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Business intelligence (BI) is a technology-driven process for analyzing information and delivering actionable information that helps executives, managers and workers brand informed business decisions. Every bit office of the BI process, organizations collect data from internal It systems and external sources, prepare information technology for analysis, run queries confronting the data and create data visualizations, BI dashboards and reports to make the analytics results available to business users for operational decision-making and strategic planning.
The ultimate goal of BI initiatives is to drive better business decisions that enable organizations to increase revenue, improve operational efficiency and proceeds competitive advantages over business rivals. To achieve that goal, BI incorporates a combination of analytics, data management and reporting tools, plus diverse methodologies for managing and analyzing data.
How the business organization intelligence process works
A concern intelligence architecture includes more than just BI software. Business organisation intelligence data is typically stored in a data warehouse congenital for an entire organisation or in smaller information marts that hold subsets of business information for individual departments and business units, ofttimes with ties to an enterprise data warehouse. In addition, data lakes based on Hadoop clusters or other big data systems are increasingly used equally repositories or landing pads for BI and analytics information, particularly for log files, sensor data, text and other types of unstructured or semistructured data.
BI data tin can include historical information and real-fourth dimension information gathered from source systems as information technology'south generated, enabling BI tools to support both strategic and tactical controlling processes. Before it's used in BI applications, raw information from different source systems generally must be integrated, consolidated and cleansed using data integration and data quality management tools to ensure that BI teams and business users are analyzing accurate and consistent data.
From there, the steps in the BI process include the following:
- information preparation, in which information sets are organized and modeled for assay;
- analytical querying of the prepared data;
- distribution of key performance indicators (KPIs) and other findings to business users; and
- use of the information to help influence and drive business organization decisions.
Initially, BI tools were primarily used by BI and IT professionals who ran queries and produced dashboards and reports for business organisation users. Increasingly, however, business analysts, executives and workers are using business organisation intelligence platforms themselves, cheers to the evolution of self-service BI and information discovery tools. Self-service business organisation intelligence environments enable business organization users to query BI data, create data visualizations and design dashboards on their own.
BI programs often comprise forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical assay and big information analytics. A common example is predictive modeling that enables what-if analysis of different business scenarios. In most cases, though, advanced analytics projects are conducted past separate teams of data scientists, statisticians, predictive modelers and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.
Why business intelligence is important
Overall, the office of business intelligence is to amend an organization's concern operations through the use of relevant data. Companies that finer employ BI tools and techniques tin interpret their nerveless data into valuable insights about their business concern processes and strategies. Such insights can then be used to make better business concern decisions that increment productivity and revenue, leading to accelerated business growth and higher profits.
Without BI, organizations can't readily accept advantage of information-driven conclusion-making. Instead, executives and workers are primarily left to base important business decisions on other factors, such as accumulated knowledge, previous experiences, intuition and gut feelings. While those methods can effect in good decisions, they're also fraught with the potential for errors and missteps considering of the lack of data underpinning them.
Benefits of business concern intelligence
A successful BI program produces a variety of concern benefits in an organization. For case, BI enables C-suite executives and department managers to monitor business operation on an ongoing basis and so they can act apace when problems or opportunities arise. Analyzing client data helps make marketing, sales and client service efforts more than constructive. Supply concatenation, manufacturing and distribution bottlenecks can be detected before they cause financial harm. Hour managers are ameliorate able to monitor employee productivity, labor costs and other workforce information.
Overall, the key benefits that businesses can get from BI applications include the ability to:
- speed upwardly and improve decision-making;
- optimize internal business organization processes;
- increase operational efficiency and productivity;
- spot business bug that demand to be addressed;
- place emerging business and market trends;
- develop stronger business strategies;
- drive higher sales and new revenues; and
- proceeds a competitive edge over rival companies.
BI initiatives likewise provide narrower concern benefits -- among them, making information technology easier for project managers to runway the condition of business projects and for organizations to assemble competitive intelligence on their rivals. In add-on, BI, data direction and It teams themselves do good from business organisation intelligence, using it to clarify diverse aspects of technology and analytics operations.
Types of business organization intelligence tools and applications
Business organisation intelligence combines a broad set of data assay applications designed to run into different information needs. Nigh are supported by both self-service BI software and traditional BI platforms. The listing of BI technologies that are bachelor to organizations includes the following:
Advertizing hoc assay . As well known as ad hoc querying, this is one of the foundational elements of modern BI applications and a primal feature of self-service BI tools. It's the process of writing and running queries to analyze specific business issues. While ad hoc queries are typically created on the fly, they often finish up being run regularly, with the analytics results incorporated into dashboards and reports.
