Business intelligence refers to the procedures and devices used to convert raw data into information that can be used in analysis.1 The term was formulated in 1865. It is associated with Richard Millar Devens. The scholar used the phrase to describe Sir Henry Furnese’s deeds. Henry was a banker who had made huge profits in his career. The gains were made by collecting and utilising information ahead of his competitors. It is noted that BI technologies have various capabilities.
For example, they can support outsized sums of unstructured data. As a result, they create a platform for discovery and development of new business opportunities. Identification of new prospects is very advantageous to companies operating in today’s competitive global market. The reason behind this is because it helps the firms gain a competitive advantage over its rivals. In addition, it ensures long term stability.
In today’s era, business intelligence is believed to have developed from the Decision Support Systems (DSS) of the 1960s. The evolution was extensively witnessed during the mid 1980s. BI data can incorporate both historical and new information acquired from source systems.2 As a result of this, the application allows for strategic and premeditated decision-making procedures. It is also important to note that business intelligence integrates various sets of data scrutiny applications.
They include ad hoc analysis and querying, cloud, online analytical processing, and enterprise reporting. In addition, it has data visualisation software. It is primarily used by experts to devise charts and info graphics. It is also used to design devices that help in creating BI dashboards and performance scorecards. The boards and cards help to display visualised data on commerce metrics.
In this paper, the author analyses various aspects of business intelligence. To this end, an analysis of the components of BI is provided. In addition, the benefits and limitations of this concept in the context of modern business organisations are analysed. The future of BI is also discussed.
Key Components of Business Intelligence
As already indicated, business intelligence has various components. They include data warehouses, advanced analytics, OLAP techniques, Real-time BI, and data sources.
A data warehouse is a set of information pertaining to a business. The data is organised systematically so that it can be examined to help in proper decision making.3 It is filled with information acquired from various databases. It supports the transmission of information from one point to another. It achieves this by handling the large records of data. In addition, warehouses contain operational data, which can be updated.
The information is used by experts to make informed choices on various aspects that are important to the business.4 Generally, warehouses enable leaders to analyse data and examine interconnected components, which can help a business thrive. Assessing information on sales over a period of several years helps the company to improve its product growth. The key BI component is also used to evaluate statistics and relation of business procedures.
A company manager, for example, can compare distribution times in varying facilities. The reason for such an analysis is to determine the best processes that can be employed to enhance the business.
OLAP (On-Line Analytical Processing)
OLAP refers to the manner in which business experts sort and select amassed data. They achieve this by using complex tools that facilitate the navigation process. The component avails multidimensional and summarised information to the executives.5 The data is often used for analysis, planning, and reporting to enhance optimisation of the business processes.
On-line analytical processing techniques and devices can be used together with data warehouses and marts developed for complex venture intelligence schemes.6 Reporting software provides statistical information, which keep executives updated on the state of their dealings. As a result, the managers can be able adjust their business processes.
There are various sources of data. They include operational catalogues and historical information. Others are external records from such sources as the internet. Generally, this business intelligence component entails different forms of stored information. It is noted that raw data and software applications are used to come up with important information, which managers can use to make the business succeed. BI analysts use data sources to devise tools that allow information to be stored in outsized caches of pie charts or graphs.
Such storage makes it possible for such information to be used for different business purposes.7 For example, executives can use the statistics to develop presentations. On their part, the presentations can aid to set realistic team goals in an organisation. In addition, managers can make proper decisions based entirely on these facts.
The business intelligence component has become extensively popular due to the invention of mobile devices. Use of various software applications allows real time distribution of metrics. The distribution is carried out through such channels as emails, messaging, and digital displays.8 Business experts can advertise special offers to clients by following the current products and market trends. In addition, marketers and executives can track clients globally and sell products by use of websites.
The business intelligence component takes advantage of statistical evaluation systems to provide certainty of facts.9 Entrepreneurs can use the advanced analytics tools to examine client’s response to a number of products. For example, a coffee shop chain can analyse the sales of specific brands and make both local and regional menu adjustments to fit the demand. Through this, the managers can determine the best market for certain products.
