Ultimate Guide to Business Intelligence

© Shutterstock.com | Sergey Nivens

In this article, we explore 1) an introduction to business intelligence, 2) business intelligence essentials, 3) how to implement business intelligence in your business (step-by-step process), and 4) business intelligence tools.


What is business intelligence?

Business Intelligence, or BI, is a process that analyzes and converts raw data into coherent and actionable information for use in business analysis to aid decision-making.

Business Intelligence enhances business performance. If statistics are anything to go by, Business Intelligence has delivered up to a ten-fold increase in ROI. In fact organizations that do use BI, see up to a five-time increase in decision-making speed.

Conversely, lack of adoption of BI has adversely impacted three-quarters of the organizations surveyed. What’s more, stats show that a whopping 99.5% of raw data is left unutilized.

Benefits of Business Intelligence

Business Intelligence is ever-growing in popularity as a performance improvement tool for businesses. That is because Business Intelligence provides a lot of advantages over conventional systems. Business Intelligence:

  • Provides newer insights: Business Intelligence offers a dynamic problem-solving platform that enables users to find answers to random queries. This helps the users comprehend the inner workings of the business and gain newer insights into the mechanism of operation.
  • Enhances sales and negotiations prospects: Business Intelligence provides valuable input to a sales team by making available instant reports on sales trends, new market scenarios, consumer preferences, etc. The reports generated by BI systems are highly accurate and up-to-date.
  • Identifies new opportunities: Business Intelligence provides a comprehensive analysis of a company’s capabilities, its shortcomings, and its position in the market. In this way, it helps the company concentrate on its strengths and recover lost ground in the market, thus bringing itself into an advantageous position with respect to its competitors.
  • Reduces cost of production: BI significantly saves time and reduces labor costs by:
    • Automating the process of data management;
    • Automating and simplifying the report generation process;
    • Reducing costs of training.
  • Enables objective-oriented approach: BI helps organizations in adapting an object-oriented approach by defining and centralizing all Key Performance Indicators (KPIs). BI also helps in setting targets and benchmarks and aligning the company in their direction. Additionally, BI sets priorities for tasks and helps employees in focusing on the most critical processes.
  • Brings discipline to data collection: Disciplined data collection is one of the primary requirements of any organization. BI lays emphasis on focusing on the correct metrics during data collection. BI makes it possible to organize otherwise unmanageable data into controllable streams and to put it into radical uses.


Categories of BI solutions differentiated by the purpose

Business Intelligence can be classified into four categories based on its purpose. They are:

  1. Real-time: Real-time BI is often described with a modifier such as “quasi” or “human”. It provides up-to-date data by directly interacting with operational systems. In this way, Real-time BI facilitates quick decision-making. Real-time BI combines the data warehousing advantages of classical systems with real-time, event-driven strategies of tactical BI.
  2. Tactical: Also known as task-oriented or task-centric BI, tactical BI deals with the current state of affairs. It trains managers to observe changes in the current business environment and discover new opportunities as they arrive. Tactical BI is action-oriented and not plan-oriented. It helps decide the action steps necessary to achieve the company’s objectives. Tactical BI warrants optimum utilization of available resources and keeps the company battle-ready to deal with risk situations. Tactical BI tools clean data and improve its quality. They are highly updatable and future-compatible.
  3. Investigative: Investigative BI or exploratory BI makes use of dashboards. It is an open-ended system where the primary goal is to investigate or explore data for clues, like patterns and irregularities. These clues are then used to formulate queries or establish correlations, giving rise to a hypothesis. Subsequent investigations make it possible to improve the queries and strengthen correlations.
  4. Traditional: Traditional BI is traditionally based on KPI dashboards. It primarily deals with historical data. This historical data is stored centrally and is readily available at hand to aid in decision-making and getting better outcomes. Over the period of several decades, this data becomes highly standardized and mature. However, since this type of data only provides an insight into the past and is not forward-looking, there is a high risk of new arbitrary opportunities being overlooked. Thus, this type of BI system is not effective in a scenario where the future is unpredictable or difficult to anticipate and deviates from historical patterns.

