Data Analytics

Sri Lanka Data Analytics Servicesfor Smarter Decisions

Make data-driven decisions with confidence. We build powerful analytics solutions that turn raw data into meaningful insights, dashboards, and predictive models that drive growth.

Who We Serve

Analytics solutions for data-driven organizations

Business Leaders

Executives needing real-time visibility into KPIs and performance metrics for strategic decisions

Data Teams

Analysts requiring self-service BI tools and data infrastructure to answer business questions quickly

Operations Managers

Operational teams tracking performance, identifying bottlenecks, and optimizing processes

Services We Offer

End-to-end data analytics capabilities

Business Intelligence Solutions
Data Warehouse Development
ETL Pipeline Development
Real-Time Analytics
Predictive Analytics
Data Visualization & Dashboards
Big Data Processing
Customer Analytics
Marketing Analytics
Financial Analytics
Data Strategy Consulting
Self-Service BI Implementation

Industries We Serve

Analytics expertise across sectors

Retail & E-commerce

Finance & Banking

Healthcare

Manufacturing

Marketing & Advertising

Logistics & Supply Chain

Our Technology Stack

Modern analytics tools and platforms

BI Tools

Power BI
Tableau
Looker
Metabase
Apache Superset

Data Processing

Apache Spark
Apache Airflow
dbt
Databricks
Snowflake

Databases

PostgreSQL
MySQL
MongoDB
BigQuery
Redshift

Languages & Tools

Python
SQL
R
Jupyter
Pandas

Our Analytics Implementation Process

From data chaos to clear insights

01

Requirements Gathering

Understand business questions, KPIs, data sources, and stakeholder needs through workshops.

02

Data Discovery

Audit existing data sources, assess data quality, identify gaps, and plan data integration strategy.

03

Data Infrastructure

Build data warehouse, establish ETL pipelines, implement data governance, and ensure data quality.

04

Analytics Development

Create dashboards, reports, and analytics models aligned with business objectives.

05

User Training

Train stakeholders on BI tools, self-service analytics, and data-driven decision-making practices.

06

Continuous Improvement

Monitor usage, gather feedback, optimize performance, and expand analytics capabilities.

How We Help

A delivered HR analytics project plus illustrative planning examples

HR Analytics & Reporting

Delivered project · Confidential enterprise client

Challenge

A large organisation relied on spreadsheets for payroll, attendance, and leave data with no unified reporting view.

Solution

Built a React.js employee management system with MySQL, role-based access, and dashboards for HR operations and reporting.

Documented outcomes

Documented: ~90% reduction in manual HR paperwork (project documentation)
Payroll, attendance, leave, and performance modules in one system
Reporting dashboard for HR and management teams

Retail Analytics Platform

Illustrative example · Sample multi-store retail chain

Hypothetical scenario for planning purposes - not a delivered client engagement.

Challenge

Sales and inventory data sit in separate systems, making it hard to spot stockouts or trends across stores.

Solution

Example approach: central data warehouse with ETL pipelines and BI dashboards for sales, inventory, and customer metrics.

Typical deliverables

Unified data model across stores and channels
ETL pipelines with data quality checks
Executive and store-manager dashboards
Self-service reporting for operations teams

Marketing Funnel Analytics

Illustrative example · Sample e-commerce business

Hypothetical scenario for planning purposes - not a delivered client engagement.

Challenge

Marketing spend is hard to tie to conversions because event data is incomplete and siloed.

Solution

Example approach: event tracking plan, customer-360 dataset, and funnel dashboards connected to ad platforms.

Typical deliverables

Event tracking specification and implementation
Funnel and campaign performance dashboards
Attribution model documentation
Monthly reporting templates

Frequently Asked Questions

Everything you need to know about data analytics

What is the difference between Business Intelligence and Data Analytics?

Business Intelligence (BI) focuses on descriptive analytics-what happened in the past through reports and dashboards. Data Analytics includes BI but also encompasses diagnostic analytics (why it happened), predictive analytics (what will happen), and prescriptive analytics (what should we do). BI answers "how many sales last quarter?" while advanced analytics answers "which customers will churn next month and how do we retain them?"

How long does it take to implement a data analytics solution?

Timeline varies by scope. A basic BI dashboard connecting to existing databases takes 3-6 weeks. A comprehensive data warehouse with ETL pipelines and multiple dashboards takes 2-4 months. Enterprise-wide analytics platforms with data governance take 6-12 months. We typically start with high-value use cases to demonstrate ROI quickly, then expand systematically.

What are the costs of data analytics implementation?

Costs depend on complexity and data volume. Basic BI dashboards start from LKR 600,000, data warehouse solutions from LKR 2,000,000, and enterprise analytics platforms from LKR 5,000,000. Ongoing costs include cloud infrastructure (LKR 50,000-300,000/month), BI tool licenses, and maintenance. We optimize costs using open-source tools where appropriate and right-sizing cloud resources.

Can you work with our existing data and systems?

Absolutely. We connect to virtually any data source: SQL databases, cloud data warehouses, Excel files, APIs, SaaS platforms (Salesforce, HubSpot, Shopify), Google Analytics, social media, and more. We handle data quality issues, transform data to useful formats, and combine multiple sources into unified analytics. If you have data, we can make it useful.

Do we need a data warehouse or can we analyze data directly?

It depends on your situation. Direct querying works for simple use cases with one or two data sources. However, data warehouses provide significant benefits: combine multiple sources, historical tracking, better performance, data quality assurance, and enable self-service analytics. For businesses with growth ambitions and multiple data sources, a data warehouse becomes essential within 1-2 years. We help assess the right approach for your stage.

How do you ensure data security and privacy?

Security is paramount in analytics. We implement role-based access controls ensuring users see only authorized data, encrypt data at rest and in transit, maintain audit logs of all access, anonymize PII where required, and ensure compliance with regulations (GDPR, HIPAA). We follow security best practices including least-privilege access, regular security audits, and secure credential management. Your data security is never compromised.

Ready to Unlock Your Data's Potential?

Let's build analytics solutions that drive measurable business outcomes

Free Data Assessment
ROI-Focused Approach
Self-Service BI