, automation, and reuse in platform administration and support
How it helps?
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Accelerated platform set-up leveraging automations & best practices
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Automated release management & repeatable maintenance tasks
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Trouble-free upgrades with automated regression testing
Why?
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Maximizes value from existing D&A investments
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Optimizes TCO while ensuring that D&A platforms are highly available & performant
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Creates savings from ‘run’ operations to fund modernization initiatives
Cloud Infrastructure Automation
Use code to automate provision, comply, & manage cloud infrastructure to reduce effort, improve security, control spend, & enable innovation
How it helps?
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Reusable configuration templates that leverage auditable, scalable and automated Infrastructure-as-a-code practices
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Enables enterprise grade cloud platform, complete with devops, security and performance
Why?
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Reduces time to turnaround environments
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Enables CI/CD automation with self-service
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Reduces mean time to repair and recover

Product Design
Bring stakeholders together to imagine, create, & iterate data products that solve business problems or address specific unmet needs
How it helps?
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Design practices for personalized & immersive user experience
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Visual and narrative storytelling concepts to accelerate decisions
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Human centric approach to uncover actionable insights
Why?
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Prepares users to interpret data uniformly, understand insights unambiguously & react faster to evolving market situations
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Enables definition of customer journeys that are most conducive to the purpose, thereby maximizing insights adoption
D&A Migration
Migrate Data & Analytics platforms quickly and efficiently to modern platforms using our robust methodology, accelerators, and pre-built toolkits.
How it helps?
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Structured assessments to make right migration choices
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Automated tools for migrating most of your assets from source to target
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Automated regression tests
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User education on new tool capabilities
Why?
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Accelerates and de-risks migration programs – Get it right the first time!
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Retains benefits from existing apps
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Zero business disruption during migration
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Happier Users!

Data Sharing
Realize better value of data, create new or better products, through secure sharing of data (both internally and externally) without replicating data assets
How it helps?
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Share live data without creating data copies while complying with privacy & cyber standards
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Enable data sharing in a hybrid multi-cloud/platform
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Automate monitoring & audits
Why?
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Accelerates time to value
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Enables net new revenue creation through enabling new use cases
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Standardizes data sharing & governance practices
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Lowers cost of data sharing

D&A Adoption
Measure, sustain & improve qualitative and quantitative adoption of data and analytics assets of the enterprise to maximize business value from D&A investments
How it helps?
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Quantitative and qualitative measurement of user adoption
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Identification and resolution of adoption bottlenecks using process alignment, self-help, concierge services & more
Why?
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Business alignment & action orientation
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Improved data understanding & trust
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Ease-of-use – user experience and persona-orientation