The business intelligence (BI) market continues to grow as more organizations turn to data-driven decision-making. In 2024, the global BI market was valued at around USD 31.98 billion, and it is expected to climb to USD 34.82 billion in 2025. Analysts predict steady growth over the next several years, reaching nearly USD 63.20 billion by 2032, with a compound annual growth rate (CAGR) of 8.9%.
Business Intelligence Definition
Business intelligence is a combination of architectures, technologies, and approaches that transform raw data into actionable insights, informing tactical and informed business decisions.
It is a technology-oriented procedure used by businesses to drive relevant information by analyzing data, helping managers and other professionals make operational business decisions.
Business intelligence refers to a set of tools that provide immediate, easy access to actionable insights about a company’s current state, based on available data.
Business Intelligence tools analyze data sets and present analytics results in dashboards, graphs, charts, reports, and maps, providing end users with comprehensive information about the business's condition.
Although 40% of organizations don’t report major issues, business analytics can be tough in some cases.
The BI survey statistics indicated that 12% of companies struggle with poor governance and data quality issues, and 10% of respondents reported insufficient field training.
Why Do Organizations Need BI Consulting Services?
To achieve consistent growth and remain competitive in the market, organizations require BI consulting services.
Here are the reasons that demonstrate the need for Business intelligence consulting services:
a) Address their weakness
b) Monitor marketing
c) Better visibility into different business functions
d) Strategic thinking
e) Value addition
What are the 5 Stages of Business Intelligence?
Business Intelligence includes the following five different stages:
Data Collection: This stage involves improving decision-making by collecting past and present data.
Data Storage: Data storage involves storing data effectively for future use, i.e., reporting and analysis.
Data Analysis: In this stage, both quantitative and qualitative approaches are employed to analyze the data, uncovering trends and patterns that provide valuable insights for the future.
Situation Awareness: The objective of this technology-oriented process is to provide company users with knowledge that supports situational awareness.
This stage involves generating corporate reports and presentations and sharing them with decision-makers to provide insights into what’s happening inside and outside the organization.
This information helps understand upcoming market trends and government regulations.
Offering data access: Enables the end user to conduct analysis and view outcomes through numerous dashboards and reporting tools.
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What is the Main Role of Business Intelligence?
Modern business intelligence is an integration of data analytics and business analytics, utilizing both as needed, but not exclusively.
With next-generation Business Intelligence, users can conclude data analysis. Using predictive analytics and advanced statistics, data scientists look into data to identify and predict patterns related to the future.
Let’s take a deeper look at how BI helps businesses streamline their processes:
More accurate data leads to better decisions. Perfectness leads to better business forecasting.
Proper planning and analysis can enhance the process, focus on business operations, and facilitate data-driven decision-making.
Advancements in sales forecasting help organizations with marketing and budgeting. In short, more accurate sales forecasting means better budget planning for the organization.
Advancements in pricing for the marketplace and product offerings can drive more sales and increase revenue.
Using BI, employees can understand key performance indicators (KPIs). Knowledge of KPIs via dashboards and reports helps employees focus more on achieving their goals.
What is the Importance of Business Intelligence in Big Data?
The term “Big Data” has become a hot topic now. Data professionals simplify it by using the V3 model, which stands for Volume, Value, Variety, and Velocity.
Big data is defined by these four “Vs”. Volume, which people usually assume is the critical defining feature, is continuously changing and not easy to retain for a long time.
Both Big Data and BI are different, but they have a few common goals. The objective of both BI and big data is to help analyze data to obtain valuable insights and view relevant data.
How Business Intelligence Works?
Business intelligence brings together data from multiple sources into a single platform. Details, including marketing analytics, financial reports, customer surveys, sales performance, and other relevant data, are gathered and compiled into a single view.
This process has three actions: Extract, Transform, and Load.
The “Extract” and “Transform” processes involve finding and gathering data from suitable sources, while the “Load” process involves uploading the data.
Once such data has been gathered into one unified data store, companies can create reports for their users.
Let’s dig deeper into an example that describes how businesses benefit from business intelligence services:
If your company starts losing customers due to lower-quality customer service, it might be because they’re unhappy with their experience when purchasing products or services online or in-store.
In this scenario, BI tools would provide management with evidence in the form of statistics showing the percentage of people who complained about particular issues in every transaction over a specified period, allowing them to identify the root cause of their unhappiness.
It is just a data-oriented process. Soon after collecting data from several sources, you can use algorithms and statistical models to discover insights into what does not work and what does.
Let’s illustrate another scenario. Examining sales data associated with you, you may notice that users who make purchases after visiting your site tend to spend more than those who make purchases in-store.
