---
title: "BI Dashboard Development Services | Cyan Orbit"
description: "We build BI dashboards on a unified data model with row-level access rules, so numbers stay fast and consistent across every team that uses them."
url: https://cyanorbit.com/solutions/bi-dashboards
---

1. [Home](https://cyanorbit.com/)
2. [Solutions](https://cyanorbit.com/solutions)
3. BI & Reporting Dashboards

Solution

# BI Dashboard Development

Reporting built on one data model instead of five spreadsheets, with dashboards fast enough to stay useful against years of history.

[Get a project estimate](https://cyanorbit.com/get-a-quote?service=backend-development) [Talk to a developer](https://cyanorbit.com/contact)

NDA on request · Free, no-obligation estimate · Reply within one business day

NDA before discovery

You own the code and IP on payment

Code in your repository from day one

A working demo every two weeks

Senior engineers do the work

[How we work](https://cyanorbit.com/process)

Most companies do not lack data, they lack one version of it. Sales has a number, finance has a slightly different number, and both are technically correct because they are calculated differently from source systems that were never reconciled. A BI dashboard project is as much about building a clean, shared data model as it is about the charts on top of it.

We build dashboards on top of that shared model, whether the audience is internal leadership checking KPIs weekly or your own customers viewing analytics embedded inside your product.

## Usually commissioned by

- Companies where different teams report different numbers for what should be the same metric
- Businesses whose current reporting is a set of manually maintained spreadsheets pulling from multiple systems
- Products that need to embed usage or performance analytics directly inside their own customer-facing interface
- Teams whose existing BI tool has become slow or expensive as data volume and user count have grown

Scope

## Core features

- ### A unified data model across source systems  
Data from your CRM, ERP, product database, and other sources gets modeled into one consistent structure, so a metric like revenue is calculated the same way everywhere it appears.
- ### Role-based dashboard access  
Each dashboard and the data behind it is scoped to who should see it, so a regional manager sees their region's numbers and a finance dashboard stays restricted to finance.
- ### Scheduled report generation and distribution  
Reports that used to be built by hand every Monday get generated and emailed automatically on a schedule, freeing up the person who used to build them manually.
- ### Drill-down from summary to transaction detail  
A summary chart is not a dead end. Clicking into a number lets you see the underlying transactions or records that produced it, which is usually the first question anyone asks about a surprising figure.
- ### Refresh rate matched to how the metric is used  
A live operations metric refreshes near real time, while a monthly financial rollup refreshes on a schedule, since treating every metric as real time adds infrastructure cost without a matching benefit.
- ### Calculated metrics specific to your business  
KPIs unique to how your business actually operates, not just generic revenue and traffic numbers, get built into the data model directly so every dashboard calculates them the same way.
- ### Embedded analytics inside your own product  
Dashboards can be embedded directly inside your product's interface for your own customers, styled to match your product rather than looking like a separate reporting tool bolted on.
- ### Threshold alerting  
Key metrics can trigger an alert when they cross a defined threshold, such as a conversion rate dropping or a support queue growing past a limit, instead of relying on someone noticing during a weekly review.

Architecture

## Decisions that shape the build

- ### Choosing a data pipeline approach  
A batch ETL pipeline running on a schedule fits most reporting needs; a real-time streaming pipeline is worth the added complexity only for metrics that genuinely need to be current to the minute.
- ### Query performance against years of history  
Pre-aggregation and materialized views keep dashboards fast once the underlying data spans years of history, since querying raw transaction-level data live does not scale past a certain volume.
- ### Data governance and row-level security  
Access rules need to work at the row level, not just the dashboard level, so a sales manager sees only their team's deals even when using the same dashboard as everyone else.
- ### One source of truth instead of team-by-team numbers  
The shared data model is what stops each team from building its own definition of a metric in its own spreadsheet, which is usually the actual problem a BI project is solving.
- ### Licensing cost at scale  
Per-seat BI tool pricing can get expensive quickly as more employees need dashboard access, which is worth modeling against a custom or open-source approach before committing to a platform.

Build vs buy

## When to build and when to buy

Metabase and Power BI are strong, cost-effective choices for standard internal dashboards over data that is already reasonably centralized, and we recommend one of them outright when the need is straightforward reporting for internal teams. Looker and Tableau handle more complex, large-scale enterprise reporting well but carry meaningfully higher licensing cost as user count grows.

A custom or embedded approach is worth the extra build effort when dashboards need to live inside your own product for customers, since off-the-shelf BI tools are not built to be white-labeled that way, or when calculated metrics are specific enough to your business that a generic BI tool's modeling layer cannot express them without workarounds.

