Data Analytics & BI

One agreed definition for every metric, and dashboards built on those definitions that people actually check every morning.

Data Analytics & BI

One agreed definition for every metric, and dashboards built on those definitions that people actually check every morning.

Metrics & Semantic Layer

When two dashboards show two different delinquency rates, people stop trusting both. We define each metric once, in code, and every report reads from that definition.

Built with:

dbt models or Databricks metric views
Power BI semantic models
Documented definitions that business owners have signed off on

sql

1-- One definition of delinquency, used by every dashboard
2CREATE VIEW gold.delinquency_rate AS
3SELECT
4  report_month,
5  count_if(days_past_due >= 30) / count(*) AS dq30_rate,
6  count_if(days_past_due >= 60) / count(*) AS dq60_rate
7FROM silver.loan_performance
8GROUP BY report_month;

Dashboards

We design each dashboard around a decision: who looks at it, how often, and what they do next.

Tools:

Power BI, Tableau and Looker
Databricks AI/BI dashboards
Row-level security, so each person sees only their own portfolio or region

Natural-Language Analytics

Business users ask questions in plain English and get answers from governed tables, without waiting for an analyst.

How:

Databricks AI/BI Genie spaces or Power BI Copilot
Grounded in the semantic layer, so answers match the dashboards
Curated example questions and instructions so answers stay accurate

Domain Analytics

Analysis is only useful when the analyst understands the business. Our subject-matter experts have worked in the industries we serve.

Areas:

Real estate and rental portfolio performance
Mortgage and RMBS loan-level performance
Risk and fraud analytics
Sports performance analytics

Data Analytics & BI

Metrics & Semantic Layer

Dashboards

Natural-Language Analytics

Domain Analytics

Related capabilities

Data Engineering

Data Science & Machine Learning

Databricks Training