This could enable the development of new products or the creation of targeted advertising options for online shoppers.
Furthermore, business intelligence and data analytics services complement crucial tools such as Tableau, Azure Synapse, Power BI, and Google Cloud.
What are the Key Features of Business Intelligence?
Here are 10 features of business intelligence solutions:
Reporting:
This technology enables you to automatically schedule custom reports, ensuring they’re sent to clients on time.
Adding excellent machine-readable style reports will help you explore data using pivots, rows, resizing columns, and filters.
Advanced Analytics:
You can analyze the link between independent and dependent variables through the regression analysis option provided by this feature.
Also, you can use modern relational OLAP to explore data from a wide variety of sources.
You can effortlessly compare business performance across customer segments, geographies, time, and product groups.
Relying on self-service BI tools in advanced analytics makes the process human-friendly and accessible.
Data Visualization:
Visualizing data through charts and structural elements enables companies to examine their operations from various angles.
Simultaneously, BI provides numerous graphical cues to convey key facts, statistics, and trends.
Location Intelligence:
Location intelligence maps and visualizes data geographically.
The real-time overview and customer geographic location provided by this feature can act as a powerful weapon for businesses.
BI users can leverage location intelligence to understand trends and patterns in consumer behavior and make faster decisions in sales and marketing.
Customized alerts:
By default, BI software has an in-built automated alert feature.
Based on the client’s request, customized alerts can be set to schedule emails to management and employees regarding different reports on a daily, weekly, or monthly basis.
Data Management:
This process has several steps, including developing, blending, examining, and cleansing data for investigation.
Inspect data to uncover characteristics, trends, and views while indicating them using tools like Power BI, Tableau, and Qlik Sense.
Self-service Analytics:
Making informed business decisions requires access to relevant data; a business intelligence solution must offer self-service analytics that enable users to access this data effortlessly and receive meaningful explanations to get started.
Integration with different systems:
To analyze and share data at the business level, a BI solution must be integrated with various systems.
Predictive Analytics:
In the dynamic world of business, you need to be competent enough to make error-free predictions.
Firms utilize predictive analytics to identify and capitalize on patterns in data, thereby detecting opportunities and threats.
Mobile business intelligence:
All companies work with vast quantities of data. In this competitive world, everyone wants to have access to and control over real-time data to make decisions.
Many companies have adopted mobile applications and SaaS applications for primary business operations.
No matter whether you’re the president, an owner, or a member of any team, mobile business intelligence provides you with a chance to enhance productivity and decision-making.
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Types of Decisions Supported by Business Intelligence
Different kinds of decisions supported by Business Intelligence include:
- Tactical Decisions
- Strategic Decisions
- Operational Decisions
- Financial Decisions
- Risk Management Decisions
- Competitive Decisions
Tactical Decisions: Organizations are making decisions to focus on day-to-day operations and improve efficiency.
Managers are using BI to analyze real-time data to streamline workflows, allocate resources, and optimize processes.
These decisions will lead to departmental reorganization, proper work schedules, and improved profitability.
These are medium-term decisions that are less complex and made by mid-level managers.
Strategic Decisions: Business decisions at a higher level are considered strategic and are usually less frequent, made by the business’s executives.
Several types of strategic decisions involve hiring additional staff, acquiring a company, or targeting a specific market.
Significant expenditure is required to make decisions at this level. Moreover, they are usually non-repetitive and can be taken only after thorough analysis.
These are long-term decisions made by higher-level managers.
Operational Decisions: Operational or structural decisions are typically made daily or hourly by junior-level managers.
They are related to day-to-day operations and have a limited impact on the company.
Examples of operational decisions include answering sales-related questions, calculating an employee's performance bonus, and approving a business quotation.
Financial Decisions: Businesses use BI to obtain up-to-date, accurate financial analytics.
Financial managers use this technology to track major KPIs, monitor expenses and revenues, predict financial outcomes related to the future, and discover cost-saving opportunities.
This, in turn, leads to informed budgeting and financial planning, as well as investment decisions and economic stability.
Risk Management: Business intelligence is used by organizations to inform risk management decisions by analyzing past data and identifying potential risks and threats.
By monitoring key risk indicators, companies can proactively minimize risks, comply with regulations, and maintain operational continuity.
Competitive Decisions: These involve collecting vast amounts of data on competitors to develop effective strategies that beat the competition.
Furthermore, it doesn’t involve obtaining information through unethical means.
Applications of Business Intelligence
Sales Intelligence: The sales department of every business focuses more on customer negotiation skills.
