"Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information."
The gathering, analyzing, and presenting of information about business operations and performance in order to make informed decisions.
Data Analytics: This involves the use of statistical and data mining techniques to analyze, interpret and discover patterns in data.
Data Warehousing: This refers to the process of collecting, managing, and storing data from multiple sources in a central repository.
Business Intelligence Tools: These are software applications that are used to collect, analyze, and present data in a way that is easy to understand and use.
Data Visualization: This refers to the use of graphical representations such as charts, graphs, and dashboards to present data in a visually appealing and easily understandable format.
Business Intelligence Architecture: This involves the design and development of a framework for business intelligence systems, including data warehousing, data modeling, and analytical tools.
Business Performance Management: This involves using business intelligence tools to monitor and improve key performance indicators such as revenue, profitability, and customer satisfaction.
ETL (Extract, Transform, Load): This is a process used to extract data from various sources, transform it into a format suitable for analysis, and load it into a data warehouse.
Data Governance: This refers to the management of data quality, security, and compliance within an organization.
Data Mining: This involves the use of artificial intelligence and machine learning techniques to discover hidden patterns and insights in data.
Cloud Computing and Business Intelligence: This involves the use of cloud-based services and infrastructure to support business intelligence systems.
Big Data Management: This involves the management and analysis of large volumes of structured and unstructured data.
Text and Social Media Analytics: This refers to the use of natural language processing and sentiment analysis techniques to extract insights from text and social media data.
Predictive Analytics: This involves the use of statistical and machine learning techniques to make predictions about future events based on historical data.
Data Integration and Interoperability: This refers to the ability of different systems and applications to exchange data and work together seamlessly.
OLAP (Online Analytical Processing): This refers to the ability to analyze multidimensional data, such as sales data by geography, product, and time.
Mobile Business Intelligence: This involves the use of mobile devices such as smartphones and tablets to access business intelligence systems and data on the go.
Data Privacy and Security: This refers to the protection and secure management of sensitive data within an organization.
Data Governance Framework: This is a set of policies, standards, and procedures that govern how data is collected, managed, and shared within an organization.
Data Quality Management: This involves ensuring that data is accurate, complete, and consistent.
Data Visualization Techniques: This includes choosing the right chart or graph to represent data, and designing effective visual representations.
Operational BI: This type of BI is focused on the operational data of a business, such as sales data or daily transactional data, and provides real-time decision-making insights.
Strategic BI: This type of BI is focused on long-term business goals and analysis. It helps identify and forecast trends and patterns to create a strategic roadmap.
Analytical BI: Analytical BI digs deeper into the data to discover relationships, patterns, and insights that were previously unknown. Its unique approach to data analysis helps to create new business opportunities.
Predictive BI: Predictive BI uses statistical algorithms and machine learning methods to identify and model future business trends and patterns.
Prescriptive BI: Prescriptive BI utilizes predictive algorithms to provide actionable insights for decision-making in real-time.
Mobile BI: This type of BI enables users to access BI data using mobile devices, such as smartphones, tablets, or laptops.
Collaborative BI: Collaborative BI enables teams to work together on a real-time basis, share data, and analyze it together.
Cloud BI: Cloud-based BI is a software-as-a-service (SaaS) model that enables users to access BI tools and technologies on-demand, online.
Self-service BI: Self-service BI enables business users to create their own reports, charts, and dashboards without the need for IT support.
Big Data BI: Big Data BI is an emerging field of business intelligence that focuses on using and analyzing large volumes of unstructured data to gain insights that were previously not possible.
"Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics."
"BI tools can handle large amounts of structured and sometimes unstructured data."
"They aim to allow for the easy interpretation of these big data."
"Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability, and help them take strategic decisions."
"Business intelligence can be used by enterprises to support a wide range of business decisions ranging from operational to strategic."
"Basic operating decisions include product positioning or pricing."
"Strategic business decisions involve priorities, goals, and directions at the broadest level."
"When combined, external and internal data can provide a complete picture which, in effect, creates an 'intelligence' that cannot be derived from any singular set of data."
"Among myriad uses, business intelligence tools empower organizations to gain insight into new markets, to assess demand and suitability of products and services for different market segments, and to gauge the impact of marketing efforts."
"BI applications use data gathered from a data warehouse (DW) or from a data mart."
"A data warehouse contains a copy of analytical data that facilitates decision support."