Enterprise business intelligence: end-to-end solution overview
December 24, 2024
Enterprise business intelligence facilitates the consolidation of business data from all of a company’s departments and divisions in a secure central storage, its analysis, and delivery to end-users in the form of reports and dashboards based on their roles.
Itransition delivers full-scale enterprise BI solutions for companies across industries to support their operational and strategic business decisions.
Key capabilities of enterprise BI
Business intelligence tools enable enterprises to analyze complex data and visualize it in an easy-to-understand format, which helps make data-driven decisions and optimize business processes for better productivity.
Data analysis
Analyze corporate data to generate meaningful insights and support a fact-based decision-making process.
- Identifying important patterns and trends in data
- Defining the correlation between various eventsÂ
- Future trends and outcomes forecasting Â
- Recommending actions to achieve desired business objectives
- Real-time data management and analysis
Reporting
Deliver actionable insights in an easy-to-read format for end-users to help them with daily tactical decisions as well as strategic decision-making and planning.
- Time-based and rule-based distribution of static reports and dashboardsÂ
- Custom reporting with a pre-determined layout and a predefined set of KPIs
- Interactive reporting with configurable chart types, filters, formatting, language, and locale settingsÂ
- BI content embedding into web pages and applicationsÂ
- Mobile reporting
Data visualization
Turn complicated data sets into interactive and immersive reports and dashboards with a wide range of visuals (e.g., heat maps, scatter plots, and pivot tables).
- Custom visualsÂ
- Pre-built visualsÂ
- Visual data querying
- Data storytelling
Collaboration & sharing
Real-time collaboration with coworkers and partners to enable cross-functional alignment and data-driven decision-making. Â
- Report and dashboard sharing and distribution
- Content commenting
- Alerting and notifications
- Personalized and chronological catalog of user activities and interactions
- Collaborative workplacesÂ
- Content search
- Automated report and dashboard updates
Empower end-users, regardless of their tech expertise, to find the data they need and answer their ad hoc queries via self-service capabilities with respect to data security. Â
- Ad hoc self-service analytical querying
- Augmented analytics capabilitiesÂ
- Intuitive user interface
- Easy-to-use report design for ad hoc reporting and analysis
- Natural language processing capabilities
Data consolidation & storage
Consolidate diverse data sets in a unified data storage, making data accessible, and ensuring its appropriate format and quality for analytics and reporting.Â
- Seamless connection to existing data sources located on-premises and in the cloudÂ
- Ingestion of structured, semi-structured, and unstructured data
- Batch and streaming data processing
- Data transformation and quality management enabled by the ETL/ELT processesÂ
- Consolidation of company-wide data in an enterprise data warehouse and business line data in subordinate data marts
- Accompanying analytics data stores with an operational data store and a data lake for operational and high-volume business data
Data governance & security
Ensure business data is of proper quality, secure, and used in alignment with established data governance policies and standards. Â
- Role-based access control
- Configurable data security levels
- Dynamic data encryption and masking
- User activity log
- Data auditingÂ
- Enterprise data catalogs
- Compliance with internal and external data privacy and security regulations
Selected success stories
10x
faster data processing
Pharmaceutical BI for a US multinational
Itransition redeveloped the customer’s business intelligence platform and migrated it to the cloud, which resulted in streamlined data processing, advanced analytics insights into employee performance, and reduced operational costs.
70%
faster time-to-market
Cloud BI for vehicle manufacturers
Itransition transformed the customer’s legacy BI system, which helped achieve 100% predictability of business processes across geographically distributed teams and 50% higher productivity.
Looking for a trustworthy enterprise BI technology partner?
The architecture of each enterprise BI system is unique, as it is tailored to the industry and the specific business needs of the enterprise. However, there are five core components that generally constitute an enterprise BI solution.
1
Data sources
1
Data sources
These include internal and external data sources providing information for a BI system. Such sources include corporate solutions and applications supporting day-to-day business workflows, relational databases, IoT devices, internal documents and archives, a corporate website, surveys and statistics, as well as data from business partners and competitors.
2
Data integration & quality management
2
Data integration & quality management
Before being analyzed, data must be modified to become consistent, accurate, relevant, and complete. The choice of data integration methods and the complexity of data quality management depend on the data type, format, volume, and data analysts’ requirements.
3
Data repositories
3
Data repositories
When cleaned and consolidated, data is further structured in an enterprise data warehouse according to the predefined data model. Enterprise BI solutions can also include an operational data store to host real-time data for quick reporting and a data lake to consolidate varying volumes of raw data for ML and big data workloads.