Sometimes it’s tough to convince potential clients to buy a product or service. This process has become more predictable and smoother through the use of business intelligence and analytics consulting services.
Initially, BI collects data on various KPIs, such as sales metrics, customer demographics, conversions, and more.
Later, this data is well-organized into structured visualizations, such as scattergrams, graphs, and pie charts.
Both the sales and marketing teams can implement BI to identify trends in customer interests, enabling the company to increase sales by targeting its ideal client base.
This shifts their focus to converting targeted leads and improving both conversion rates and overall profit margins.
Visualization: Business intelligence software utilizes various data analytics tools to comprehend and manage data pertinent to business operations.
Organizations present this data in visual formats to monitor sales, productivity, and logistics.
Some business intelligence platforms offer custom reporting capabilities that enable end users to define their own parameters.
Whereas others will provide ready-made reporting templates with built-in standard metrics.
Reporting: The activity of organizing data into a synopsis to track overall business performance.
It translates data into simple, plain language, providing a clear understanding of what’s happening.
Performance Management: Companies can utilize BI applications to track progress toward goals using customizable or preset timeframes.
Target delivery times, project deadlines, and sales goals fall under data-driven goals.
Users can track the progress toward their goal and use this information to evaluate the company's overall productivity.
What are the Advantages of Business Intelligence?
Here are the different advantages of BI:
Fast and Accurate Reporting:
Employees utilize business intelligence to measure key KPIs using customized templates, producing real-time reports and delivering the latest, most relevant information to help businesses respond promptly and enhance reporting accuracy.
Increased collaboration:
The centralized platform provided by BI tools enables teams to access and share information, collaborate on analysis, and generate actionable items.
It enhances cross-functional collaboration by breaking down silos within the company.
Better ROI:
Both CX and sales efficiency can be improved by the built-in CRM feature present in the business intelligence system.
This leads to smoother handling of both current and after-sales services. Business intelligence enables organizations to eliminate underperforming products, optimize their marketing approaches, and increase ROI.
Minimized risks:
Companies use it to make data-driven decisions, reduce guesswork in business decisions, and allocate resources effectively.
It becomes very easy to inspect both the success ratio and the performance of different programs. That helps tackle various organizational challenges before they arise.
Enhanced productivity:
Business intelligence helps companies automate day-to-day tasks, categorize processes without human effort, refine processes, and enhance productivity and CX.
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Business Intelligence Examples
Let’s take a look at some real-world examples of business intelligence from leading international brands that use these tools:
Netflix: Everyone is familiar with the OTT platform Netflix, which uses both data science and business intelligence to acquire fresh subscribers and enhance the user experience.
Business intelligence solutions produce customized watch lists and delightful artwork while convincing subscribers to watch their preferred genres.
It uses recommendation systems to promote content to the right audience at the right time.
Starbucks: Starbucks uses BI to analyze data based on traffic patterns, population density, customer demographics, average income levels, and public transport centers.
By providing the best deals and loyalty card programs, it tracks individual purchase information through a mobile app.
This information will be used later to predict purchases and send customized offers through email or apps to encourage customers and improve sales.
Tesla is a reputable automotive company that utilizes BI to wirelessly connect its vehicles to corporate offices, allowing for data collection.
Later, that data can be analyzed to prevent issues such as traffic hazards and equipment damage.
This technology helps this automotive giant increase user satisfaction and inform decisions about upcoming upgrades.
Uber: This is a transportation company based in California that tracks traffic conditions, journey times and durations, driver availability, and customer demand using business intelligence.
It utilizes a rating system and surge pricing in its business model to regulate fares and foster trust between customers and drivers.
Walmart: Based on client purchases, it uses business intelligence to measure in-store and online client behavior.
They can use it to make smarter decisions around varieties, resources, promotions, merchandising, and inventory to generate traffic.
Business Intelligence vs. Business Analytics
Both processes use data to enhance business, but let’s explore further to understand the differences between business analytics and business intelligence:
The focus of business intelligence is on descriptive analytics
Business intelligence places a greater emphasis on descriptive analytics, which involves summarizing past and current data to show what has occurred or is currently happening.
BI provides the “what” and “how” answers so you can duplicate what works and modify what doesn't.
The focus of business analytics is on predictive analytics
Business analytics places greater emphasis on predictive analytics, which uses modeling, ML, and data mining to predict future outcomes.
Business analytics provides a solution to the “why” to better predict upcoming events.
Business intelligence is less expensive than Business Analytics
Many parameters are used to conduct data visualization and growth analysis. Business analytics prioritizes past and current data and analyzes customer needs.
The report does not merely provide a synopsis of its findings.