Designing and Implementing a Business Intelligence System
When executing business intelligence programs, users are required to pose various questions and make critical decisions. The following are some of the issues to be taken into consideration:
Goal Alignment Queries
The process establishes the short and medium term uses of the software. The company executives analyse the strategic objectives to be met using the BI application. In addition, a hypothesis is made to establish how results will be improved.
Cost and Risk Queries
The financial impact of a new BI program needs to be evaluated. The aim is to determine how the business processes will be affected. The process entails reviewing the cost of current operations and the increment resulting from the use of the BI initiative.10 A financial matrix is then developed.
It is very important for managers to assess competency involved in acquiring business information. Various aspects need to be evaluated. For example, the executives should determine whether or not the company is capable of scrutinising key sources of information. In addition, the question of how information is gathered and stored should be addressed. Furthermore, the executives should examine the statistical parameters of all the information collected.
Clients and Stakeholders Issues
The managers carry out this assessment. They establish the beneficiaries of the new initiative.11 In addition, the program is examined to determine if it is the most suitable to satisfy the needs of all clients, employees, and shareholders.
Metrics Related Queries
Entrepreneurs must choose the best metrics to be used for each data acquired. The process entails proper evaluation to establish which is the most suitable and the reason why.12 In addition, the managers need to determine the number of metrics to be tracked and the system to be used for the procedure.
Results Related Queries
Executives are required to ensure the business intelligence program is well monitored. The reason behind this is to ensure that the desired results are met. In instances where the objectives fail to be achieved, adjustments to the program are made.13 It is also very important for the business intelligence application to be tested for accuracy and consistency.
Types of Companies that use Business Intelligence Systems
Restaurant chains, such as Ruby Tuesday, Hardee’s, and T.G.I Fridays, extensively use business intelligence applications. They use the software to make informed choices on products to add on and remove from their menus. In addition, they make use of BI to renegotiate contracts with their supplies. Due to the extensive utilisation of the software, the chains are among the leading companies who gain real value from the systems.14
Other Business Enterprises
Various professional sports teams have achieved great success due to the use of business analytics. Such teams are Boston Red Sox, New England Patriots, and Oakland A’s. Patriots, for example, managed to win three Super Bowl Titles in a period of four years. The team’s management applied in-depth analytics. The application was used to sign players and manage their salaries.15
The squad members, including the coach, analyse game films and statistics to get familiar with mechanisms that can be used to help the side achieve positive results. Off the pitch, the New England Patriots employ business analytics to evaluate and improve the experience of their supporters during match days. During each home game, a group of about 20 people from the club are tasked with the duty of making quantitative analysis of various services offered. They include food, cleanliness within the stadium, and parking.
Businesses in the retail sector also use this application. A case in point is Wal-Mart. The business utilises outsized data and category evaluation to maintain competitiveness in the market. Most e-commerce outlets use analytics. They include, among others, Amazon and Yahoo. They use test and learn technique to keep up with the changing business trends. For example, Capital One conducts approximately thirty thousand experiments annually.16 The reason behind this is to develop special and satisfactory offers for their clients.
Business Intelligence Tools for Program Analysis and Reporting
There are various business intelligence tools available in the market. In addition, more are being developed every day. The new applications are built with in-memory technology.17 As a result of this, they have the capability to provide greater accessibility compared to other installed systems. However, they can suffer setbacks when working with outsized datasets. In addition, they require fast and stable internet connection. Examples of BI tools include Good Data, iDashboards, Birst, Qlik view, and Tableau.
The tool operates on a cloud-based platform.18 It provides business experts with quality visuals, prompt data engine, and pivoting from multiple variables. In addition, the device is fitted with a reports and dashboards sharing feature.
The aspect facilitates faster and easier cooperation among different users. GoodData is also easy to install. However, deploying and managing the data model can be a complex task in certain instances. As a result, high levels of technical expertise are necessary. Since the tool is cloud-based, consistent internet connection is highly required.
