Services

Data Strategy

In a data-driven world, leveraging your data is key to staying competitive. Our Data Strategy Engagement helps you overcome fragmented systems and outdated practices by developing a tailored roadmap that aligns your data capabilities with business goals. We assess your current infrastructure, design scalable architecture, and implement governance frameworks to unlock the full potential of your data for smarter decision-making and growth.

Discovery Phase

  • Stakeholder Interviews
  • Assess Current Data Landscape
  • Evaluate Data Governance & Quality
  • Data Maturity Assessment

Strategy Formulation

  • Develop a Vision & Roadmap
  • Data Architecture Blueprint
  • Data Governance Framework
  • Technology Stack Evaluation
  • Data Enablement & Literacy

Implementation Roadmap

  • Prioritize Initiatives
  • Data Governance Execution
  • Project Plans & Milestones

Data Analytics Modernization

We partner with firms in multiple industries and sizes to build their data analytics platform taking advantage of the flexibility offered by the cloud paradigm. In these efforts, we typically cover:

Cloud Environment

Configure the cloud environment and deploy necessary services

Data Zones

Establish data landing zones and refinement areas

Data Model

Create a performant and expandable Data Model

Data Pipelines

Develop the required Data Pipelines

Machine Learning

Identify and train machine learning models

Data Visualization

Build the necessary Data Visualizations

Data Integration & Visualization

Our Data Integration and Visualization offering streamlines data from multiple sources, ensuring clean and consistent datasets through tailored pipelines. We work closely with stakeholders to define key metrics, then design interactive dashboards that present actionable insights. By empowering users with self-service tools, we enable them to explore and visualize data independently, driving better decision-making across the organization.

Requirements Gathering

Collaborate with business users to understand their reporting needs and key performance indicators (KPIs). Gather requirements to ensure that the visualizations deliver insights aligned with their goals.


Data Source Identification

Work with the client to identify key data sources across the organization. Assess their quality, availability, and relevance to business objectives. This ensures the integration covers all essential data inputs.


Data Ingestion and Integration

Design and implement data pipelines to ingest data from disparate sources (e.g., databases, APIs, external services). Transform and consolidate this data into a centralized system (e.g., data warehouse or lake) for unified access.

Data Transformation

Apply business rules to transform raw data into usable formats. Cleanse the data to ensure accuracy, consistency, and readiness for analysis, removing duplicates, fixing errors, and aligning formats across sources.

Dashboard and Report Design

Design intuitive, interactive dashboards and reports using modern visualization tools (e.g., Power BI, Tableau). Ensure the visualizations present clear insights that enable decision-making, combining visual appeal with functional relevance.

Self-service Enablement

Implement self-service analytics platforms that allow business users to explore data, create custom reports, and visualize insights without needing technical expertise. This enhances data accessibility across the organization.

Advanced Analytics & AI

Unlock the potential of your data with our Advanced Analytics and AI approach. By starting with a readiness assessment, we ensure your infrastructure and team are prepared to adopt AI-driven solutions. We then identify key business use cases, develop tailored models, and run pilot programs to validate results. Once proven, these solutions are deployed and integrated seamlessly into your operations, with ongoing optimization and training to empower your team for continued success in advanced analytics and AI.

Readiness Assessment

Evaluate the organization’s current data infrastructure, governance, and analytics capabilities. Assess data quality, technology stack, and team skillsets to determine readiness for advanced analytics and AI implementation.

Use Case Discovery

Collaborate with business stakeholders to identify and prioritize high-impact use cases for advanced analytics and AI. Focus on areas where data-driven insights can provide significant business value and competitive advantage.

Data Preparation

Gather and prepare data from relevant sources, ensuring it meets quality standards. This step includes cleaning, transforming, and enriching data to make it suitable for AI and machine learning models.

Model Development

Develop and train machine learning or AI models based on identified use cases. Experiment with various algorithms, optimize performance, and validate results to ensure models deliver meaningful insights.

Pilot Implementation

Run a pilot project to validate the chosen use cases and model efficacy. Test the solution in a controlled environment, monitor outcomes, and measure the impact to ensure scalability and practical benefits.

Deployment and Integration

Once the pilot is successful, scale the solution across the organization. Integrate the models into existing systems, automate processes, and ensure alignment with business workflows.

Data Governance

Strong data governance ensures data accuracy, security, and compliance. We assess current practices, align stakeholders, and implement a governance framework with clear policies and roles. Using the right tools and training, we establish a sustainable governance culture, enabling trust in your data while ensuring ongoing compliance and security.

01

Current State Assessment

Review existing governance practices, identifying gaps in data quality, security, and compliance

02

Stakeholder Alignment

Align business and IT stakeholders on data governance goals, roles, and responsibilities

03

Policy & Framework Development

Create a governance framework with policies for data access, usage, quality, and security

04

Metadata Management

Implement a data catalog to centralize metadata and ensure data consistency and compliance

05

Data Quality Management

Establish processes to monitor and improve data quality, ensuring accuracy and reliability

06

Governance Technology Enablement

Deploy governance tools for enforcing policies, managing lineage, and automating compliance

07

Training and Adoption

Train stakeholders on governance roles and promote adherence to governance policies

08

Monitoring and Continuous Improvement

Continuously monitor governance policies and data quality, refining as needed

Managed Services

Maximize your system's efficiency and reliability with expert-managed services that ensure seamless operation and continuous improvement.

Supporting Your Data Journey, Every Step of the Way

With decades of expertise, our managed services ensure your data systems run smoothly and efficiently. From proactive performance monitoring to hands-on support, we help businesses stay agile and scalable across industries like finance, healthcare, and technology. Our dedicated team provides tailored solutions that keep your operations running at peak performance.

What We Deliver:

Performance diagnostics and fine-tuning

Continuous monitoring and fine-tuning to keep your data systems optimized.

End-user support

Fast, expert assistance to resolve any challenges that arise.

Ad-hoc advisory

On-demand consultancy to guide critical decisions and ensure your data strategy stays on course.

Platform upgrades

Regular updates and enhancements to keep your systems current and aligned with business goals.