Our Capabilities

Solving today’s challenges
while preparing for tomorrow’s

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?

Best practices to estimate and articulate business value from D&A initiatives
Pre-built assessment questionnaire & templates to identify value drivers
Business Analysis framework templatized by domain & business functions that help unearth the real problems

Why?

Measure & communicate ROI from D&A initiatives
Help prioritize use cases objectively
Empower stakeholders to take better, informed, & faster investment decisions

Modern Architectures

Modern Architectures

Leverage modern Data Architectures and design paradigms to implement future-ready Data and Analytics platforms that power next-gen business competency

How it helps?

Architectural templates for large transformation & modernization initiatives
Component architecture approach to drive consistency across multiple D&A initiatives within the Enterprise
Facilitate transition from old to new while maintaining interoperability between old and new systems where required

Why?

Reduce time to insights
Ensure consistency in D&A Platforms
Ease of interfacing with external and internal systems

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?

Assessment & roadmap definition leveraging proven frameworks and pre-built reference architectures
Automations such as CTL, RTDS and best practices to implement the platform at speed
Automated migration for a wide variety of data formats & sources

Why?

Delivers an agile, flexible & scalable data platform
Unified & simple platform governance
Cost effective & security compliant
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?

Reusable Logical Data Model (LDM) templates for common domains and functions
LDM for non-functional requirements such as traceability, auditability, security, quality
Performance benchmarks for data access and data ingestion

Why?

Scales with data volume and velocity
Minimizes maintenance efforts with data variety and variability
Optimizes performance for data access and ingestion
Supports data trust – quality, timeliness, traceability, auditability and security

Product Design

Bring stakeholders together to imagine, create, & iterate data products that solve business problems or address specific unmet needs

How it helps?

Design practices for personalized & immersive user experience
Visual and narrative storytelling concepts to accelerate decisions
Human centric approach to uncover actionable insights

Why?

Prepares users to interpret data uniformly, understand insights unambiguously & react faster to evolving market situations
Enables definition of customer journeys that are most conducive to the purpose, thereby maximizing insights adoption

Modern Data Pipelines

Unify & convert data from different sources into usable format in the fastest way possible

How it helps?

Makes data available as events happen (in real-time)
Comprehensive support for common file & databases
Easily extendable
Supports CDC, Query & API-based ingestion approaches

Why?

Rapid on-boarding of new data source
Quick Insights – Maximize returns on your data through automated data pipelines
Enhanced re-usability through established data ingestion patterns
One stop solution for homogenous and heterogenous data ingestion

Business Analytics

Convert data into user-friendly insights to deliver greater value–for customers, employees, partners, or shareholders–with greater efficiency

How it helps?

Repeatable discovery-to-delivery approach
Fully automated suite of tools to enable enterprise-grade apps
Domain, digital and analytics expertise to create products that meet your business objectives

Why?

Intelligent business insights apps in days, not weeks
Responsive, purpose-built solutions that satisfies unmet needs

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?

Framework to manage Opex efficiently for D&A Initiatives
Strike a balance between idle resources and over provisioning
Provide Insights that help alleviate stakeholder fears on unexpected cost overruns
Make faster decisions on retirement of Technical Debt (services that do not matter the most)

Why?

Drives the financial accountability culture by enabling D&A teams to make the right choices considering speed, cost, and quality
Maximizes value from varying cloud spends – It’s not just about saving costs, as these spends can drive significant incremental revenue

Data Migration

Convert and migrate data from legacy databases to cloud-native modern data platforms in an accelerated & efficient manner

How it helps?

Data landscape assessment and roadmap advisory
Multi-year TCO and ROI view to aid your funding decisions
Automated conversion and migration for most of your legacy sources

Why?

Balances Speed with Accuracy
Reduces migration risks
Minimizes cost
Zero business disruption

Analytics Migration

Migrate BI/Analytics platforms quickly and efficiently to modern platforms using our robust methodology, accelerators, and pre-built toolkits

How it helps?

Structured assessments to make right migration choices
Automated tools for migrating most of your assets from source to target
Automated regression tests
User education on new tool capabilities

Why?

Accelerates and de-risks migration programs – Get it right the first time!
Retains benefits from existing apps
Zero business disruption during migration
Happier Users!

