Technology Services
Turn the data you already have into decisions you can defend
Most companies aren't short of data. They're short of clean, connected data and the right questions to ask it. We modernise old systems, build the pipelines and dashboards, and help you predict what's coming next.
Tools and platforms
- Power BI
- Tableau
- Apache Spark
- Hadoop
- Python
- Scala
- SQL
- Kafka / streaming
- Snowflake · BigQuery
- ML models
- Engagement model
- Define · Implement · Realise · Grow
- Delivery
- Projects or managed platform
- Starts with
- Proof of concept / value
What's included
Four connected services. Use one, or all of them.
Legacy modernisation
Migrate or re-engineer ageing applications and databases onto modern platforms, carrying the business rules across so nothing is lost. Includes application migration, re-engineering, database migration and prototyping.
Dashboards and reporting
Clear dashboards and reports that give leaders one version of the truth, from sales and pricing to inventory and demand.
Advanced and predictive analytics
Statistical and machine-learning models that forecast demand, flag customers likely to churn, predict equipment failure and find patterns humans miss.
Big-data engineering (DataOps)
Architecture, pipelines, cluster automation and data governance for platforms built on Spark, Hadoop and the cloud.
Platform support
Administration, monitoring, tool configuration and performance tuning for your analytics stack, from assessment through post-launch enhancements.
Advisory and proofs of value
Independent advice on platforms and best practice, and a small proof of concept before you commit to the full build.
Where analytics pays off
Revenue
- Customer lifetime value
- Churn and cancellation risk
- Pricing and discount leakage
- Sales and demand forecasting
Operations
- Predictive maintenance
- Inventory and assortment
- Supply-chain visibility
- Process bottlenecks
Customer
- Single customer view
- Social and sentiment monitoring
- Campaign performance
- Service quality
How it works
Step 1: Define
Agree the business questions, data sources and success measures.
Step 2: Implement
Build pipelines, models and dashboards in short iterations.
Step 3: Realise
Put insights in front of the people who make decisions, with training.
Step 4: Grow
Extend to new use cases and keep the platform healthy.
Why Sarthak
Modernising now almost always costs less than maintaining legacy systems for another five years.
Business first, tools second
We start from the decision you want to improve, then pick the technology.
Engineers and analysts together
Data engineers and analysts on one team, so models actually reach production.
Governed and secure
Access control, lineage and data-security practices built in from the start.
Questions we hear often
Ask us something elseRelated services
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Have a project in mind?
Share where you are and what's stuck. A senior consultant will reply, not a sales script.