Data, AI & Analytics

Business Intelligence, Dashboards & Self-Service Analytics

BI platform implementation (Power BI, Tableau, Looker), executive dashboards, self-service analytics, semantic layer design, and embedded analytics — turning your data into decisions.

Why This Matters

The BI Challenges That Block Data-Driven Culture

Most organisations have a BI tool. Far fewer have a BI culture — where leaders trust the data and use it to make decisions. These are the barriers we remove.

Multiple Conflicting Data Sources

Finance reports one revenue number, sales reports another. No single source of truth means every meeting starts with a debate about whose numbers are right.

Every Report Goes Through the Data Team

Business users can't answer their own questions. Every ad-hoc query creates a ticket, a wait, and a bottleneck — slowing decisions across the business.

Dashboards Nobody Uses

Dashboards built for analysts, not decision-makers. Dense tables, no context, no narrative — leaders go back to Excel because the dashboard doesn't answer their actual question.

Untrusted Data, Untrusted Decisions

Inconsistent metric definitions, no governance, and no data lineage mean users can't trust the numbers — so they don't act on them.

Embedded Analytics Blocking Product Roadmap

Product teams want to add reporting features to the SaaS platform but building custom charts takes sprints. Embedded BI is the unlock they need.

BI Tool ROI Hard to Justify

Power BI or Tableau licences sit underused because deployment, governance, and adoption were never done properly. The tool is blamed when the problem is implementation.

Our Approach

Semantic Layer First. Adoption as the Success Metric.

We build BI solutions around a governed semantic layer — one place where revenue, churn, CAC, and every other critical metric is defined in code and tested. This eliminates the metric disagreements that destroy trust in BI tools, and it means every new dashboard automatically uses the same definitions.

Adoption is our north star metric. We measure dashboard usage, interview non-users to understand friction, and iterate until BI is woven into how teams make decisions — not just something the data team presents at the monthly review.

60%
Fewer data team support tickets after self-service rollout
Faster board reporting cycle vs manual Excel process
18%
SaaS churn reduction with embedded analytics
1
Single version of truth — governed metric catalogue
What's Included

Business Intelligence Capabilities

From BI platform implementation to embedded analytics and self-service governance — we build BI solutions that people actually use.

BI Platform Implementation

Power BI, Tableau, Looker, and Metabase deployments — semantic layer design, data model optimisation, workspace governance, row-level security, and performance tuning for large datasets.

Executive Dashboards & Reporting

KPI dashboards, financial reporting, operational metrics, and board-level scorecards — designed for decision-makers with clear narrative, drill-through capability, and mobile responsiveness.

Self-Service Analytics

Semantic layers, certified datasets, and governed data catalogue access that let business users explore data independently — reducing data team queue depth by 60%+.

Embedded Analytics

Embed interactive charts, dashboards, and data exploration into your SaaS product or internal application — white-labelled BI as a product feature with tenant-level row security.

Semantic Layer & Metrics Catalogue

dbt Metrics, LookML, or Power BI calculation groups — one definition of revenue, churn, and CAC across every dashboard, so metric disagreements become a thing of the past.

BI Governance & Adoption

Workspace governance, certified content programmes, usage analytics, and end-user training — the difference between a BI tool that's used and one that collects dust.

How We Deliver

From Business Questions to Live Dashboards

A structured delivery process that starts with business decisions, not data schemas — so every dashboard answers a real question.

01

Analytics Discovery

Map business questions, KPIs, and decision workflows. Identify which metrics matter most and which data sources they come from.

02

Data Model Design

Design the semantic layer — dimensional models, metric definitions, and calculated fields that serve both executive dashboards and ad-hoc exploration.

03

Platform Setup

Deploy and configure the BI platform — workspace structure, data connections, row-level security, scheduled refreshes, and governance policies.

04

Dashboard Build

Build priority dashboards — executive scorecards first, then operational and departmental views. Design for mobile and for non-technical audiences.

05

Self-Service Enablement

Publish certified datasets, write documentation, and run user training workshops. Establish the data request triage process for ongoing governance.

06

Adoption & Iteration

Monitor usage analytics, identify low-adoption areas, iterate on design, and expand coverage to additional departments and use cases.

Technology

BI Technology Stack

We're certified across the major BI platforms and semantic layer tools — recommending what fits your team, not what we're incentivised to sell.