4
BI & analytics layer
4
BI & analytics layer
This component encompasses a set of tools, such as OLAP software, data mining, and data visualization tools, that enable BI users to access and manipulate business data. The functional scope of this layer is defined by the analytics maturity of an enterprise.
5
Data governance
5
Data governance
This component includes a set of tools and practices that help govern the BI workflow, ensure data security, availability, and quality, and proper and beneficial use.
Benefits of implementing enterprise BI
Data consolidation
The aggregation of different types of enterprise data from siloed systems with varying data models into a single unified storage helps achieve data accuracy, transparency, and reliability.
Enhanced data quality & value
Enterprise BI tools allow for aggregating disparate data sets and drawing meaningful and accurate insights from them. It reduces errors and helps companies make better business decisions, cutting costs and improving productivity.
Data-driven decision-making
Quick access to high-quality relevant business data, elimination of communication bottlenecks, and convenient self-service capabilities help meet the varying analytics and reporting needs of business users regardless of their tech skills and seniority levels.
Best enterprise business intelligence platforms
Enterprise BI use cases by industry
BI solutions for the retail sector help increase customer satisfaction, craft effective marketing and sales campaigns, and quickly identify new sales opportunities.
- Inventory levels optimization
- Inventory planning, including purchasing, replenishment, and allocation
- Product assortment assessment and planning
- Dynamic price modeling
- Customer satisfaction and loyalty analysis
- Customer lifetime value calculation
- Customer behavior modeling
- Customer attrition and retention analysis
- Supplier performance assessment and risk forecasting
- Analysis of marketing campaign effectiveness
- Marketing and sales KPIs tracking
- Sales performance analytics
- Sales forecasting and planning
BI solutions for financial institutions are used to mitigate financial risks, enhance customer experience, and increase customer lifetime value.
- Financial performance KPIs monitoring, including net profit, cash conversion cycles, and operating profit margins
- Tracking financial behavior and detecting fraudulent activities
- Spend analysis
- Analysis of investment strategies and benchmarking
- Revenue and profitability analysis
- Customer retention metrics monitoring, including attrition rate, average order value, repeat customer rate, and purchase frequency
- Customer lifetime value calculation
- Financial risks monitoring and assessment
- Marketing campaigns profitability analysis
- Monitoring market trends and predicting customer needs/behavior
- Customer portfolio analysis
- Customer portfolio analysis
- Accounts receivable and accounts payable forecasting
BI solutions for healthcare organizations help analyze patient and clinical data and improve patient care, diagnostics accuracy, care teams coordination, and treatment efficiency.
- Patient needs anticipation
- Patient risks prediction
- Patient readmission forecasting
- Patient satisfaction analysis
- Caregiver performance monitoring and evaluation
- Outbreaks prediction
- Workload prediction and medical staff scheduling
- Healthcare insurance fraud detection
Manufacturing
Manufacturing BI solutions facilitate efficient production planning, informed decision-making, minimized production errors, and improved overall equipment efficiency.
- Tracking the performance of individual machines and departments
- Analyzing uptime and downtime per employee, machine, and department
- Scrap rates monitoring
- Production quality analysis
- Procurement planning
- Bottlenecks and shift performance analysis
- Suppliers performance monitoring and evaluation
- Demand forecasting
- Optimal inventory levels forecasting
BI solutions for marketing agencies help target customers with the optimal products and services, maximize business performance with effective marketing strategies, and identify new target audiences.
- Measuring the effectiveness of marketing efforts by channels
- Analyzing marketing campaign performance
- Tracking trends in customer behavior
- Customer engagement analysis
- Customer satisfaction and loyalty analysis
- Customer lifetime value calculation
- Customer behavior modeling
- Marketing and sales resource planning
- Budget analysis and planning
- Customer attrition and retention analysis
Telecommunications
BI solutions empower telecom providers to make meaningful upgrades to their services and support options, create targeted campaigns, refine pricing strategies, launch new products, or discontinue unprofitable ones based on customer needs.
- Analysis of customer needs, preferences, and demographics
- Customer profitability analysis
- Customer lifetime value calculation
- Customer churn prediction
- Customer attrition analysis
- Marketing campaign analysis
- Analysis of product performance, usage, and revenue
Real estate
BI solutions for the real estate sector help companies spot new investment opportunities, enhance customer experience, maximize profits, and minimize operational risks.