Types of Business Intelligence Solutions

There are several types of BI solutions and tools. They are:

  • Spreadsheets: Spreadsheets are a form of visual and interactive data organization and management interface in tabular form. Examples such as MS Excel enable users to store alphanumeric data in cells and apply standard formulae to them for calculations. Spreadsheets are very easy to use and most of them allow additional features like graphs and charts, pivot tables and macros.
  • Reporting Software: Reporting software accumulates and manages data and creates easily-readable reports based on the data. A wide range of free and commercial reporting software is available.
  • Online analytical processing (OLAP): OLAP helps solve multi-dimensional queries effectively and quickly. Apart from business reporting, OLAP is used for the purposes of marketing, sales, budget-making, planning and forecasting.
  • Data mining: Data mining is the process of determining patterns in large groups of data. It helps users in finding relevant information in a large pool of data without having to waste time in browsing through unwanted information.
  • Data warehousing: A data warehouse is a data reporting and analysis tool that stores both current and historical data. The data is sourced from various operational systems.
  • Process mining: Process mining is a kind of management solution that uses event logs to evaluate business processes. These event logs are typically documented by an information system.
  • Digital dashboards: A digital dashboard is a simple, easy to interpret digital interface that provides a graphical representation of data. Typically, digital dashboards come in the form of web pages, linked to an information database.
  • Decision engineering: Decision engineering is an arrangement that utilizes the benefits of an array of best practices to aid in business decision-making. In this arrangement, the decisions are represented by a visual decision language.
  • Customer intelligence: Customer intelligence is the process of collecting customer details such as preferences, needs, and behaviors so as to better understand customers and forge stronger business relationships.
  • Business performance management: Business performance management is a set of analytical tools that helps businesses reach their short and long-term goals by managing company performance.


Implementing Business Intelligence in your business involves a series of successive steps. These steps should help BI bring in the following advantages to your business:

  • Help in better decision-making
  • Increase operational efficiency of the organization
  • Give the business a competitive edge over its rivals
  • Increase turnover and profits
  • Enhance quality of customer service

The steps are described below.

Step 1: Defining the Objective and Purpose of BI in Your Business

Analyzing BI systems will reveal various perspectives. It is vital to the success of the organization that Business Intelligence is in sync with the overall philosophy of the organization. Since BI plays a dominant role in decision-making, it should be implemented in such a way that it helps to determine the objectives of the organization and accurately realize them.

BI should serve the following purposes in your business:

  • Collect and consolidate raw data: Raw data is data that is obtained from a source, and that has not been processed. It is also known as primary data.
  • Analyze data and report information: During data analysis, raw data is examined, cleaned, processed and transformed into information.
  • Drill information to gather knowledge: Information is processed to obtain knowledge. This knowledge forms the basis of decisions.
  • Convert knowledge into decisions: The knowledge gathered by processing information is used in decision-making. Decision-making involves the selection of a course of action from several alternatives.

Step 2: Identification and Preparation of Source Data

Source data or atomic data is nothing but raw data that has not yet been processed to derive information. Source data is extracted, processed and organized into information. Processed source data is usually stored in a database.

Identifying End User Requirements

In any organization, there are different units with different responsibility areas. The end users in each of these units or departments perform various functions. So, it is very important to understand how these end users will analyze and interpret this data.

The correct approach to identifying end user requirements is to extensively interview the end users. Interviews will help collect data, like how much information the end user possesses, what additional information he needs to be provided with and what format would be most suitable for him to receive the information in.

We have identified some of the specific requirements of different end users below.

  • Board of Directors: The board of directors requires information on areas such as competitive analysis, trend analysis, Key Performance Indicator tracking and exception reporting.
  • Administrative Planning and Analysis: This unit is concerned with information pertaining to assessment of investments made and acquisitions undertaken, long-term planning, reorganization, allocation of company resources, and general planning in important areas like human resources and production capacity.
  • Finance Department: The requirements of the finance department are based on budgeting, consolidation, capital management, variance analysis, financial modeling and modeling assets and liabilities.
  • Sales and Marketing Department: The sales and marketing department is the one closest to the customers, so its requirements have to do mostly with customer profiling, profitability, distributions and overall sales performance.

Identifying Data Sources

Once the requirements of the end users are established, it becomes important to find solutions to those requirements. This can be done by identifying data sources. Often times, the data is found in the company databases. However, in certain cases, the required data isn’t available in the databases. In such instances, the data can either be sourced from outside, or if that is not feasible, then a request is made to the concerned end users to modify their requirements.

Step 3: Designing the Data Model

A data model is designed to cater to the requirements of the end users, so it should be competent enough to assess the needs and expectations of its end users. Also, the data model must be designed in such a way that the end user is able to identify with the business terminologies used in the model.

While designing the data model, the emphasis should be on capturing all possible relationships within the data model – it is a strenuous and time-consuming task no doubt, but it has to be done.

A well-designed data model takes into account all the errors and discrepancies and enables users to make changes before the model is implemented.

There are various approaches to data model design. They are:

  • Conceptual Data Modeling: This approach identifies the high-level relationships between various entities.
  • Enterprise Data Modeling: This approach concentrates on the unique requirements of a particular business process.
  • Logical Data Modeling: This approach helps in the creation of a physical data model by exemplifying the entities, traits and relationships pertaining to a particular business function.
  • Physical Data Modeling: A physical data model creates a physical and database-specific model, based on a logical model.