BI Platforms

Power BITableauLookerMetabaseApache Superset

Semantic Layer

dbt MetricsLookMLPower BI Calculation GroupsCube.dev

Embedded Analytics

Looker EmbeddedPower BI EmbeddedSuperset EmbeddedMetabase Embedding

Data Warehouses

SnowflakeBigQueryRedshiftDatabricks SQL

Governance

Microsoft PurviewCollibraAtlandbt Docs

Monitoring

Tableau Server Admin ViewsPower BI Activity LogLooker System Activity
Use Cases

BI Across Industries & Geographies

Enterprise BI, SaaS embedded analytics, healthcare operations, and financial reporting — deployed across India, UAE, USA, Europe, and Australia.

Financial Services

Group Financial Reporting Platform

Unified Power BI workspace consolidating 12 subsidiaries across UAE, India, and Europe — automated monthly board pack replacing 3-day Excel process. Finance team self-serves 80% of requests.

Retail / D2C

E-Commerce Performance Suite

Real-time Looker dashboards on Snowflake — revenue, AOV, conversion funnel, and cohort analysis. CMO gets a 9am daily briefing without involving the data team.

SaaS / Product

SaaS Embedded Analytics

Multi-tenant Metabase embedding in a B2B SaaS platform — per-customer usage dashboards as a product differentiator. Reduced churn by 18% among accounts with embedded analytics enabled.

Healthcare

Hospital Operations Dashboard

Power BI dashboards across 6 hospital sites — bed occupancy, theatre utilisation, patient wait times, and staffing ratios. Clinical managers self-serve operational decisions daily.

Business Impact

What High-Adoption BI Delivers

60%
Fewer data team support tickets
after self-service analytics rollout
Faster board reporting cycle
automated vs manual Excel consolidation
18%
SaaS churn reduction
for customers using embedded analytics
1
Single version of the truth
metric governance across all dashboards
Why Kansoft

Why Analytics Leaders Choose Kansoft for BI

BI Platform Specialists

Certified across Power BI, Tableau, and Looker — we've implemented enterprise BI for Fortune 500 subsidiaries, mid-market SaaS companies, and regulated healthcare providers.

Adoption-First Design

We design dashboards for decision-makers, not data analysts. Usage analytics and adoption tracking are standard on every deployment — we measure whether people use what we build.

Multi-Region Delivery

Teams across India, UAE, USA, Europe, and Australia — with regional BI expertise for UAE VAT reporting, GDPR data residency, and US GAAP financial dashboards.

Governance Built In

Row-level security, certified content, lineage tracking, and usage monitoring from the start — not retrofitted after audit finds uncontrolled data access.

Semantic Layer Expertise

We build the metrics catalogue and semantic layer that makes self-service reliable — consistent definitions that eliminate the 'whose numbers are right?' debate permanently.

FAQ

Common Questions About Business Intelligence

Which BI tool do you recommend — Power BI, Tableau, or Looker?
It depends on your ecosystem, team skill set, and use case. Power BI is the strongest choice if you're already in the Microsoft stack. Tableau excels for visual analytics and large enterprise deployments. Looker is the best fit for code-first data teams and embedded analytics. We'll recommend based on your context, not our commercial preference.
How do you ensure dashboards are actually used after launch?
We build adoption into the project — user research before design, stakeholder reviews during build, and training workshops at launch. Post-launch, we monitor usage analytics and iterate on low-adoption dashboards. We've found that governance (certified datasets, clear ownership) and training matter more than dashboard design for long-term adoption.
What is a semantic layer and why does it matter?
A semantic layer defines business metrics (revenue, churn, CAC) once, in code, so that every dashboard uses the same calculation. Without it, different analysts build the same metric differently — and you end up with five revenue numbers in five dashboards. dbt Metrics, LookML, and Power BI calculation groups are the main implementations.
Can you work with our existing Power BI / Tableau environment?
Yes. We frequently inherit existing BI environments and improve them — restructuring workspace governance, rewriting slow queries, implementing row-level security that was missing, and adding certified dataset programmes. We work with what you have.
How long does a BI implementation take?
A core BI platform with 3–5 priority dashboards and self-service setup takes 6–10 weeks. Enterprise-wide deployment with multiple departments and embedded analytics takes 3–6 months. We phase delivery so you have working dashboards in weeks, not months.
Do you build embedded analytics for SaaS products?
Yes — embedded analytics is one of our specialisations. We've embedded Power BI, Looker, and Metabase into SaaS products with multi-tenant row-level security, white-labelling, and performance optimisation for concurrent user loads.
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