Business intelligence (BI) is a technology-driven process for analyzing data and presenting useful information to help corporate executives, business managers, and other end users make more informed business decisions. BI encompasses a wide variety of tools, applications, and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards, and data visualizations. to make the analytical results available to both corporate decision makers and operational workers.
The potential benefits of business intelligence programs include accelerating and improving decision making, optimizing internal business processes, increasing operational efficiency, driving new revenue, and gaining competitive advantages over business rivals. BI systems can also help companies identify market trends and identify business problems that need to be addressed.
BI data can include historical information as well as new data collected from source systems as it is generated, allowing BI analysis to support both strategic and tactical decision-making processes. Initially, BI tools were used primarily by data analysts and other IT professionals who performed analysis and produced reports with query results for business users. Increasingly, however, business executives and workers are using BI software for themselves, thanks in part to the development of self-service BI and data discovery tools.
Business intelligence combines a broad set of data analytics applications, including ad hoc query and analysis, business reporting, online analytical processing (OLAP), mobile BI, real-time BI, operational BI, cloud, and software such as BI services, open source BI, collaborative BI and location intelligence. BI technology also includes data visualization software for designing charts and other infographics, as well as tools for building BI dashboards and performance tables that display visualized data on business metrics and key performance indicators in an easy-to-understand way.. BI applications can be purchased separately from different vendors or as part of a unified BI platform from a single vendor.
BI programs can also incorporate forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical analysis, and big data analytics. In many cases, however, advanced analytics projects are led and managed by independent teams of data scientists, statisticians, predictive modelers, and other expert analytics professionals, while BI teams oversee the more direct inquiry and analysis of data. business.
Business intelligence data is typically stored in a data warehouse or in smaller databases that contain subsets of information about a company. Additionally, Hadoop systems are increasingly being used within BI architectures as repositories or landing pads for BI and analytics data, especially for unstructured data, log files, sensor data, and other types of large data. Before use in BI applications, raw data from different source systems must be integrated, consolidated, and cleansed using data quality and data integration tools to ensure that users are analyzing accurate and consistent information.
In addition to BI managers, business intelligence teams generally include a mix of BI architects, BI developers, business analysts, and data management professionals; Business users are also often included to represent the business side and to ensure that their needs are met in the BI development process. To help you, a growing number of organizations are replacing traditional waterfall development with Agile BI and warehouse data approaches that use Agile software development techniques to break BI projects into small chunks and deliver new functionality to end users. incrementally and iteratively.Doing so can enable companies to get BI functions up and running more quickly and to refine or modify development plans as business needs change or new requirements emerge and take precedence over old ones.
The sporadic use of the term business intelligence dates back to at least the 1860s, but consultant Howard Dresner is credited with the first proposal in 1989 as an umbrella category for the application of data analysis techniques to support business processes. business decision making. What came to be known as BI technologies evolved from earlier analytical systems, often based on mainframes, such as decision support systems and executive information systems. Business intelligence is sometimes used interchangeably with business analytics, in other cases, business analytics is used more closely to refer to advanced data analytics or more broadly to include both BI analytics and advanced analytics.
I Source Intelligence vs. Business Advanced analysis
| Business intelligence | Advanced analysis | |
| Answer the questions: | -What happened?
-When? -Who? -How much? |
-Why it happened?
-Will it happen again? -What happens if we change X? -What else can information tell us that we never thought to ask? |
| It includes: | -Reports (KPI metrics)
-Ad hoc consultation OLAP (cube, slice and dice, drilling) -Dashboards / Scorecards -Bi operational / real time -Automated monitoring / alert |
-Statistical / quantitative analysis
-Data mining -Predictive modeling / analysis -Big data analysis -Text analysis -Multivariate tests |
B i biography
Biere, M. (2003). Business intelligence for the company. Prentice Hall Professional. Curto Díaz, J. (2012). Introduction to Business Intelligence. Editorial UOC.
Sabherwal, R., & Becerra-Fernandez, I. (2011). Business Intelligence: Practices, Technologies and
Administration. John Wiley & Sons.
Download the original file
