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BI development: a step-by-step roadmap,
system components & benefits

October 21, 2025

Business intelligence software development roadmap

A BI development process can differ from one project to another depending on available resources, BI solution complexity, and the company’s priorities. Here is a typical roadmap for BI solutions development encompassing the key phases of such a project.

1

Discovery & solution conceptualization

At the beginning of the BI development project, a BI team gathers information on a company’s analytical and reporting objectives, expectations from the BI solution, and issues users currently face when analyzing and visualizing data. Then, they assess the company’s IT infrastructure, conduct an initial review of data sources and data quality, including its completeness, timeliness, accuracy, and consistency, and evaluate existing data security and regulatory compliance practices.

Based on preliminary research results, BI specialists outline functional and non-functional requirements for the BI solution and identify potential project risks.

2

Architecture design

The BI team proceeds with a more comprehensive audit of data sources and conceptual and logical data modeling. They also design ETL/ELT processes, data storage solutions, data models for OLAP cubes, and dashboards for various user roles. Besides, they establish the BI system’s policies for data integration and quality control, data protection practices, and data governance standards and policies.

3

Deployment environment & technology selection

After designing the BI solution’s architecture, the BI team selects the most suitable environment for BI deployment, such as cloud, on-premises, or hybrid, and chooses an optimal tech stack for each component of the BI system.

4

Project implementation planning

At this point, the BI delivery team outlines the scope of BI system development and testing activities, develops an implementation strategy, plans resource distribution, formulates the approach to risk management, and calculates BI development project costs, duration, and TCO. Here, they also outline a BI development team’s roles and responsibilities, establish communication workflows and channels, and create the project’s schedule.

5

Components development & delivery to the staging environment

The development process covers building or configuring data connectors and ETL/ELT processes, developing data storage solutions, including enterprise data warehouses, data lakes, and data marts, and implementing data quality management policies and mechanisms.

BI specialists also design and implement data processing and querying mechanisms, implement data security mechanisms, including row-level security, access controls, and network monitoring, and integrate the BI solution with the business’s broader IT ecosystem. Moreover, they create role-specific reports and dashboards, enabling users from different departments to visualize the analysis results and present the insights in an understandable format.

Throughout BI development, the team thoroughly reviews the solution to confirm that it matches the outlined business requirements. They use different types of QA activities to make sure the software operates as intended, including functional, performance, usability, and compatibility testing.

6

Solution deployment to the target environment

At this stage, BI engineers deliver the developed BI solution to the live environment, prepare technical documentation to explain the design, development, and usage of a BI system for future reference, and educate users on how to utilize it effectively to fulfill their specific needs. After the BI system's launch, the BI team can monitor its performance, stability, and usability and troubleshoot any issues that emerge. If required, they also integrate new data sources and configure additional dashboards to improve the BI solution’s operation.

Essential BI components to develop

BI development involves creating an ecosystem of integrated components that cover different activities in the business intelligence lifecycle.

Data integration

These solutions consolidate information from different sources utilizing various methods, such as ETL/ELT, change data capture, and data virtualization, and ensure its accuracy and completeness for further storage and analysis.

Data storage

These include data warehouses and other data storage options, like data marts, data lakes, lakehouses, and operational data stores, that keep enterprise data in a ready-for-analysis format and simplify data access.

Data analytics

A data analytics component contains engines that process data to generate descriptive, diagnostic, prescriptive, and predictive insights, discovering trends and patterns within large datasets.

Data visualization

Data visualization tools enable data analysts and business users to transform complex data into an easy-to-understand format with the help of intuitive reports and dashboards.

Data quality

Comprehensive data quality management policies and practices help companies maintain data accuracy, consistency, and reliability throughout its lifecycle in the BI system.

Data governance

A robust data governance and security framework establishes data ownership and access controls, ensuring its integrity and safety across all BI workflows.

Business intelligence use cases

For key business areas

Enterprise BI

Enterprise-grade BI solutions help analyze data from the entire organization, enabling top-level executives to monitor key performance indicators, evaluate overall business health, compare it against set goals and competitors, and make strategic decisions.

