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Business Intelligence Implementation: Plan, Software, Costs, and Required Skills

Full Guide on Business Intelligence Implementation - ScienceSoft

ScienceSoft has been providing a full range of BI services, including consulting, implementation, support, and BI as a service since 2005.

Business Intelligence (BI) Implementation: Summary

BI implementation allows analyzing company’s data to support decision-making at strategic, tactical and operational levels. 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.

Business intelligence Project Plan Steps

Each BI implementation project is unique in its requirements, and a set of steps for implementing BI depends on its scale and specificity. Based on our 17-year experience in delivering business intelligence solutions, we outline some general steps that are typical of most BI implementation projects:

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.


Feasibility study


Requirements engineering


Conceptualization and platform selection


Project planning

Alex Bekker

Alex Bekker, Head of Data Analytics Department at ScienceSoft, shares his experience:

Our practice has shown that effective BI implementation project planning can help reduce project time and budget by up to 30%.





User training




Solution support and evolution

Consider Professional Services for BI Implementation

ScienceSoft has 17-year experience in rendering BI services and knows how to carry out BI implementation with minimal costs while meeting your short- and long-term business needs.

BI implementation consulting

We offer:

  • BI implementation feasibility study.
  • BI solution concept.
  • BI needs business analysis.
  • BI solution launch strategy.
  • Optimal BI implementation sourcing model.
  • BI software selection.
Get BI implementation consulting

BI implementation

We help you implement a full-fledged solution in accordance with the defined strategy by:

  • Analyzing your BI needs.
  • Developing components of a BI solution (a data lake, DWH, OLAP cubes, reports and dashboards).
  • Setting up ETL processes.
  • Designing reports and dashboards.
  • Adding data science capabilities, if needed.
  • Conducting management activities (master data/metadata management, data quality assurance, data security, etc.).
  • Running quality assurance procedures, etc
Check Our Offer

ScienceSoft as a Trusted BI Consulting and Development Partner:

When we first contacted ScienceSoft, we needed expert advice on the creation of the centralized analytical solution to achieve company-wide transparent analytics and reporting. 

The system created by ScienceSoft automates data integration from different sources, invoice generation, and provides visibility into the invoicing process. We have already engaged ScienceSoft in supporting the solution and would definitely consider ScienceSoft as an IT vendor in the future.

Heather Owen Nigl, Chief Financial Officer, Alta Resources

Talents Required 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 dashboadring 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.

DevOps engineer

– sets up the BI software development infrastructure, automates and streamlines development and release processes by introducing CI/CD pipelines, monitors system security, performance, and availability, etc.

The sample BI implementation project involving building a DWH, an OLAP cube, custom-built reports and dashboards would require the following team composition:

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

*FTE – full-time equivalent (8 hours/day).

BI 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.

Lack Expertise for Your BI Implementation?

Based on the industry best practices and our domain experience, ScienceSoft will help you implement a cost-efficient BI solution with essential functionality to align with your business needs and then iterate as your BI needs grow.

BI Software ScienceSoft Recommends

Below, we list software from reliable tech vendors that we use in our BI projects. Among our recommendations are two leading (according to The Forrester Wave and Gartner Magic Quadrant reports) options of DWH platforms and a recognized by the major research companies (Gartner, Forrester, IDC, etc.) visualization tool that can work with both of them.

Amazon Redshift

Best for: big data warehousing


Data warehouse.


Leader in Gartner’s Magic Quadrant for Data Management Solutions for Analytics, this DWH stores and processes business data of (extra-) large volumes.

  • Ingestion of all data types.
  • Integrations with AWS services (including S3) and third-party tools.
  • Federated queries support.
  • ML capabilities.
  • Separate scaling of compute and storage, etc.


  • On-demand pricing: $0.25/hour (dc2.large) - $13.04/hour (ra3.16xlarge).
  • Reserved instance pricing offers saving up to 75% over the on-demand option (in a 3-year term).
  • Data storage (RA3 node types): $0.024/GB/month.

Azure Synapse Analytics

Best for: enterprise DWH


Data warehouse.


Leader in Gartner’s Data Management Solutions for Analytics, this DWH unifies enterprise data warehousing and big data analysis.

  • Ingestion of all data types.
  • Multilanguage support.
  • Embedded Spark engine.
  • Native integrations with an Azure data lake and operational database.
  • Built-in integrations with Microsoft’s BI and ML software and third-party solutions.
  • Advanced security, etc.


  • Compute on-demand pricing: $1.20/hour (DW100c) - $360/hour (DW30000c).
  • Compute reserved instance pricing allows saving up to 65% over the on-demand option (in a 3-year term).
  • Data storage: $122.88/TB/month.

Power BI

Best for: data visualization

Product category

BI and data visualization software.


The leading Analytics and BI platform (Gartner’s 2020 Magic Quadrant) and enterprise BI platform (the Forrester’s Wave).

  • Native connectors with 100+ data sources.
  • Multilanguage support.
  • Integrations with a data lake and operational databases.
  • Self-service data preparation and analysis.
  • Scheduled and ad hoc reporting.
  • Interactive dashboarding.
  • Pre-built and customizable visuals.
  • Row- and workspace-level security.
  • Data encryption.

DEMO: Watch our Power BI demo.


  • Power BI Desktop – free.
  • Power BI Pro – $9.99/user/month.
  • Power BI Premium –$4,995/dedicated storage and compute resources/month.

Choose BI Software with Expert Help

ScienceSoft is ready to assist you with the selection of the right technology stack for your BI project to reduce BI implementation costs and ensure maximum ROI.

BI Implementation Cost

The cost of a BI implementation project, which involves developing a data warehouse, OLAP cubes, reports and dashboards, depends on the BI system complexity and the company size and may range as follows:

  • $80,000 - $200,000* – for companies with 200 – 500 employees
  • $200,000 - $400,000* – for companies with 500 – 1,000 employees
  • $400,000 - $1,000,000* – for companies with 1,000+ employees

*Monthly software license fee and other regular fees are NOT included.

The cost of a BI implementation project may vary significantly from project to project. We present the major cost factors:

  • Number of data sources (ERP, CRM, HRM, EHR, ecommerce software, etc.).
  • Data volume.
  • Number of data tables and columns used for analysis.
  • Complexity of data cleansing procedures.
  • Types of analytics required, presence and number of machine learning algorithms.
  • Number and complexity of reports (including ad hoc reports).
  • Number of dashboards.
  • User permission system complexity.
  • Whether big data is to be analyzed.

About ScienceSoft

ScienceSoft is a global IT consulting and IT service company headquartered in McKinney, TX, US. Since 2005, we’ve been providing our customers with BI services, including BI consulting, implementation, supporting and upgrading a BI solution, or getting regular data analysis and reporting on a subscription-fee basis. Being ISO 9001 and ISO 27001-certified, we rely on a mature quality management system and guarantee cooperation with us does not pose any risks to our customers’ data security.