BI & Reporting Services That Make Your Data Work
You need business intelligence reporting that gives your leadership team answers, not more spreadsheets. Whether you want to hire a business intelligence company to consolidate your scattered data into a single source of truth, bring in experienced BI consultants for strategy and platform selection, or need full business intelligence services covering data warehousing, automated reporting, and predictive analytics, the goal is the same: make every decision in your organisation backed by data you trust.
Business intelligence implementation typically costs between $15,000 and $200,000 depending on data complexity, number of sources, and reporting requirements. A focused BI setup with a data warehouse and automated reports starts around $15,000. Enterprise BI with predictive analytics, self-service tools, and multi-department rollout runs $50,000 to $200,000.
Core Capabilities and Features
Data Warehousing
Your BI is only as good as the data behind it. A data warehouse is the structured, cleaned, centralised store of your business data. It pulls from your operational systems (CRM, ERP, billing, marketing), transforms the data into consistent formats, and makes it available for reporting and analysis.
- Warehouses built on BigQuery, Snowflake, or PostgreSQL depending on your scale and budget
- For smaller businesses, a well-structured PostgreSQL instance is often all you need
- For enterprises with billions of rows and dozens of sources, Snowflake or BigQuery provide the scale and speed required
Automated Reporting
Manual reporting is the silent killer of productivity. If your finance team spends two days every month building a report that could be automated, that is 24 days a year lost to data entry disguised as analysis. Your automated reports generate on schedule (daily, weekly, monthly), pull directly from your warehouse, and deliver to stakeholders via email, Slack, or a shared dashboard.
- Reports generate on schedule and deliver via email, Slack, or a shared dashboard
- Eliminates manual compilation and frees your team to analyse data instead of compiling it
- If your finance team spends 2 days each month building a board report in Excel, automation eliminates that entirely
Self-Service BI
Not every question requires a data engineer. Self-service BI gives business users the tools to explore data, build their own reports, and answer their own questions without filing a ticket with IT. Your self-service environments are set up in Power BI, Tableau, or Metabase with curated data models, pre-built dimensions and metrics, and governance guardrails that prevent users from accidentally accessing raw data or building misleading reports.
- Curated data models with pre-built dimensions and metrics for drag-and-drop analysis
- Governance guardrails that prevent access to raw data or creation of misleading reports
- Over 70% of enterprises now use self-service analytics
Why It Matters
If your monthly board report takes a week to compile, involves three people, and is out of date by the time it gets presented, that is not a reporting process. That is a warning sign. The organisations that grow fastest are the ones that know their numbers. Not approximately. Not based on the last report from two weeks ago. They know today's numbers, and they know what those numbers mean for next quarter. That level of clarity does not come from buying a BI tool. It comes from building a data infrastructure that connects your systems, cleans your data, and delivers insights automatically. It comes from reports that update themselves. Dashboards that answer questions without someone needing to build a new spreadsheet. And a team that is trained to use the tools confidently. The companies that get the most from their BI investment are the ones who treat it as a capability, not a project. They start small. They validate assumptions. They invest in data quality because they know that the most beautiful dashboard in the world is worthless if the data behind it is wrong. And they keep iterating: new questions, new data sources, new reports. That is the approach taken with every build, and it is the reason these BI implementations deliver value that lasts.
By the Numbers
$55B
The global BI market is growing at over 12% annually. Businesses that delay BI investment are not saving money. They are falling behind competitors who make faster, better-informed decisions.
Source: DataStackHub / BI Statistics, 2025
127%
BI implementations deliver an average 127% return on investment within three years. The return comes from faster decisions, eliminated manual work, reduced errors, and better resource allocation.
Source: DataStackHub / BI Statistics, 2025
85%
The failure rate is driven by unclear objectives, poor data quality, and scope overload. Starting with a focused pilot and expanding is far more likely to succeed than a company-wide rollout.
Source: Gartner / Integrate.io, 2026
18-22%
Organisations using BI report average cost reductions of 18 to 22% through improved forecasting and efficiency. BI does not just help you make better decisions. It helps you stop making expensive wrong ones.
Source: DataStackHub / BI Statistics, 2025
5x
Organisations with high BI adoption are five times more likely to make faster and better-informed decisions. Speed compounds: one faster decision per week adds up to 250 better decisions per year.
Source: Aberdeen Group
"The biggest BI failure we see is building 40 reports before anyone has asked a single question. Start with one question. Answer it reliably. Earn trust. Then scale. That approach works every time."
Technologies
Our Tech Stack
Our Process
How we turn ideas into reality.
Discovery & Assessment
Your current data landscape is audited. Where does your data live? What systems produce it? How does it flow (or not flow) between departments? What reports do people currently create manually? What questions do they want answered but cannot get to? This phase typically takes 1 to 2 weeks and gives the foundation for everything that follows.
