Analytics & Reporting
Put trusted data in the hands of the people who decide
A governed, human-centric approach to business intelligence, self-service analytics and reporting, so end users can rely on the numbers they see.
What it is
Analytics and reporting turn a data platform into decisions. We design business intelligence (BI) and dashboards, self-service analytics, operational and regulatory reporting, forecasting and planning, and embedded analytics inside the applications people already use. Underneath sits a semantic layer, sometimes called a metrics layer, where each business measure is defined once and reused everywhere.
The work is as much about adoption as technology. We involve the people who will use the output, build data literacy through training and documentation, and measure whether reports are actually used. Examples from our financial services work include cost and performance analysis, and the same patterns apply in manufacturing, retail and the public sector.
Problems it addresses
- Different reports show different numbers for the same measure, and meetings are spent reconciling them.
- Analysts spend most of their time preparing data in spreadsheets rather than interpreting it.
- Dashboards multiply, few are trusted, and nobody owns retiring them.
- Business users cannot explore data safely without asking a central team.
- Regulatory and management reports are assembled by hand and are difficult to trace to sources.
- Forecasts and plans live in disconnected files that are updated on different cycles.
What we deliver
- A semantic layer with certified metric definitions, hierarchies and business glossary terms.
- Executive and operational dashboards designed with the people who use them.
- Self-service datasets and a governed workspace, with role-based and row-level access.
- Operational and regulatory reporting pipelines with lineage, reconciliation and approvals.
- Forecasting and planning models, with assumptions visible and reviewable.
- Embedded analytics for customer, partner or staff-facing applications.
- Natural-language query over governed metrics, with evaluation of answers before wider rollout.
- Training, data literacy materials and usage monitoring to support adoption.
Our method
How we work
We follow our four-step method, and each step ends with a review where you can pause, adjust or stop. See the full method.
Discovery & Strategy
We interview users, review existing reports and agree the decisions that analytics should support and the metrics behind them.
Pilot & Validation
One domain is delivered end to end, from curated data to certified metrics and a dashboard, and tested with real users.
Build & Scale
Further reports, self-service workspaces and embedded views are added, using shared definitions, testing and access controls.
Optimize & Evolve
We track usage, data quality and report performance, retire unused content and extend the metrics layer.
Technologies
Technologies we commonly work with
These are examples of tools we commonly work with. We choose based on your platform, users and existing licenses, and we avoid adding a tool when one you own will do.
Analytics and BI
Dashboards, self-service analytics and a shared semantic layer so teams use the same definitions.
- Power BIMicrosoft's BI and dashboarding platform with semantic models.
- TableauVisual analytics and dashboards for exploration and reporting.
- LookerGoverned BI built on a modeled semantic layer.
- Amazon QuickSightServerless BI and embedded analytics on AWS.
- Apache SupersetOpen source data exploration and dashboards.
- CubeHeadless semantic layer that serves consistent metrics to any tool.
Data platforms
Warehouses, lakes and lakehouses where governed data is stored, modeled and shared.
- DatabricksLakehouse platform for data engineering, SQL analytics and machine learning.
- SnowflakeCloud data platform for warehousing, sharing and analytics.
- Microsoft FabricUnified analytics platform with OneLake, pipelines and Power BI.
- Google BigQueryServerless data warehouse with built-in machine learning.
- Amazon RedshiftCloud data warehouse in the AWS ecosystem.
- Azure Synapse AnalyticsAnalytics service combining warehousing and big data on Azure.
- Delta LakeOpen table format that adds reliability to data lake storage.
- Apache IcebergOpen table format for large analytic tables across engines.
Governance and security
Catalogs, lineage, access control and key management that make data and AI auditable.
- Microsoft PurviewData catalog, classification and governance across Microsoft estates.
- Unity CatalogUnified governance for data and AI assets on Databricks.
- CollibraData governance and catalog platform for policies and stewardship.
- AWS Lake FormationFine-grained access control for data lakes on AWS.
- Google DataplexData management and governance across Google Cloud data.
- Azure Key VaultManaged storage for secrets, keys and certificates on Azure.
- AWS KMSManaged encryption keys for services and applications on AWS.
- Microsoft Entra IDIdentity and access management for people and workloads.
- OpenLineageOpen standard for collecting data lineage across tools.
- Great ExpectationsOpen source framework for data quality checks.
These tools are examples of what we commonly work with, listed as text only. We are vendor-neutral and recommend what fits your estate. Product names belong to their owners, and their appearance here does not imply a partnership, endorsement or certification.
Governance and compliance
Reports often carry sensitive and regulated information, so access and evidence matter. We apply role-based and row-level security, mask personal information where it is not needed, and keep lineage from each figure back to its source so that reviewers can follow it. Where reports feed regulatory filings, we help document controls, approvals and reconciliations, with expectations from supervisors such as Office of the Superintendent of Financial Institutions (OSFI) and Canadian Investment Regulatory Organization (CIRO) in Canada, the Securities and Exchange Commission (SEC) and Financial Industry Regulatory Authority (FINRA) in the United States, and the Financial Conduct Authority (FCA) and EU authorities treated as context. Public bodies and health organizations have their own disclosure and privacy rules, including Personal Information Protection and Electronic Documents Act (PIPEDA), General Data Protection Regulation (GDPR) and health privacy laws. Your finance, compliance and legal teams determine what applies.
Ways to start
Engagement options
Most clients begin with an assessment or a pilot. Scope, owners and success measures are agreed in writing for each option, and the options can be combined.
Assessment
A review of current reports, metrics and tools, with a plan for a semantic layer and a prioritized reporting backlog.
Pilot
One decision area delivered end to end, with certified metrics, a dashboard and feedback from real users.
Build
Delivery of the semantic layer, reporting estate, self-service environment and training, working with your analysts.
Advisory retainer
Ongoing review of metric definitions, new reports and adoption while your team owns the estate.
This page is general information about ARCHR services. It is not legal, financial or investment advice, and it does not assure compliance with any regulation.
FAQ
Frequently asked questions
Which BI tools do you work with?
We work with the tools that fit your platform and skills, on AWS, Microsoft Azure or Google Cloud. We recommend a tool only after understanding your users and the licenses you already hold.
What is a governed semantic layer?
It is a single, documented definition of business metrics and relationships that all reports draw from, so that the same question gives the same answer wherever it is asked.
Can business users build their own reports?
Yes. Self-service is designed in with curated datasets, certified metrics and role-based access, so users can explore safely without bypassing governance.
Can you support regulatory reporting?
We can help structure the data, lineage and controls behind regulatory and management reports so figures trace to their sources. What you file and how remains the decision of your finance and compliance teams.
Let's talk about your data and AI priorities
Tell us what you are trying to solve. We aim to reply within one business day.