Step 4: Selecting BI Tools

Selecting appropriate Business Intelligence tools is one of the most important steps in BI implementation. Only with the right set of tools will it be possible for a business to correctly measure and manage their goals and take steps to handle exceptions whenever they arise.

In smaller entities with a simple data flow, spreadsheets are generally adequate in providing a feasible solution. However, in the case of larger companies, many more services and products are offered and as such, the data flow is much too complex to be managed by a spreadsheet. In such cases, specialized BI tools are necessary. These BI tools are function-specific, that is, they cater to the requirements of specific departments.

Conversely, certain BI tools like data warehousing take on a more generalized approach. These tools can be modified to suit the requirements of individual departments. Certain ERP and CRM solutions providers offer pre-integrated BI solutions that help to reduce deployment time.

These days, a lot of solutions are offered specifically for small and medium businesses. Many of these are either free or offer free trials.

Step 5: Designing and Implementing BI

Designing and implementing Business Intelligence systems is an extensive process. The primary requirement in developing such systems is for organizations to be able to work with IT and information in general.

Here are some important steps to follow while building a BI system:

  • Extensive research should be carried out to correctly asses the organization’s requirements. While assessing requirements, it is extremely important to consider future requirements alongside current requirements.
  • It is mandatory to involve end users in both the design and implementation phases. It is equally important to involve departments such as IT and Knowledge Management in these phases.
  • It is important to select data sources at this stage. Once data sources are identified, data models can be built, and data stores created.
  • Data should be processed to make information accessible to clients.
  • Information sharing is one of the primary components of any BI model. Information sharing takes care of all exchanges of data within the system via various protocols.
  • Analytical capability is of great importance to the success of a BI model. Analysis should be correctly interpreted and should be properly integrated within the management system.
  • Along with delivering the BI model, it is mandatory to grant access rights to all concerned departments and individuals.

Step 6: Discovering and Exploring New Informational Needs and Business Applications and Practices

Designing a BI model is a continuous learning process. As the information is analyzed, newer learning and insight is gained. As newer informational needs are discovered and explored, newer methods of information management have to be devised.

At this stage, cyclic methodologies and procedures such as iterative designing and Rapid Application Development (RAD) come into play. These tools help in creating a prototype of a BI environment, based on which a new, refined BI application can be created.

Of course, this discovery and exploration phase calls for full assistance and cooperation from all concerned departments, including IT and Knowledge Management.

Implementing Business Intelligence models into your organization has certain pre-conditions. They are:

  • Efforts should be made to ensure that the data is accurate and workable.
  • A lot of effort has to be put to train end users and all individuals concerned on using the BI system effectively.
  • Reports can never be perfected at one go. So rather than allocating a lot of time to developing the perfect BI model, it is better to deploy a workable system as quickly as possible and then adjust and make changes and corrections along the way.
  • The primary focus before building the BI system is to calculate returns on investment. For all intents and purposes, the BI model has to be in touch with reality.


There are thousands of effective Business Intelligence tools available on the market. We will discuss some of the most popular ones.

  • Microsoft Excel: Microsoft Excel is the most popular BI tool. Essentially a simple spreadsheet, Excel has numerous integrated features like mathematical formulae, pivot tables, visual charts and conditional formatting. What’s more, Excel spreadsheets are highly compatible with most personal computers, smartphones, and tablets. Also, Excel is relatively inexpensive.
  • OLAP Tools: OLAP tools are used by advanced users. They are basically used when the need arises to analyze data in more than one dimension.
  • Yellowfin BI: Yellowfin BI is a Business Intelligence tool that is increasingly finding acceptance for its easy data handling features. It allows easy accessibility to dashboards and has high compatibility across platforms.
  • SAP BI: SAP BI is another popular BI tool. It provides a detailed picture of your organization by offering visualizations and integrating applications and reporting tools into a single package.
  • Oracle Hyperion: Oracle Hyperion is a versatile BI tool. It allows the storage of data either locally or in clouds and is compatible with various other Oracle tools. An effective BI system, Oracle Hyperion is appreciated for its ability to significantly reduce planning and forecasting times.
  • Pentaho: Pentaho is an open-source BI system that enables faster decision making, which in turn, translates into increased profits. Pentaho allows the integration of analytics into the company’s applications. Dashboards are web-based and allow good visualization.
  • Sisense: Sisense is a highly user-friendly BI tool that requires little prior training to operate. Powerful visualizations are its forte. Sisense allows data integration from several sources, thus guaranteeing very high accuracy. Dashboards can be created and customized easily using this BI system.
  • Jaspersoft: Jaspersoft is a highly popular open-source BI tool that is perfect for visualization, reporting, and analytics. Highly affordable and extremely flexible, Jaspersoft is highly compatible with all applications and mobile devices. It is available on-site and in-cloud.

Comments are closed.