- Property value analysis
- Analysis of variables affecting property’s long-term profitability
- Property sales analysis
- Marketing campaign monitoring and evaluation
- Property management analysis
- Market rent analysis
- Analysis of brokerage agents’ activities and performance
- Risk forecasting
Logistics
BI solutions help logistics organizations work out cost-effective delivery routes, minimize delivery costs, improve their operational capacity planning, and maximize on-time deliveries.
- Fleet operations monitoring, including shipping time, loading time, and transportation costs
- Distribution schedules and route planning
- Carrier performance analysis
- Vehicle condition analysis
- Predictive analytics for vehicle maintenance
- Driver behavior analysis
- Fuel consumption monitoring and analysis
- Delivery delays and failures analysis
- Defining optimal delivery time, speed, and transportation mode
Education
BI solutions for educational organizations help improve the institution’s operational workflows, reduce management complexity, and foster data-driven decision-making.
- Students’ performance monitoring and evaluation
- Student intelligence, including course attendants, interests, GPA, teachers’ feedback, etc.
- Students’ retention analysis
- Expenses and revenue analytics
- Workforce planning and scheduling
- Marketing campaigns effectiveness evaluation
Agriculture
BI solutions for agricultural companies are used to optimize production, reduce waste, and cut costs.
- Plant and livestock wellness monitoring and evaluation
- Soil and yield analysis
- Waste identification and analysis
- Recalls tracking and analysis
- Crop performance analysis
- Demand forecasting
- Production planning and forecasting
- Financial performance monitoring
- Farm machinery and equipment performance analysis
- Sustainability initiatives impact and performance analysis
- Food safety and security evaluation
- Weather tracking and forecasting
Need help with implementing an industry-specific enterprise BI solution?
Essential integrations for enterprise BI
The efficiency of enterprise BI solutions depends on the quality and quantity of data they process. Therefore, integrating BI systems with the sources of data most essential to the company’s business processes speeds up the analytical process and provides more relevant and accurate insights as a result. By accessing real-time and historical data from multiple types of enterprise systems, BI solutions can help users make more data-based decisions in different areas of their business.
Enterprise BI
CRM
ERP
HRM
Supply chain management
Finance & accounting
Ecommerce platforms
CRM
- Customer behavior monitoring and modeling
- Customer satisfaction analysis
- Customer churn prediction
- Customer value analytics
- Analysis of marketing campaigns profitability
ERP
- Business process monitoring and evaluation
- Cause-effect analysis and bottleneck recognitionÂ
- Operational performance analysis, including driver analysis and gap analysis
- Operational performance forecasting
HRM
- Employee performance monitoring and evaluationÂ
- Employee satisfaction, engagement, and productivity analysis
- Employee turnover predictionÂ
- Employee retention analysis
- Workforce planning and scheduling
Supply chain management
- Procurement analytics
- Supplier performance analysis
- Demand forecasting
- Identification of optimal inventory levelsÂ
- Prediction of order fulfillment ratesÂ
- Supply chain risk analytics
Finance & accounting
- Financial performance monitoring and evaluation
- Profitability analysis
- Financial planning and budgeting
- Financial risk forecasting
Ecommerce platforms
- Sales performance analysis
- Customer behavior analytics
- Evaluation of marketing campaigns effectivenessÂ
- Customer churn analytics and forecasting
- Market trends analysis
Enterprise BI implementation roadmap
Enterprise BI solution providers usually go through the following steps while implementing enterprise BI platforms and tailoring them to the particular organization’s business operations:
1
Business needs analysis
2
Business & technology environment evaluation
3
Conceptualization
4
Architecture design
5
Deployment environment & tech stack selection
6
Project planning
7
Components development & delivery
8
QA & end-user training
9
Launch
Enterprise BI: adoption best practices
Balance agility & data governance
On the one hand, enterprise business intelligence drives data democratization at all corporate levels and facilitates data-driven cultural expansion, especially when paired with self-service capabilities. On the other hand, if not managed properly by a solid data governance framework, the solution’s validity can be compromised by sensitive data exposure, lack of trust in data, and data inconsistency.
Open architecture
When implementing a BI solution for an enterprise, make sure it scales easily without performance bottlenecks and a sharp increase in spending. Enterprise BI architecture should allow for a seamless integration with new data sources, the addition of new data repositories (a data lake and/or an operational data store, and data marts), and an increase in the number of users and analytics complexity.