BI Strategy & Architecture
Based on the audit, your BI architecture is designed. This includes the data warehouse design (star schema, snowflake, or data vault depending on your needs), ETL pipeline architecture, data governance rules, and the reporting and analytics layer. The right BI platform is recommended for your context, not the one with the fanciest marketing.
Warehousing & Pipeline Build
The infrastructure that makes BI possible is built. This is the engine: extracting data from your source systems (CRM, ERP, databases, marketing tools, billing), transforming it into a consistent format, and loading it into a warehouse (BigQuery, Snowflake, or PostgreSQL). Tools like dbt, Apache Airflow, or Fivetran are used depending on complexity and budget.
Report & Dashboard Development
The reports and dashboards your team needs are built using Power BI, Tableau, Looker Studio, or Metabase depending on your environment. Every report is designed for a specific audience and a specific decision. Self-service reporting capabilities are also built so business users can create their own reports without waiting for IT.
Pricing
Investment Overview
Number of Data Sources
Connecting 3 systems is straightforward. Connecting 12 systems with different APIs, data formats, and update frequencies requires a more complex warehouse and pipeline architecture.
Data Volume and Complexity
A company with 100,000 rows of monthly sales data needs different infrastructure than one processing 50 million transactions per day. Scale drives warehouse costs and query performance requirements.
Platform Licensing
Power BI Pro costs around $10 per user per month. Tableau Creator is around $75. Snowflake and BigQuery charge based on storage and compute. Open-source tools (Metabase, Apache Superset) eliminate licensing but require more engineering to maintain.
Everything we do at Techneth is built around making data move reliably between the systems that matter. If you want to understand our approach before committing, you can read more about our team and how we work. Or explore the full range of digital product and development services we offer, like business intelligence and reporting. And if you already know what you need, get in touch directly and we will find time to talk.
Frequently Asked Questions
Everything you need to know about this service.
- How long does a BI implementation take?
- A focused BI pilot (one department, 2 to 3 data sources, automated reporting) takes 4 to 8 weeks. A full enterprise BI rollout with multiple departments, predictive analytics, and self-service capabilities takes 3 to 9 months. Starting with a pilot that proves value quickly, then expanding in phases is recommended. Trying to build everything at once almost always results in a project that delivers nothing usable.
- What is the difference between BI and data analytics?
- Data analytics typically focuses on specific questions: which campaigns performed best? What is the conversion rate? BI is broader. It covers the infrastructure (data warehouse, pipelines, governance), the tools (Power BI, Tableau), and the processes (automated reporting, self-service, forecasting) that enable an entire organisation to make data-driven decisions. Analytics is a subset of BI. BI is the system that makes analytics reliable and scalable.
- Which BI platform should I use?
- It depends on your environment, team skills, and budget. Power BI is the strongest choice for Microsoft-heavy organisations, it is affordable and integrates deeply with Azure and Excel. Tableau is best for complex visual analysis and is preferred by data teams. Looker Studio is free and works well for Google-connected marketing data. Metabase and Apache Superset are strong open-source options for teams with engineering resources.
- What is a data warehouse and do I need one?
- A data warehouse is a centralised store of your business data, structured for reporting and analysis. It pulls from your operational systems (CRM, ERP, billing) and organises data into a format optimised for queries. You need one if you have 3 or more data sources, if your reports take too long to generate, or if different teams report different numbers for the same metric. Without a warehouse, you are running BI on top of operational databases, which is slow, fragile, and risky.
- Can you automate our monthly reporting?
- Yes. This is one of the most common and highest-ROI BI projects. Automated reports pull from your data warehouse, generate on a schedule (daily, weekly, monthly), and deliver via email, Slack, or a shared dashboard. If your finance team currently spends 2 days each month building a board report in Excel, automation eliminates that entirely. The report updates itself, and your team spends that time analysing the data instead of compiling it.
- How do you ensure data quality?
- Data quality is built into the pipeline from the start. This includes automated validation rules that check for completeness, consistency, and accuracy at every stage of the ETL process. Data reconciliation checks compare warehouse totals against source systems. Monitoring and alerting are set up for data freshness, pipeline failures, and anomalies. A data dictionary documents definitions, ownership, and update frequency for every metric.
Ready to get a quote on your business intelligence and reporting?
Tell us what you are building and we will put together a scoped proposal within 3 business days. Here is what happens when you reach out:
- 1You fill in the short project brief form (takes 5 minutes).
- 2We review it and come back with initial thoughts within 24 hours.
- 3We schedule a 30 minute call to align on scope, timeline, and budget.
- 4You receive a written proposal with fixed price options.
No commitment required until you are ready. Request your free business intelligence and reporting quote now.
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