Business Analytics has a much broader perspective
Business intelligence relies more on data collection, whereas Business analytics focuses on delivering immediate results.
Business analytics is necessary and mandatory for developing a strategy and for reprogramming a company’s future operations to achieve profitability.
Business intelligence aims to adopt and translate received data into valuable insights. Business analytics is future-driven, as it helps understand future challenges.
Reporting vs. Applying
BI is simpler and organizes data into reports that are easy to understand, informing viewers of what is happening.
BI outcomes, charts, simple-to-understand reports, and interactive dashboards are frequently used.
Business Analytics takes it a step further, explaining why things occur by utilizing both statistical analysis and data applications.
Structured vs. Semi-structured data
Business intelligence applications are better suited to structured data from business applications, such as financial software systems and ERP systems.
It helps generate insights from previous financial transactions.
Business analytics applications are better suited for semi-structured and unstructured data, converting them into valuable data before analysis, and later providing insights from that data through in-depth predictive analytics.
Disadvantages of Self-Service BI
Incorrect analytics outcomes:
As a result of incomplete data sets or data issues that go unaddressed, self-service queries might yield incorrect results.
When numerous users work with different versions of the same data and organize it for analysis in various ways, there is a risk of irregularity. These challenges can result in ineffective decision-making.
Issues related to privacy, ethics, and data security:
When reliable data security measures and effective information governance are not aligned, the increased data accessibility enabled by self-service BI may raise concerns.
Unauthorized individuals may gain access to confidential data, violating data privacy laws and ethical business standards.
Deployments without supervision:
Self-service BI settings may become disorganized when there is no centralized monitoring and supervision by the BI team.
Irregular data silos, disparate BI tools, and rising costs can hinder the productivity and efficiency of extending self-service capabilities when business divisions implement BI systems independently.
Business Intelligence Trends
Connected Cloud:
Many companies' working approach has changed after the COVID-19 pandemic. During this period, many companies started changing their current BI strategies.
Organizations realigned their expenses to accommodate the transition to Cloud BI and analytics platforms, as on-premises solutions were unable to overcome the challenges of a largely remote workforce.
According to Gartner’s reports, 40% of all enterprise workloads have already been transferred to the cloud. Organizations are now slowly implementing data solutions after realizing the importance of analytics.
Leading industry brands, such as SAP, Amazon Web Services, and Oracle, offer industry-oriented BI solutions with ready-to-use automation and personalization.
You don’t need to build workflows from the start; personalization gives you more control over how the application functions and appears.
Artificial Intelligence:
In 2025, companies will progressively integrate both AI and BI to obtain detailed insights and make intelligent decisions.
The integration of these two technologies will enable them to discover and automate IT operations more efficiently, while maintaining high levels of agility and scalability, thereby analyzing extensive datasets with reduced human involvement.
These capabilities can make the data analysis process error-free and faster, while minimizing the stress on individuals.
Predictive and Real-time Analytics:
In the upcoming year, companies will combine real-time and predictive analytics to inspect data.
This two-tiered strategy will enable companies to address unwarranted threats promptly and adjust their responses in real-time based on evolving circumstances.
This will enable them to optimize their current processes and drive innovation by gaining deeper insights, adopting more effective procedures, and identifying new opportunities for organizational growth.
Augmented Analytics:
Combining AI and ML makes it easier for companies to let non-technical employees understand the importance of business intelligence.
With the help of augmented analytics, the entire team can quickly build powerful data analytics models and gain useful insights.
One of the key features of any platform for business intelligence is data analytics, which has become more accessible by asking relevant questions and providing contextual feedback to generate related insights.
In 2025, it will continue to influence organizations by helping them manage the complexity and volume of data through flawless data collection, cleaning, and insight generation.
Natural Language Processing (NLP):
Due to NLP, self-service BI has become a growing trend in data analysis. A few language tools, such as Bard and ChatGPT, have gained popularity for extracting insights from unstructured data.
These language tools could accelerate the extensive development of NLP in analysis.
Developing a platform that responds in major spoken languages requires patience and time, but technology is advancing rapidly.
In 2025, major developments in NLP are expected.
Data Discovery or Visualization:
For a larger audience, visual data discovery provides fresh insights. It will expand over time with rising frequency.
Both employees and companies need to understand the impact of data. In this case, data discovery or visualization is relevant.
Data analytics dashboards increase data transparency and accessibility by analyzing and disclosing sensitive information.
Data Automation:
Automation plays a critical role in large-scale analytics projects, where manual effort yields inaccurate results and wastes time.
In such cases, data-driven decision-makers prefer data automation using BI for many tasks.
