Business Intelligence Implementation
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What We Do
Business Intelligence (BI) Implementation: Summary
Business intelligence implementation allows analyzing company’s data to support decision-making at strategic, tactical and operational levels.
Based on devstudio360 experience with real-life projects, BI implementation may take from 6 months and cost from $80,000, requiring a team of a PM, a BA, a solution architect, a BI developer, a data engineer, QA and DevOps engineers.
You can use our online calculator to get a ballpark cost estimate for your case.
Business Intelligence Implementation Steps
Each business intelligence implementation project is unique in its requirements, and a set of steps depends on its scale and specificity. Based on our 18-year experience in delivering business intelligence solutions, we outline some general steps that are typical of most projects.
Key steps to business intelligence implementation
- Conduct feasibility study.
- Gather requirements.
- Conceptualize and select platform.
- Plan the project.
- Develop the solution.
- Train users.
- Launch the project.
- Support and evolve the solution.
Sample project scope
- Business domain: Market analysis, financial analytics.
- Data sources: 2 big data sources (data in the data sources has clear mapping rules, so no data cleaning is needed).
- Storage layer: Data warehouse (cloud deployment).
- Analytics layer: an OLAP cube (a multidimensional dataset for online analytical processing).
- Data output layer: Power BI reports and dashboards (dashboard levels: CEO, department, personal).
- Data security model: Role-based security model.
1. Feasibility study
2. Requirements engineering
3. Conceptualization and platform selection
- Defining the desired BI solution features, technology stack and skills required to fulfill the project.
- Mapping the proposed solution to the requirements.
- Defining data sources and ETL procedures, data quality assurance processes, business intelligence implementation and user adoption strategies.
As a result, the project team draws up the solution architecture with a detailed feature list.
4. Project planning
- Defining deliverables, assessing risks, estimating BI implementation costs, TCO and ROI. After fulfilling this step, you get a detailed project plan, a project schedule and a communication plan.
5. Development
- Delivering the back end and the front end of the BI solution.
- Implementing ETL processes for each of the data sources, setting up data quality management and data security.
- Running quality assurance procedures to avoid such problems as wrongly calculated KPIs, slow BI solution response or low-quality UX.
6. User training
- Providing end users with user manuals and training sessions.
- Adjusting common workflows for each user group, etc.
7. Launch
- Pre-launch user acceptance testing to check the BI solution in real-world scenarios.
- Deploying the solution in production, ready for end users to employ.
8. Solution support and evolution
Further, in the course of BI evolution, the team can upgrade the solution with self-service capabilities, advanced business analytics and data science capabilities, etc.
Consider Professional Services for BI Implementation
devstudio360 offers 19 years of expertise in BI implementation services, delivering cost-effective business intelligence solutions tailored to meet both your short- and long-term business needs.
BI consulting
- Feasibility study.
- Solution concept.
- Business analysis.
- Launch strategy.
- Optimal sourcing model.
- BI software selection.
BI implementation
- Analyzing your BI needs.
- Developing a BI solution’s components.
- Setting up ETL processes.
- Designing reports and dashboards.
- Adding data science capabilities, if needed.
- Conducting data management activities.
- Running quality assurance procedures, etc.
devstudio360 Team to Implement a BI Solution
Project manager
– manages scoping, planning, executing, and monitoring all aspects of the BI implementation project.
Business analyst
– interprets business needs, spells out the BI solution requirements, BI solution functionality, user roles, content and modules, integrations of the future BI solution.
Solution architect
– models BI infrastructure components (DWH, ETL processes, BI reports, etc.) and their integration points, ensures design feasibility.
Business intelligence developer
– develops a data model, sets up ETL processes, implements and maintains data modeling tools, query tools, data visualization and dashboarding tools, ad hoc reporting tools, etc.
Data engineer
– transforms data into a format suitable for analysis by analyzing raw data, developing and maintaining datasets, improving data quality and efficiency.
Quality assurance engineer
– validates the BI solution: designs and implements a test strategy, a test plan and test cases for BI components, validates SQL queries related to test cases and produces test summary reports.
Feasibility study – project planning stages
- Project manager – 1 FTE*
- Solution architect – 1 FTE
- Business analyst – 2 FTE
- Data engineer – 0.5 FTE
- Business intelligence developer – 0.5 FTE
- Quality assurance engineer – 0.5 FTE
- DevOps engineer – 1 FTE
Development – user training stages
- Project manager – 0.5 FTE
- Solution architect – 0.5 FTE
- Business analyst – 1 FTE
- Data engineer – 2 FTE
- Business intelligence developer – 1-2 FTE
- Quality assurance engineer – 2 FTE
- DevOps engineer – 0.25 FTE
Launch stage
- Project manager – 1 FTE
- Business analyst – 0.5 FTE
- Data engineer – 1 FTE
- Business intelligence developer – 1 FTE
- Quality assurance engineer – 1 FTE
- DevOps engineer – 1 FTE
The sample BI implementation
project involving building a DWH, an OLAP cube, custom-built reports and dashboards would require the following team composition:
Business Intelligence Implementation Sourcing Models
All in-house
The company has full control over the BI implementation project.
Caution: The implementation project can be delayed or compromised due to the lack of the required resources.
Technical activities are partially outsourced
Hiring a vendor to outsource the design, implementation or support of the BI solution. The model presupposes your high control over the implementation project.
Caution: High requirement for in-house competencies.
Technical activities are fully outsourced
Among the major pros – no risk of the resource overprovisioning after the project completion.
Caution: High requirements for in-house PM and BA competencies.
Everything is outsourced, except a project sponsor
This model promises no idle costs and no delays due to resource unavailability.
Caution: Increased vendor risks due to increased vendor dependency.