Focus on end-users
The success of enterprise BI implementation depends on user adoption rates. To increase user adoption, introduce self-service BI capabilities, conduct tailored user trainings and workshops on a regular basis, track user activity to spot problems early on, and ensure data quality from the very beginning to foster trust in the new software.
_0.webp)
Enterprise BI cost factors
The cost of implementing an enterprise business intelligence solution varies across companies due to a number of factors, which include:
- Data sources - their number, attributes and integration flexibility
- Data complexity – data structure (structured, unstructured, semi-structured), variety, and volume
- Data cleansing complexity - is defined by the amount of corrupt, duplicate or inconsistent dataÂ
- Data storage requirements – if analytics data stored are to be complemented with a data lake or an ODS
- Data analytics complexity – if real-time, self-service, or augmented analytics is requiredÂ
- Data reporting complexity – number of reports and dashboards, their complexity and frequency, custom data visualization, and self-service capabilities
- Data security complexity - compliance requirements, complexity of access management and controls, and data backups
Enterprise BI implementation challenges
Implementing BI platforms often comes with a set of challenges. Explore the most common obstacles adopters of BI platforms run into and some effective strategies to overcome them.
Most companies have a high volume of aggregated historical data that needs to be integrated with a new BI solution.
Most companies have a high volume of aggregated historical data that needs to be integrated with a new BI solution.
Use ETL tools and data integration platforms to automate data ingestion and transformation. This way, you’ll be able to efficiently integrate your historical data into the new software and gain valuable insights from your company’s past performance.
Some companies, especially in the financial or healthcare fields, handle highly sensitive data. Loading it into additional systems can pose security risks.
Some companies, especially in the financial or healthcare fields, handle highly sensitive data. Loading it into additional systems can pose security risks.
In addition to common security measures (e.g., data encryption, access controls, and regular security audits), implement specialized security measures like data masking into your BI solution. It’s also essential to have an emergency security incident response plan ready when working with highly sensitive data.
Some decision-makers report that their business analytics tools don’t drive the required ROI.
Some decision-makers report that their business analytics tools don’t drive the required ROI.
Define clear business goals and KPIs to align the usage of BI tools with them. Identify the areas where your software does not meet the KPIs. Based on the results, you might need to provide additional training to your personnel, adjust your data collection and governance protocols to improve the quality or volume of analyzed data, or upgrade your BI solution in line with evolving needs.
Enterprise BI services we offer
Consulting
We help companies implement or enhance their existing BI solution by developing business intelligence roadmaps, conceptualizing BI solutions, choosing optimal technology, as well as devising data governance policies and standards.
Implementation
We design and implement multi-component enterprise business intelligence solutions by covering every project step from business needs analysis to BI solution development and launch.
Development
We create full-scale enterprise BI solutions from the ground up as well as develop and deliver separate custom BI components to solve non-trivial BI tasks and meet unique business requirements.
About Itransition
15+ years of experience with business intelligence
25+ years in enterprise software development
40+ successful BI projects
Strategic partnerships with Microsoft, AWS, and Google Cloud
ISO 27001 and ISO 9001-certified to ensure service quality and customer data safety
Insights
Business intelligence architecture: key components, benefits, and BI team
Discover what business intelligence architecture (BI architecture) is and what components and skills are needed to build a high-performing BI solution.
Insights
Self-service BI: use cases, features & platforms to consider
Explore the concept of self-service business intelligence, key software features and benefits, as well as self-service BI challenges and how to overcome them.
Insights
Enterprise data warehousing: architecture, types, best tools, and selection
Learn more about the best enterprise data warehouse solutions, their capabilities, and benefits, and choose the optimal technology for your case.
Insights
Operational business intelligence: essentials, pros, and applications
Let’s discuss operational business intelligence’s tech stack, use cases, benefits, challenges, and differences with traditional BI.
Insights
Building a data warehouse: a step-by-step guide
We overview the process of building a data warehouse (DWH), including architectural approaches, key steps, talents required, software and best practices.
Insights
Cloud business intelligence: the whys and hows
Learn why cloud business intelligence has become an imperative for enterprise success and how businesses can choose the right cloud BI tool for their needs.
Insights
Mobile BI solution: functionality, top 3 tools, benefits, and best practices
Mobile business intelligence is on the rise. Find out how mobile BI works, its key capabilities, best mobile BI platforms, and how it benefits businesses.
Insights
Data warehouse modernization: a how-to guide
Explore the top data warehouse modernization strategies, along with benefits, challenges and tips for addressing them.
More about BI services
Services
Insights