What is Business Intelligence and what is the utility of BI Tools?
Business Intelligence (BI) is defined as any real-time, current or past information that helps various business professionals including managers analyze current/past activities to help in predicting future course of the company’s business. Business Intelligence is thus a stream of data and hence it requires sorting as well as analysis before it is suitable for use in a company’s decision-making process. Such sorting and analysis of relevant data is usually carried out by software solutions, to ensure superior speed and accuracy of the data collection and analysis procedure. Any and all software solutions aiding the process of generating Business Intelligence for an enterprise are termed as Business Intelligence Tools. So BI data can help an enterprise rapidly adjust to changing business environment, while BI tools ensure that the changing business environment is rapidly as well as correctly identified and reported to facilitate a streamlined decision-making process. In case of historic data, BI tools usually sort and analyze data, which was previously stored in the enterprise database.
Commonly Used Business Intelligence Tools
BI tools are commonly classified into the following categories:
• Local Information Systems
• Business Performance Management
• Process Mining
• Online Analytical Processing (OLAP)
• Data Warehousing
• Data Mining
• Reporting and Querying Software
Most of these Business Intelligence technology and tools apart from spreadsheets are available as part of software suitable for a specific industry, standalone solutions, ERP system components or as a BI software suite. These solutions are often developed by a custom development company in response to requirements specified by a client or detected after a thorough analysis of the company’s business model. A few open-source business intelligence tools are also available, however most enterprises prefer to use proprietary business intelligence technology to ensure adequate protection of critical data. The type of business intelligence architecture implemented by an organization varies on the industry, market conditions as well as specific market requirements. Some of the commonly available BI tool categories are described here:
Local Information Systems
The term Local Information System (LIS) originated from its use in the public sector of the UK; other terms used synonymously with LIS in different parts of the world include – Data Observatory and Community information systems. In the global business intelligence technology market, LIS applications are usually limited to providing support for geographic reporting of enterprise operations. The functions supported by LIS tools often overlap with some of the features of Geographic Information Systems and Knowledge Management tools. Unique functions of LIS include providing a region-specific database accessible by citizens, policy makers, managers as well as data experts. LIS statistics are usually compiled with respect to a small area such as the National Neighborhood Statistics projects in the UK. Currently operating Local Information Systems include the DarlingtonLIS, UK; Newcastle Council; New Zealand Ministry of Health and Fife Council, UK.
Business Performance Management
Business Performance Management (BPM) refers to a set of management as well as analytical processes designed to facilitate improvement of a company’s processes in accordance with the preset goals of the organization. Such tools are capable of handling large amounts of data and help managers in determining fruitful interventions designed to improve the functioning of specific business processes. Currently available tools for BPM are based on the balanced scorecard framework and queries supported by BPM tools include metric-related queries, customer/stakeholder queries, goal-alignment queries, cost/risk queries as well as much more.
Process Mining is commonly defined as a process management technique which allows decision-makers to analyze business processes on the basis of available event logs. These event logs are automatically generated by the enterprise event system and the aim of Process Mining is to facilitate improvement of overall performance by providing tools and techniques designed to identify social, organizational, control and process structures by using the event logs. The technique is preferred if other conventional techniques fail of provide adequate insight into an enterprise process. Process Mining features in certain contemporary management techniques such as Business Process Intelligence, Business Operations Management and Business Activity Monitoring. Current Process Mining techniques are classified into the following categories: extension, conformation analysis and discovery.
Dashboards are defined as an easily read, real-time interface, which provides a snapshot of the current status of key business processes as a chart or graph. Dashboards are one of the most prolific and widely used tools for supporting informed and instantaneous decision making. Dashboards are capable of displaying a wide variety of user-defined key performance indicators significant for different departments of an organization. A production dashboard can display the total number of units produced, the average rate of production per hours, number of produced units which failed inspection during a one month period and so on. The key benefit of a dashboard is its capability to be customized to show only the relevant data, which results in significant time savings during the process of decision making. Currently available dashboards are commonly classified into three categories- desktop widgets, web-based applications as well as standalone solutions, which feature spark lines, bullet graphs, pie charts and/or bar charts to represent the data. Dashboards are also capable of being integrated into mobile business intelligence solutions to ensure seamless connectivity irrespective of the user’s location.
Online Analytical Processing (OLAP)
OLAP tools are designed to help users interactively analyze multidimensional data from multiple perspectives. OLAP as a business intelligence method includes various aspects of data mining and rational reporting. The term Online Analytical Processing is a derivative of OLTP (Online Transaction Processing), which is used in reference to traditional databases. Key analytical operations performed by these tools are- consolidation, drill-down and slice ‘n’ dice. The consolidation process refers to the aggregation of data to enable its analysis on multiple dimensions. The drill-down technique enables users to navigate through large quantities on data to sort out the relevant data. The slice ‘n’ dice technique allows users to remove (slice) a particular data set to allow closer inspection (dicing) of the selected data set. Databases with OLAP support utilize a multidimensional data model for supporting rapid execution of both ad-hoc as well as complex analytical queries.