Business intelligence services from senior BI and analytics teams

Ryz business intelligence services give you senior BI developers and analytics engineers who build the semantic models, metrics and dashboards your teams run the business on, in Power BI, Tableau, Looker or the tool you already own. They come from the top 1% of the people we interview, work on US business hours, and sit with the finance, sales and operations people who use the reports. The aim is fewer, trusted dashboards with one definition of each metric, not another folder of reports nobody opens.

What we build

• Semantic models: Power BI datasets with star schemas, LookML models or Tableau published data sources, where measures such as revenue, churn and margin are defined once and reused everywhere.
• Executive and operational dashboards: KPI views for leadership and detailed operational reports for teams, designed around the decisions each audience makes.
• Analytics-ready data marts: dbt models in Snowflake, BigQuery, Databricks, Redshift or Fabric that shape raw data into tables BI tools can query fast. For deeper pipeline work, see our data engineering services.
• Self-service analytics: curated datasets, documentation and training so analysts and business users can answer their own questions without breaking the model.
• Embedded analytics: dashboards inside your own application with Power BI Embedded, Looker embedding or Tableau Embedded Analytics, with row-level security per customer.
• Report migrations: moving from Excel workbooks, SSRS, Qlik or Crystal Reports to a modern BI tool, with old and new numbers reconciled report by report.
• Financial and operational reporting: P&L views, cohort and retention analysis, pipeline and forecast reporting, inventory and supply metrics.
• Alerts and scheduled delivery: data-driven alerts, subscriptions and exports, so the people who need a number get it without logging in.

How an engagement works

Talk. We start with the decisions: who looks at which numbers, how often, and which ones they argue about. Then we review your sources, warehouse, BI tool and licenses.

Match. We propose BI developers who know your tool in depth (DAX and Power Query, LookML, or Tableau calculations and extracts) and analytics engineers who know your warehouse.

Join. The team works in your BI workspace, warehouse and repos, joins standups and reviews dashboards with business owners every week.

Grow. Add data engineers when sources multiply, or train your analysts and hand over a documented model.

In week 1, the team typically inventories existing reports and metrics, finds where numbers conflict, and agrees on the first business area to fix. By month 1, a governed semantic model for that area is live with a first set of dashboards reviewed by its users. By month 3, the usual picture is several domains modeled, a metric glossary, usage tracking and unused reports retired.

The stack our teams work in

How we keep the numbers right

BI projects fail when two dashboards show different revenue, when reports take a minute to load, when business logic is buried in hundreds of report-level calculations, or when nobody uses what was built. A senior BI team works against each of these:

• Metric definitions agreed in writing. Each core metric has an owner, a plain-language definition, filters and edge cases (refunds, test accounts, currency) agreed before it is built.
• Logic in the model, not the visual. Calculations live in the semantic model or dbt, so every report uses the same measure and a change happens in one place.
• Reconciliation against the source of record. New numbers are checked against the general ledger, CRM or billing system, and differences are explained before anyone relies on the dashboard.
• Star schemas and performance. Fact and dimension tables, aggregations, incremental refresh and query folding in Power BI, or extracts and persistent derived tables in Tableau and Looker, so dashboards load in seconds.
• Row-level security tested. Security roles are tested with real user accounts, because a sales rep seeing the wrong region is both a privacy and a trust problem.
• Change control. Models in Git, development and test workspaces, and deployment pipelines, so a dashboard edit does not break production at month-end close.
• Design for decisions. Each dashboard answers a defined question for a defined audience, with context such as targets and prior periods. Usage metrics show what is used, and the rest is retired.
• Data freshness shown. Every report shows when its data was last refreshed, so users never act on stale numbers without knowing it.

Team shapes and cost

Typical Ryz cost is $7,000 to $15,000 per person per month. Mid-level is $7,000 to $10,000, senior is $10,000 to $15,000, and leads are $15,000 or more, quoted per team.

• One senior BI developer: 1 × $10,000 to $15,000 = $10,000 to $15,000 per month. Fits one business area or a tool migration with a clear scope.
• BI pair: a senior BI developer plus a senior analytics engineer: 2 × $10,000 to $15,000 = $20,000 to $30,000 per month. Fits building the model and the dashboards together.
• Analytics team: a lead ($15,000+) plus a senior data engineer, a senior analytics engineer and a mid-level BI developer ($27,000 to $40,000) = from $42,000 per month. Fits a company-wide BI rebuild.

Every quote is scoped per team. You get a plan, a price and the names of the people before you start.

Dedicated team or staff augmentation?

Staff augmentation fits when you have a data or analytics lead and need senior BI capacity: developers join your sprints and report to your leads. See our hire Power BI developers and hire data analysts pages for profiles.

A dedicated development team fits a defined outcome, such as replacing spreadsheet reporting, migrating BI tools, or building embedded analytics into your product, owned from requirements to rollout and training.

When Ryz isn't the right fit

If you only need a single dashboard built over a few days, a freelance marketplace is quicker. If you want a strategy firm to define your data operating model without a build, a management consultancy fits better. If your business users are on European or Asian hours, a global network will give you better overlap.

Related

• Software development services
• Data engineering services
• Hire SQL developers
• Engineering teams for retail and e-commerce

FAQ

Power BI, Tableau or Looker?

Power BI fits Microsoft-centric companies and offers strong value per user. Tableau is strong for visual exploration. Looker fits teams that want a code-based semantic layer in Git, especially on BigQuery. If you already have licenses, we usually build in that tool.

How much do business intelligence services cost?

Typical cost is $7,000 to $15,000 per person per month. One senior BI developer is $10,000 to $15,000 per month, and a BI pair is $20,000 to $30,000 per month. Total cost is team size × duration × monthly rate; BI licenses are separate.

How fast can a BI team start?

After the scoping call we propose a team with names. Most of the timeline depends on scope and on your onboarding, especially access to the warehouse, BI workspace and source systems.

Do we need a data warehouse before BI?

For anything beyond a few sources, yes. Dashboards built directly on application databases get slow and inconsistent. A warehouse with tested models gives BI a stable foundation, and our teams can build both.

Can you fix our existing dashboards instead of starting over?

Usually, yes. We audit usage and logic, keep what people rely on, move calculations into a shared model and retire duplicates.

Questions we didn't answer? Email info@ryzlabs.com.