The Role of BI in the Present Business Environment
In the present business environment, business intelligence plays a major role in many key areas, including:
Faster decision-making:
At the organizational level, BI establishes business goals. The tools offered by BI examine and validate raw data to help in better decision-making.
Consider an example: a retail firm leverages BI and analytics to predict product purchases and offer customized solutions to its customers via email.
This approach encourages customers to return to their site repeatedly, resulting in increased revenue.
Goal and ROI Enhancement:
For instance, operations reporting is automated by a consolidated business intelligence implementation and solution.
It enables the marketing team to generate tailored marketing campaigns for specific regions. They can respond to consumer behavior and improve marketing efforts by tracking and monitoring real-time data.
Improved Productivity:
It is possible to increase labor productivity by consolidating business information. The significant advantage of business intelligence analytics tools and management is the automated creation of reports and real-time updating.
Therefore, the employees may concentrate on more productive tasks.
Sales and Market Intelligence:
Both sales and marketing teams use Customer Relationship Management (CRM) software to monitor their customers.
As they include customer interactions and contacts, enormous amounts of data can be assessed for strategic efforts.
Businesses can leverage business intelligence systems to conduct sales-loss/win analysis, identify new clients, manage and monitor existing clients, and provide post-sales support.
Planning the Business for a Brighter Future:
Investing in experienced business intelligence consultants enables firms to enhance their ability to predict market trends and implement corporate-level changes, thereby staying competitive.
How can Business Intelligence Enable Better Conversions in Digital Marketing?
Target Demographics:
Business intelligence for marketing enables businesses to organize information across multiple channels, empowering them to create effective marketing action plans.
Marketers utilize this technology to collect customer data from multiple sources and present it in a dashboard view, including their purchasing habits, demographics, preferred products, and areas of pain.
Marketers will review this information thoroughly and begin sending campaigns to their niche audiences through the relevant channels to drive results.
Optimize the company website for more conversions:
Firms are utilizing business intelligence for CRO (conversion rate optimization) by periodically updating their sites to attract more visitors who subscribe to newsletters, make purchases, and so on.
By using marketing business intelligence tools, firms can gain valuable insights into the journey of visitors who converted.
Customer journey analysis:
Business intelligence tools offer marketers a comprehensive view of the customer journey.
These tools ensure marketers have a clear understanding of the factors that drive conversions and address pain points throughout the client lifecycle.
A/B testing:
Business intelligence enables A/B testing and optimization by providing statistical analysis and insights to determine the winning variation.
By testing various versions of ads, email content, and landing pages, marketers can track the performance of changes and identify the elements that drive more conversions.
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How can Business Intelligence help in eCommerce Reporting?
Listed below are some crucial reports that business intelligence tools can provide to help eCommerce companies understand their business and attract the right prospects:
Inventory Reports:
For the success of e-commerce businesses, inventory management is key.
eCommerce business intelligence tools can track real-time inventory data, minimize stockouts, ensure maximum stock levels, and reduce holding costs.
By combining sales and inventory data, eCommerce companies can identify high-selling products, predict demand, and make informed supply chain decisions.
Sales and Revenue Reports:
When it comes to sales, data collection is top of mind. Business intelligence in eCommerce helps track the overall performance of all sales professionals.
This involves the number of leads generated and the total number of qualified leads each sales team member converts.
Moreover, business intelligence reporting involves a clear understanding of the origin of leads and the month with the highest sales.
Marketing Reports:
In e-commerce, business intelligence is utilized for business planning, forecasting, and data visualization. Marketing is essential for the success and development of e-commerce companies.
Therefore, marketing strategies such as SEO and PPC can generate sufficient data for analysis and evaluation. Hence, BI helps companies centralize data, enabling it to be leveraged effectively.
Customer Data Reports:
eCommerce companies take full advantage of business intelligence and analytics services to monitor their customers' touchpoints.
These reports involve a 360-degree view of clients’ behavior across various levels, along with the tasks carried out by resellers and distributors.
E-commerce firms can improve profitability by leveraging insights from this customer intelligence tool, which tracks which products were searched for by which users, which users ordered specific products, and more.
Conclusion:
Business intelligence is the ideal solution for organizations to collect data from numerous sources. They can choose from multiple options to perform this. Still, the most effective method is to utilize tools that enable them to visualize data, allowing their decision-makers to make better, more informed decisions.
If you are in search of a reliable BI services company, you are in the correct location.
Express Analytics is a trusted organization that helps you maximize profits and productivity through data-driven insights.
References:
The Role of Business Intelligence: What it is and Why it Matters
Why is Business Intelligence Important for Your Organization?
12 Reasons Why Business Intelligence Is Vital for Your Business