The BI tool is incredibly powerful and flexible in nature. It was developed with an extremely responsive data storage interface compatible with on-disk. The key feature allows it to operate promptly and handle complex calculations with huge datasets. In addition, Birst enables users to conduct Excel computations with little trouble. Its setup is also user friendly.
The aspect is made possible by the advanced graphical interface used for coherent modelling. The technology allows the tool to automatically formulate precise data systems. Generally, Brist is advantageous to mid-sized and large non-profit organisations with devoted IT experts who work with large volumes of data.
iDashboads is an efficient data visualisation software. It enables business managers to effectively evaluate their programs and formulate strategic plans for the organisation.19 In addition, the tool’s interface is user friendly. Due to this fact, a worker can develop personalised dashboards with minimal level of expertise. iDashboards are fitted with a built-in wizard. The feature enables it to connect with compound data sources and automatically refresh itself.
The business intelligence tool is fast to set up, easy to administer, and cost effective. Its primary use is to examine data by controlling the associative model.20 Due to this, the users can gain access to a wide range of information by clicking on the main data file. The visualisation capability is highly beneficial to analytical experts with pre-defined queries. In spite of the tool’s many benefits, its users are required to be experts. The reason behind this is because it is a sophisticated device with a complex user interface.
The business intelligence tool has the capability of operating directly from the user’s database.21 However, all the information to be accessed must be in one catalogue. The aspect is advantageous because it facilitates prompt deployment of adequate data systems. In addition, Tableau allows companies to restructure their statistics representation in-memory.
The device is also programmed with a unique language referred to as VizQL.22 The special technological advancement enables it to transform data into graphical form at high speeds. Generally, the business intelligence tool is suitable for companies with small IT departments.
Benefits of Business Intelligence Tools
The applications have a number of benefits. They include efficient data integration and distribution, flexibility, and creation of unique visuals. BI devices enable users to merge data from multiple sources.23 In many organisations, there are instances where information is stored in different catalogues. As a result, it becomes a challenge to quickly access the needed records. Through the use of BI tools, an individual can easily acquire needed information from any database equipped with an Application Programming Interface.
Business intelligence tools have the capability of storing data in a cache.24 Through this, a separate catalogue is created. The process allows users to work with minimal risk of altering the information stored in the original file. In addition, they facilitate both manual and automatic data loading. The tools provide users with numerous ways of accessing and dispensing information and dashboards.
Users can easily and quickly email up-to-date reports on scheduled times. In addition, one can view and control dashboards by using a device like smartphone or a tablet. However, internet connection is required to enable the process. Majority of BI applications also enable experts to design custom portals for project audiences.25 In a board meeting, for example, an employee can use a BI tool to enable the members gain unique access to the reports being tabled.
Organisations that spire for more flexible reporting can use BI tools to satisfy their needs. The devices present data dynamically through multiple viewpoints. The reason behind this is because information is directly loaded from the initial file to the warehouse.
For example, an IT expert working with the tool can view a report on the number of clients admitted to the application. In addition, they can analyse the rate and trend of achievement at each phase. Business intelligence tools display data in a manner that can be easily translated. Complex graphical information can easily be transformed into different formats, which facilitates understanding.26
Limitations of Business Intelligence Programs
Business intelligence has great benefits to organisations that wish to maintain their top positions in the market. However, there are also disadvantages associated with the use of BI. The limitations include piling of historical data, cost, and complexity. Others are muddling of commercial settings, limited use, and time consuming with regards to implementation.
Piling of Historical Data
The primary goal of business intelligence system is to store an organisation’s data.27 The process allows the information to be retrieved at certain times to help in decision making. Over time, the stored data becomes less valuable to the firm. The reason behind this is because of the ever changing terrain of the corporate world. As a result, the stored data is considered as historical and not very significant at the current times.
Complexity as a limitation is associated with the data implementation aspect of the program.28 BI tends to be extremely composite. As a result of this, it can be a challenge for experts to use various business techniques. Generally, the complexity can result in untimely collapse of an organisation.