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?

Best practice frameworks & methods to validate security at every stage of data handshake
Support for local data regulations such as PCI, HIPAA, GDPR etc.
Supports security in multi cloud/platform scenarios

Why?

Improves trust amongst partners, customers & other stakeholders
Stops any type of misuse of PII Data
Safeguards organizations from regulatory penalties

Augmented Self-Service

Empower users with AI-driven self-service capabilities to derive faster & deeper insights from data

How it helps?

Assess needs, choices and define self-service roadmap
Roll-out self-service tools & capabilities to ensure trusted data delivery
Train your team, establish support and on-going enablement

Why?

Reduces IT dependency – Users can explore, curate & analyse data on their own
Eases consumption & improves user experience

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?

Adopt mining techniques & feature engineering processes that can automatically engineer new features
Leverage repository of diverse algorithms that best fits needs
Build a platform that explains model decisions in human interpretable format
Automate repetitive, tedious and time-consuming tasks across the model lifecycle

Why?

Integrate your existing data science capabilities with new-age capabilities
Free-up data scientists’ time to discover & solve new business problems

Business Automation

Transform your business and customer experience using smarter technologies to drive hyper-productivity, enhance service quality & accelerate digital transformation

How it helps?

Prioritize and streamline workflows through RPA/ automation techniques
Standardize to drive efficiency across multiple business processes
Leverage smarter technologies that are purpose built for automation and can handle scale & variety

Why?

Drives hyper productivity leading to significant cost savings
Enhances agility and flexibility with the automated process always ready to perform a task on-Demand 24 x 7
Improves overall governance with the audit trails driving insights, promoting accountability & demonstrating compliance

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?

Share live data without creating data copies while complying with privacy & cyber standards
Enable data sharing in a hybrid multi-cloud/platform
Automate monitoring & audits

Why?

Accelerates time to value
Enables net new revenue creation through enabling new use cases
Standardizes data sharing & governance practices
Lowers cost of data sharing

DataOps Automation

Continuous improvement to reduce time & effort to convert data into insights in a secure & reliable way

How it helps?

Automated data profiling, quality checks and discoverability
Automated data pipeline development
Framework to authenticate & authorize data access
Support for data-as-a-service

Why?

Reduces Manual QA Efforts
Accelerates Time to Insights
Reduces Data Silos

Data Quality

Guarantee access to trustworthy data for consumption across entire community of users

How it helps?

Automated DQ issue detection from source to insights
Smart data validation rules
Real time alerting and tracking of data quality issues
Pre-built dashboards for DQ visibility and to drive improvement actions

Why?

Improve trust on the data to drive meaningful adoption
Reduce time to conduct diagnostics and root-cause-analysis
Present reliable information for downstream analytical applications

Platform Support

Platform Support

Optimize D&A investments through continuous improvement, automation, and reuse in platform administration and support

How it helps?

Accelerated platform set-up leveraging automations & best practices
Automated release management & repeatable maintenance tasks
Trouble-free upgrades with automated regression testing

Why?

Maximizes value from existing D&A investments
Optimizes TCO while ensuring that D&A platforms are highly available & performant
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?

Reusable configuration templates that leverage auditable, scalable and automated Infrastructure-as-a-code practices
Enables enterprise grade cloud platform, complete with devops, security and performance

Why?

Reduces time to turnaround environments
Enables CI/CD automation with self-service
Reduces mean time to repair and recover

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?

Quantitative and qualitative measurement of user adoption
Identification and resolution of adoption bottlenecks using process alignment, self-help, concierge services & more

Why?

Business alignment & action orientation
Improved data understanding & trust
Ease-of-use – user experience and persona-orientation

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Our Capabilities

Solving today’s challenges while preparing for tomorrow’s

Centers of Excellence

Cloud & Data Engineering

Business Consulting

Analytics & Data Management

Service Management

Foundational Components

Business Value Discovery

How it helps?

Why?

Find out your Top 3 Obstacles to becoming more Data-driven

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InfoCepts

What We Do

Who We Are

Thought Leadership

Solving today’s challenges
while preparing for tomorrow’s

Cloud & Data
Engineering

Business
Consulting

Analytics & Data
Management

Service
Management