Operational BI

Operational BI solutions enable front-line managers and employees to analyze real-time data on current business operations, production output, resource availability, and incidents and swiftly respond to changing conditions.

Human resources

Business intelligence tools help HR specialists analyze employee productivity and satisfaction, predict employee churn, identify training needs, make better hiring decisions, and optimize staff allocation and schedules.

Supply chain management

Processing data from supply chain operations, business intelligence software helps specialists drill down into the details about inventory levels, supplier performance, and delivery efficiency to optimize fulfillment accuracy and speed, prevent understocking, and analyze market trends to forecast demand.

Finance

BI tools for financial departments enable financial data analysis and performance tracking, providing insights into the company’s profitability, cash flow, expenses, and revenue and facilitating budget planning and financial risk forecasting.

Customer service

Customer service departments use BI software to analyze client satisfaction, agent performance, and issue resolution effectiveness. BI solutions also provide insights into the issues customers face, how fast specialists resolve problems, which channels are the most effective for customer support, whether clients find the service helpful, and how to improve their experience.

Marketing & sales

Marketing and sales teams use BI tools to dive into various performance metrics and ensure the effectiveness of their promotional campaigns. BI software for marketing and sales also facilitates the analysis of customer-related metrics, such as engagement, satisfaction, and churn, helping forecast customer behavior, identify high-value clients, and personalize customer experience.

For various industries

Healthcare

Healthcare providers use BI software to evaluate caregiver performance, analyze patient feedback, predict patient needs, and personalize care.

Retail & ecommerce

For store owners and employees, BI software facilitates the company’s product offering analysis, sales tracking, demand forecasting, as well as the creation of a 360-degree customer view for developing personalized offers, enabling the optimization of inventory management, product pricing, and positioning.

Financial services

Financial institutions apply BI tools for activities such as analyzing trading data to predict investment risks, detecting signs of financial fraud based on transaction data, evaluating portfolio performance, budgeting and revenue forecasting, and handling regulatory compliance.

Manufacturing

In the manufacturing industry, business intelligence solutions help monitor inventory levels, plan procurement activities, predict equipment maintenance needs, and analyze energy utilization and emission levels.

Real estate

Real estate agents employ BI systems to analyze property value, sales data, and property management practices, evaluate property profitability factors, and track rent trends and property price dynamics.

Telecommunications, media & entertainment

Using BI systems, companies from the telecommunications, media, and entertainment sectors can determine customer profitability, lifetime value, and churn factors, timely catch indicators of customer attrition, and evaluate marketing and product success.

Real-life examples of BI development

BI platform for a fashion retailer

50%

cut in infrastructure costs

BI platform for a fashion retailer

Itransition developed a centralized BI platform for data gathering and business analysis, which helped the client personalize customer experiences and increase the visitors-to-buyers conversion rate by 8%.

BI for incident management

BI for incident management

Itransition developed a BI solution for incident analytics to replace the client’s disjointed systems, expanding the functionality of legacy solutions, adding new capabilities, and making the system easier for the client to maintain.

BI solution for case study coverage analysis

19%

growth of the number of leads

BI solution for case study coverage analysis

Itransition delivered a BI solution that encompasses a case study scoring system, an expertise scoring system, and dynamic dashboards. The system enables users to analyze the company’s portfolio cases and discover expertise coverage gaps to optimize content development efforts.

Benchmark dashboards for ad campaign optimization

7x

reduction in spending

Benchmark dashboards for ad campaign optimization

Itransition developed BI software for ad campaign forecasting and ad impressions monitoring that helped the client make accurate predictions about marketing campaign outcomes and accurately evaluate the effectiveness of campaigns and advertising strategies.

Benefits of developing a BI solution

Increased data availability

A business intelligence system aggregates data from the company’s systems in a single place and ensures its reliability, usability, and accessibility for analysis and informed decision-making.

Streamlined reporting

Users can easily and quickly get access to the needed insights via a unified interface and generate comprehensive reports without having to switch between different tools to pull together distributed data.

Cost reduction

Business intelligence tools automate manual data management processes, allowing companies to cut down on costs related to time-consuming report compilation, human errors, and missed cost-saving opportunities.