Business Intelligence is similar to other improved technologies. The reason is that developers of BI tools target firms to buy their applications. Generally, not all companies can afford the tools. The limited use is experienced in spite of inventors’ efforts to create devices that can be used by small and medium sized organisations.29 Some of the companies do not consider BI systems to be important.
Time Consuming Implementation
Execution of business intelligence in a company requires time and critical evaluation. At times, it may take up to 18 months. Some businesses cannot afford to wait for the duration to expire.
Future of Business Intelligence
To come up with excellent decisions, managers should have an insight into the future. The process entails analysing probable changes to a situation and the impacts to be experienced.30 Poor evaluation leads to great risks. As a result, the outcome tends to be negative. Generally, bad choices can lead to the downfall of a business or career. Proper anticipation of the future of BI requires a clear understanding of the system’s dynamics.
Business intelligence will turn out to be more entity-centric. With the numerous technological advancements, more information sources are on the online platform. The process shows the feature will be a key part of the BI stack. BI will evolve to be more personalised. Currently, reports are developed on one occasion and used by different persons.31 The major reason for this is because loads of technical resources are required to personalise the information. As advancements are made, more people will want to view data in a way they find most suitable. As a result, they will make more use of BI tools.
It is noted that the business intelligence market has been registering positive growth annually. In 2008, the demand for these applications was 7%. In 2009, the figure increased to 15%. IDC research firm predicted a growth of 22% in 2013.32 With the trend, business intelligence will make an entry into major global markets.
For the future of BI to continue being positive, various factors need to be looked into. The applications should be quicker to deploy, easy to use, and affordable for small and middle sized companies. In addition, they should be updated regularly, made interactive, and focused on value.
Business intelligence avails information in a simple and useful manner. Initially, most companies used powerful transaction-oriented data systems.33 With the changing market trends, organisations have shifted to using analytical based systems. The reason behind this is s to remain competitive. The major change is as a result of the development of business intelligence applications. Over the years, BI has continued to rely on real-time data.
Business experts’ burden of monitoring and evaluating programs and outcomes has been lessened. Business intelligence applications are being developed with a wide range of capabilities and functions.34 They include online analytical processing, data and process mining, and business performance management.
In spite of the extensive use of business intelligence by different organisations, key considerations must be made to guarantee effective implementation. The BI system chosen must be effectively utilised to achieve the desired outcomes. In addition, efforts should be made to simplify BI. They include training and organisation.
Employees should be educated on how to use the applications to produce desired business value. A number of measures must be put in place for these systems to function efficiently. For example, technical constraints must be assessed.35 The issues to be examined include security and user access to the warehouse and data volume. Other aspects include data storage, benchmarking, and performance target.
Ask, U 2013, ‘Business intelligence practices’, International Journal of Business Intelligence Research, vol. 4 no. 2, pp. 1-18.
Baars, H & Kemper, H 2008, ‘Management support with structured and unstructured data: an integrated business intelligence framework’, Information Systems Management Journal, vol. 25, pp. 132-148.
Barrett, S 2010, ‘Competitive intelligence: significance in higher education’, Information Systems Management Journal, vol. 2 no. 4, pp. 26-30.
Chaudhuri, S, Dayal, U & Narasayya, V 2011, ‘An overview of business intelligence technology’, Communications of the ACM, vol. 54 no. 8, pp. 88-98.
Dell’Aquila, C, DiTria, F, Lefons, E & Tangora, F 2008, ‘Business intelligence systems: A comparative analysis’, WSEAS Transactions on Information Science and Applications, vol. 5 no. 5, pp. 612-621.
Esat, F, Hart, M, Khatieb, Z & Rocha, M 2007, ‘Introducing students to business intelligence: acceptance and perceptions of OLAP software’, Informing Science and Information Technology, vol. 4, pp. 105-123.
Hwang, M & Xu, H 2007, ‘The effect of implementation factors on data warehousing success: an exploratory study,’ Journal of Information, Information Technology, and Organisations, vol. 2, pp. 1-14.
