Business intelligence implementation is setting up practices and technologies to collect, aggregate, and analyze business information. Itransition delivers effective BI solutions to help companies make data-driven business decisions, improve operational efficiency, and drive more revenue.
the projected global business intelligence market by 2028
Fortune Business Insights
of the global workforce have access to business intelligence tools
Accenture
of large enterprises plan to invest more in their business analytics initiatives
MicroStrategy
15+ years in business intelligence
20+ years in enterprise software development
Solid experience in delivering custom, platform-based, and embedded BI solutions
Strategic partnerships with Microsoft, AWS, and Google Cloud
40+ successful BI projectsÂ
faster time-to-market
We migrated the customer’s legacy BI system to the microservices architecture to achieve a 15-20x higher system throughput, 100% process predictability and transparency, and 50% higher productivity.
reduction in spending
We developed an analytics optimization suite for a leading digital media company to make realistic forecasts based on the results of marketing campaigns and monitor advertising campaign performance.
While a BI implementation process can differ from company to company depending on their needs, objectives, and BI strategy, some steps are typical for most projects. Below, we’ve formulated a typical implementation roadmap for an enterprise BI solution based on our experience:
A BI implementation project starts with the elicitation of business needs and goals, expectations, risks and concerns, as well as existing issues and bottlenecks from stakeholders, including C-level executives, department managers, data analysts, business consultants, and users.
At this stage, your goal is to get a clear vision of what business problems you want to solve with the BI implementation. You can do this using a combination of various techniques, such as interviews, brainstorming sessions, workshops, observation sessions, questionnaires, and business process audits. Based on the findings, you can define the overall trajectory of the BI implementation project and use them as the foundation for a BI solution conceptualization. You can also break down the defined business needs into KPIs to measure the company’s BI implementation progress down the line.
The internal IT team carries out BI implementation
Before we outline the most popular BI software options, here’s a checklist of must-have BI functionality:
The cost of implementing a full-scale BI solution depends on multiple factors, including:
Consolidation of all business-critical data into a central database helps break down data silos and ensure data consistency across business departments.
Accurate and timely reporting, personal data views, and an intuitive user interface can encourage business users to make data-driven decisions, regardless of their tech expertise.
A 360-degree view of the business allows decision-makers to assess corporate performance against the set goals, identify inefficiencies, and spot growth opportunities.
Data-driven insights can improve customer-facing activities like pricing, churn prevention, promotion optimization, cross-selling and upselling.
Business process transparency can optimize internal processes such as supply chain management, fraud prevention, demand planning, procurement management, and more.
Solid analytics capabilities can help discover emerging trends, study competitors, and quickly spot changes in demand, market capacity, and investment environment.
Challenge
Analytics insights across different departments can appear inconsistent, outdated, or irrelevant.
Challenge
Solutions we offer
Poor data quality may jeopardize the overall BI success, resulting in wasted time and resources and business stagnation. To avoid that, we help companies adopt a solid data quality management approach, which involves:
Challenge
BI adoption levels are not as high as expected.
Challenge
Solutions we offer
Here’s how companies can mitigate BI adoption issues:
Challenge
Deployment of self-service tools across different business units results in a chaotic data environment and overlapping KPIs.
Challenge
Solutions we offer
Self-service data analysis and exploration should be regulated by robust data governance standards and policies, which should be established before the BI deployment.