Online analytical processing (OLAP). One of the early on BI technologies, OLAP tools enable users to analyze data along multiple dimensions, which is particularly suited to complex queries and calculations. In the by, the data had to be extracted from a data warehouse and stored in multidimensional OLAP cubes, just it'south increasingly possible to run OLAP analyses directly against columnar databases.
Mobile BI . Mobile business intelligence makes BI applications and dashboards available on smartphones and tablets. Often used more to view data than to analyze information technology, mobile BI tools typically are designed with an accent on ease of utilize. For example, mobile dashboards may just display ii or three information visualizations and KPIs so they can easily be viewed on a device'south screen.
Existent-fourth dimension BI . In real-time BI applications, data is analyzed as it'south created, collected and processed to requite users an up-to-appointment view of concern operations, customer behavior, financial markets and other areas of involvement. The existent-fourth dimension analytics process frequently involves streaming data and supports conclusion analytics uses, such every bit credit scoring, stock trading and targeted promotional offers.
Operational intelligence (OI). Also called operational BI, this is a class of real-time analytics that delivers data to managers and frontline workers in business operations. OI applications are designed to assist in operational decision-making and enable faster activeness on issues -- for instance, helping call center agents to resolve problems for customers and logistics managers to ease distribution bottlenecks.
Software-as-a-service BI . SaaS BI tools use cloud computing systems hosted by vendors to deliver data analysis capabilities to users in the class of a service that'due south typically priced on a subscription basis. Besides known every bit cloud BI, the SaaS selection increasingly offers multi-deject back up, which enables organizations to deploy BI applications on different cloud platforms to come across user needs and avert vendor lock-in.
Open source BI (OSBI). Business concern intelligence software that is open source typically includes ii versions: a community edition that tin can be used gratuitous of charge and a subscription-based commercial release with technical support past the vendor. BI teams tin also access the source code for evolution uses. In addition, some vendors of proprietary BI tools offering gratis editions, primarily for individual users.
Embedded BI . Embedded business concern intelligence tools put BI and data visualization functionality directly into business applications. That enables business users to analyze data within the applications they use to do their task. Embedded analytics features are most commonly incorporated by application software vendors, but corporate software developers can also include them in homegrown applications.
Collaborative BI . This is more of a process than a specific technology. It involves the combination of BI applications and collaboration tools to enable different users to work together on information assay and share information with one some other. For example, users can annotate BI data and analytics results with comments, questions and highlighting via the utilise of online chat and give-and-take tools.
Location intelligence (LI). This is a specialized course of BI that enables users to analyze location and geospatial data, with map-based data visualization functionality incorporated. Location intelligence offers insights on geographic elements in business organisation data and operations. Potential uses include site pick for retail stores and corporate facilities, location-based marketing and logistics management.
Business intelligence vendors and market
Cocky-service BI and information visualization tools accept become the standard for modern BI software. Tableau, Qlik and Spotfire, which is now office of Tibco Software, took the lead in developing self-service technology early and became prominent competitors in the BI marketplace by 2010. Virtually vendors of traditional BI query and reporting tools have followed in their path since and so. At present, virtually every major BI tool incorporates self-service features, such as visual data discovery and ad hoc querying.
In addition, mod BI platforms typically include:
- data visualization software for designing charts and other infographics to show data in an easy-to-grasp fashion;
- tools for building BI dashboards, reports and performance scorecards that display visualized data on KPIs and other business metrics;
- data storytelling features for combining visualizations and text in presentations for business concern users; and
- usage monitoring, performance optimization, security controls and other functions for managing BI deployments.
BI tools are available from dozens of vendors overall. Major It vendors that offer BI software include IBM, Microsoft, Oracle, SAP, SAS and Salesforce, which bought Tableau in 2019 and also sells its own tools developed before the acquisition. Google is also in the BI market through its Looker unit, acquired in 2020. Other notable BI vendors include Alteryx, Domo, GoodData, Infor Birst, Data Builders, Logi Analytics, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot and Yellowfin.
While total-featured BI platforms are the about widely used business organisation intelligence engineering, the BI market also includes other product categories. Some vendors offer tools specifically for embedded BI uses; examples include GoodData and Logi Analytics. Companies like Looker, Sisense and ThoughtSpot target circuitous and curated information analysis applications. Diverse dashboard and data visualization specialists focus on those parts of the BI process; other vendors specialize in information storytelling tools.