Jaklic, J, Popovic, A &Turk, T 2010, ‘Conceptual model of business value of business intelligence systems management’, Journal of Contemporary Management Issues, vol. 15 no. 1, pp. 5-30.
Langdon, M 2009, ‘Business model innovation: the strategy of business breakthroughs’, International Journal of Innovation Science, vol. 1 no. 4, pp. 191-204.
Marinela, M & Anca, A 2009, ‘Using business rules in business intelligence’, Journal of Applied Qualitative Methods, vol. 4 no. 3, pp. 382-393.
Matei, G 2010, ‘A collaborative approach to business intelligence systems’, Journal of Applied Collaborative Systems, vol. 2 no. 2, pp. 91-101.
Ramon, M & Avila, E 2008, ‘Conceptual maps and geo-references in business intelligence products and services’, ACIMED, vol. 17 no. 4, pp. 91-104.
1 Chaudhuri, S, Dayal, U & Narasayya, V 2011, ‘An overview of business intelligence technology’, Communications of the ACM, vol. 54 no. 8, p. 98.
2 Esat, F, Hart, M, Khatieb, Z & Rocha, M 2007, ‘Introducing students to business intelligence: acceptance and perceptions of OLAP software’, Informing Science and Information Technology, vol. 4, p. 109.
3 Hwang, M & Xu, H 2007, ‘The effect of implementation factors on data warehousing success: an exploratory study,’ Journal of Information, Information Technology, and Organisations, vol. 2, p. 11.
4 Matei, G 2010, ‘A collaborative approach to business intelligence systems’, Journal of Applied Collaborative Systems, vol. 2 no. 2, p. 98.
5 Chaudhuri et al., p. 92.
6 Dell’Aquila, C, DiTria, F, Lefons, E & Tangora, F 2008, ‘Business intelligence systems: A comparative analysis’, WSEAS Transactions on Information Science and Applications, vol. 5 no. 5, p. 615.
7 Ask, U 2013, ‘Business intelligence practices’, International Journal of Business Intelligence Research, vol. 4 no. 2, p. 18.
8 Barrett, S 2010, ‘Competitive intelligence: significance in higher education’, Information Systems Management Journal, vol. 2 no. 4, p. 28.
9 Baars, H & Kemper, H 2008, ‘Management support with structured and unstructured data: an integrated business intelligence framework’, Information Systems Management Journal, vol. 25, p. 142.
10 Jaklic, J, Popovic, A &Turk, T 2010, ‘Conceptual model of business value of business intelligence systems management’, Journal of Contemporary Management Issues, vol. 15 no. 1, p. 21.
11 Langdon, M 2009, ‘Business model innovation: the strategy of business breakthroughs’, International Journal of Innovation Science, vol. 1 no. 4, p. 191.
12 Marinela, M & Anca, A 2009, ‘Using business rules in business intelligence’, Journal of Applied Qualitative Methods, vol. 4 no. 3, p. 390.
13 Matei, p. 98.
14 Marinela et al., p. 391.
15 Chaudhuri et al., p. 90.
16 Barrett, p. 29.
17 Baars & Kemper, p. 140.
18 Dell’Aquila et al., p. 615.
19 Esat et al., p. 120.
20 Jaklic et al., p. 19.
21 Langdon, p. 204.
22 Matei, 99.
23 Ramon, M & Avila, E 2008, ‘Conceptual maps and geo-references in business intelligence products and services’, ACIMED, vol. 17 no. 4, p. 95.
24 Marinela et al., p. 386.
25 Jaklic et al., p. 20.
26 Chaudhuri et al., p. 88.
27 Ask, p. 17.
28 Barrett, p. 28.
29 Dell’Aquila et al., p. 617.
30 Esat et al., p. 110.
31 Jaklic et al., p. 20.
32 Ask, p. 15.
33 Langdon, p. 194.
34 Ramon & Avila, p. 96.
35 Chaudhuri et al., p. 92.