Delivery

## How delivery is phased

1. ### Define KPIs and source systems  
We identify the metrics that actually matter to the business and every source system that feeds into them, and reconcile any conflicting definitions before building anything.
2. ### Build the data pipeline and model  
The pipeline that moves and transforms data from source systems into the unified model gets built and validated against known correct numbers before dashboards are built on top of it.
3. ### Build dashboards and access rules  
Dashboards get built for each audience with role-based and row-level access rules applied. This typically takes several weeks depending on how many data sources and dashboards are involved.
4. ### Validate with stakeholders and launch  
Each dashboard gets checked against the numbers stakeholders currently trust before rollout, since adoption depends on the new numbers being credible from day one.

Technology

## Typical stack

- [PostgreSQL](https://cyanorbit.com/technologies/postgresql)
- [Python](https://cyanorbit.com/technologies/python)
- [AWS](https://cyanorbit.com/technologies/aws)
- [React](https://cyanorbit.com/technologies/react)
- [GraphQL](https://cyanorbit.com/technologies/graphql)

FAQ

## BI & Reporting Dashboards FAQs

Should we use Power BI, Metabase, or build custom dashboards?

Power BI or Metabase are usually the right starting point for standard internal reporting over reasonably centralized data. Build custom or embedded dashboards when you need to expose analytics inside your own product for customers, or when your KPIs are specific enough that a general BI tool cannot model them cleanly.

How do you keep a BI dashboard fast against years of historical data?

Pre-aggregated tables and materialized views compute expensive rollups ahead of time, so a dashboard query hits a small, fast summary table instead of scanning years of raw transaction data on every page load.

Can BI dashboards be embedded inside our own product for customers?

Yes. Dashboards can be embedded directly in your product's interface, styled to match your brand, and scoped so each customer only sees their own data, which most standalone BI tools are not designed to support.

How do you handle row-level security so users only see their own data?

Access rules are enforced at the query layer based on the logged-in user's role and scope, such as their region or account, so the same dashboard shows different rows to different users rather than relying on separate dashboards per user group.

What is the difference between real-time and batch refreshed dashboards?

A real-time dashboard reflects data within seconds or minutes, which requires a streaming pipeline and costs more to run. A batch refreshed dashboard updates on a schedule, such as hourly or daily, which is simpler and cheaper and fits most metrics that do not need to the minute accuracy.

Services

## Services involved

- [Backend DevelopmentWe build the server-side systems underneath your product: data models, business logic, queues and the infrastructure that keeps them fast under load.](https://cyanorbit.com/services/backend-development)
- [API DevelopmentWe design, build, document and version REST and GraphQL APIs that partners can integrate against without calling your engineers first.](https://cyanorbit.com/services/api-development)
- [Custom Software DevelopmentWe build software around the processes your business already runs on, so operations stop depending on spreadsheets, workarounds and tools that were never built for your workflow.](https://cyanorbit.com/services/custom-software-development)
- [Cloud & DevOpsWe design cloud infrastructure as code, build CI/CD pipelines, and get your team ready for incidents before they happen.](https://cyanorbit.com/services/cloud-devops)

Industries

## Industries that commission this

- [Retail & E-commerceInventory, POS and storefront software that stays in sync across every channel, with EDI wired in for your wholesale partners.](https://cyanorbit.com/industries/retail-ecommerce)
- [Logistics & Supply ChainFreight, warehouse and fleet software that speaks EDI 204/214/210 to your trading partners and stays accurate in the field.](https://cyanorbit.com/industries/logistics)
- [ManufacturingShop floor, ERP and traceability software that connects PLC data to the systems your planners and OEM customers actually use.](https://cyanorbit.com/industries/manufacturing)
- [Professional ServicesEngagement management, time tracking, and client portals built around the way consulting and advisory firms actually bill for their time.](https://cyanorbit.com/industries/professional-services)

Insights

## Planning guides

- [6 min readHow Much Does Custom CRM Development Cost?Custom CRM development cost typically ranges from $40,000 for a focused pipeline tool to $250,000+ for a multi-team platform with automation and reporting.](https://cyanorbit.com/blog/crm-development-cost)
- [7 min readCustom Development vs No-Code ToolsCustom development vs no-code tools compared on speed, cost at scale, and where each one actually holds up as your workflow gets more complex.](https://cyanorbit.com/blog/custom-development-vs-no-code)
- [8 min readHow Much Does Custom Software Development Cost?Custom software development cost ranges from $15,000 for a simple internal tool to $500,000 or more for enterprise platforms. Here is what drives the number.](https://cyanorbit.com/blog/custom-software-development-cost)

## Discuss your bi & reporting dashboards project

Share a few details about your project. A senior engineer reviews every request and replies with next steps, questions, and a rough budget range.

[Get a project estimate](https://cyanorbit.com/get-a-quote?service=backend-development) [Talk to a developer](https://cyanorbit.com/contact)