Competitive advantage

Able to benchmark their business performance against other market players, companies can make business decisions targeted at addressing product gaps and customer journey bottlenecks to outperform their competitors.

Risk mitigation

By providing a complete picture of business processes, BI software enables companies to identify potential risks that can lead to operational disruption and downtime and mitigate them proactively to maintain business continuity.

New opportunities identification

BI solutions streamline industry trend analysis, allowing businesses to anticipate market shifts, pinpoint underserved niches, and seize potential sales opportunities to develop new products, optimize their marketing efforts, and enter overlooked markets.

Itransition’s BI development services

Ensure the success of your BI development project with Itransition

Get a quote

Enable long-term business growth with a BI solution

As company needs evolve and the number of operations and tools grows, getting insights from data scattered across business departments and systems becomes challenging. BI software helps different users, from C-suite executives to regular employees, get accurate and easy-to-interpret insights to make better decisions.

If you want to enhance your current analytics and reporting capabilities, consider turning to Itransition to determine how BI can support your goals, conceptualize your BI solution, and provide comprehensive BI development services.

FAQs

To excel in their field, a BI developer should be proficient in the following areas:

  • Data analysis, database development, and data integration and transformation
  • Scripting and programming languages such as SQL, Python, R, JavaScript, and others
  • Data warehousing concepts and data modeling
  • Analytical thinking and problem-solving
  • Data science, data mining, and machine learning concepts
  • Creating, maintaining, and updating technical documentation
  • Team and client collaboration and communication

Becoming a business intelligence developer requires specific education, i.e., a bachelor’s degree in information technology, business intelligence, computer science, mathematics, or software development.

Also, you need to obtain real-life experience and constantly deepen your knowledge of BI tools and development technologies by taking dedicated courses and getting a certification from recognized institutions or companies to boost your credibility.

Business analytics is a subset of BI that focuses on analyzing data to understand past events and predict future outcomes using advanced statistical analysis, data modeling, and machine learning algorithms. Business intelligence, in turn, involves analyzing current and past enterprise data and visualizing it using descriptive dashboards and reports. This way, BI helps stakeholders better understand the company’s present-day operations and performance to make tactical and strategic decisions.

Data engineers focus on creating a data architecture that supports the company’s data analytics and reporting operations, while data scientists develop statistical models, machine learning algorithms, and predictive analytics solutions to process complex datasets and uncover trends and insights from them. A BI developer, in turn, works in collaboration with these specialists to conceptualize and implement reporting and analytical solutions in line with the company’s business needs.

Data integration & quality management

Azure Data Factory

Azure Stream Analytics

Azure Functions

Azure Event Grid

Azure Event Hubs

Microsoft SQL Server Integration Services

AWS Glue

AWS Data Exchange

Amazon MWAA

Oracle Data Integrator

Databricks

Apache NiFi

Talend

Informatica PowerCenter

MuleSoft Anypoint Platform

IBM InfoSphere Information Server

SnapLogic

Syncsort

Striim

Pentaho

Fivetran

Matillion

Data storage

Azure Blob Storage

Azure Data Lake Storage

Azure SQL Database

Azure Synapse Analytics

Azure SQL Database elastic pools

Azure SQL Managed Instance

Azure Cosmos DB

Amazon S3

Amazon Redshift

Amazon Aurora

Amazon RDS

Amazon DynamoDB

Amazon ElastiCache

Google BigQuery

Google Cloud Storage

Microsoft SQL Server

PostgreSQL

MySQL

Oracle

IBM Cloud Object Storage

SAP HANA Cloud

Teradata

Data analytics

Azure Synapse Analytics

Azure Analysis Services

Microsoft SQL Server Analysis Services

Amazon Redshift

Amazon Athena

Amazon Kinesis Data Analytics

Google BigQuery

Data visualization
Microsoft Power BI Tableau

Qlik Sense

QlikView

Amazon QuickSight

Looker

Apache Superset

Metabase

Redash

Datawrapper

Infogram

Excel

Python
Data security management

Microsoft Entra ID (formerly Azure Active Directory)

Azure Firewall

Azure Key Vault

Azure VPN Gateway

Amazon Cognito

AWS KMS

AWS Secrets Manager

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