Examples of business intelligence apply cases
In general terms, enterprise BI use cases include:
- monitoring concern performance or other types of metrics;
- supporting conclusion-making and strategic planning;
- evaluating and improving concern processes;
- giving operational workers useful information nearly customers, equipment, supply chains and other elements of business operations; and
- detecting trends, patterns and relationships in information.
Specific use cases and BI applications vary from industry to industry. For example, financial services firms and insurers use BI for risk analysis during the loan and policy approving processes and to identify additional products to offer to existing customers based on their current portfolios. BI helps retailers with marketing entrada direction, promotional planning and inventory direction, while manufacturers rely on BI for both historical and real-time analysis of institute operations and to help them manage product planning, procurement and distribution.
Airlines and hotel chains are large users of BI for things such as tracking flight capacity and room occupancy rates, setting and adjusting prices, and scheduling workers. In healthcare organizations, BI and analytics aid in the diagnosis of diseases and other medical conditions and in efforts to ameliorate patient care and outcomes. Universities and school systems tap BI to monitor overall student functioning metrics and identify individuals who might need assistance, amidst other applications.
Concern intelligence for big information
BI platforms are increasingly beingness used as front end-end interfaces for large data systems that contain a combination of structured, unstructured and semistructured data. Modern BI software typically offers flexible connectivity options, enabling information technology to connect to a range of data sources. This, forth with the relatively uncomplicated user interface (UI) in well-nigh BI tools, makes it a good fit for big data architectures.
Users of BI tools can access Hadoop and Spark systems, NoSQL databases and other large data platforms, in add-on to conventional data warehouses, and get a unified view of the diverse information stored in them. That enables a broad number of potential users to become involved in analyzing sets of big information, instead of highly skilled data scientists being the merely ones with visibility into the data.
Alternatively, big data systems serve equally staging areas for raw data that later is filtered and refined and so loaded into a information warehouse for assay by BI users.
Business intelligence trends
In addition to BI managers, business organization intelligence teams generally include a mix of BI architects, BI developers, BI analysts and BI specialists who work closely with data architects, information engineers and other data management professionals. Business analysts and other stop users are also often included in the BI evolution process to correspond the business side and make sure its needs are met.
To help with that, a growing number of organizations are replacing traditional waterfall development with Agile BI and data warehousing approaches that use Agile software development techniques to suspension up BI projects into small chunks and deliver new functionality on an incremental and iterative footing. Doing and so enables companies to put BI features into use more than apace and to refine or modify development plans as business needs change or new requirements emerge.
Other notable trends in the BI market include the following:
- The proliferation of augmented analytics technologies . BI tools increasingly offer natural linguistic communication querying capabilities as an alternative to writing queries in SQL or some other programming language, plus AI and automobile learning algorithms that help users find, empathise and prepare data and create charts and other infographics.
- Low-code and no-lawmaking development. Many BI vendors are too adding graphical tools that enable BI applications to be adult with little or no coding.
- Increased use of the cloud. BI systems initially were slow to movement to the cloud, partly because data warehouses were primarily deployed in on-premises information centers. But cloud deployments of both data warehouses and BI tools are growing; in early 2020, consulting firm Gartner said virtually new BI spending is now for cloud-based projects.
- Efforts to improve data literacy . With cocky-service BI broadening the use of concern intelligence tools in organizations, it'south disquisitional to ensure that new users can understand and work with data. That's prompting BI teams to include data literacy skills in user preparation programs. BI vendors have also launched initiatives, such as the Qlik-led Data Literacy Project.
Business intelligence vs. information analytics and business analytics
Sporadic use of the term business intelligence dates back to at least the 1860s, just consultant Howard Dresner is credited with first proposing it in 1989 equally an umbrella phrase for applying data analysis techniques to support business decision-making processes. What came to be known equally BI tools evolved from earlier, often mainframe-based analytics technologies, such as decision support systems and executive information systems that were primarily used past business executives.
Concern intelligence is sometimes used interchangeably with business analytics. In other cases, business analytics is used either more narrowly to refer to advanced analytics or more broadly to include both that and BI. Meanwhile, data analytics is primarily an umbrella term that encompasses all forms of BI and analytics applications. That includes the main types of information analysis: descriptive analytics, which is typically what BI provides; predictive analytics, which models time to come beliefs and outcomes; and prescriptive analytics, which recommends business organisation actions.
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Source: https://www.techtarget.com/searchbusinessanalytics/definition/business-intelligence-BI
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