Business Intelligence Software Sets You Back – Business intelligence (BI) is a technology-driven process of analyzing data and delivering actionable information that helps managers, executives and employees make informed business decisions. As part of the BI process, organizations collect data from internal IT systems and external sources, prepare analysis, answer questions against data and create data visualizations, BI dashboards and reports to make analysis results available to business users for decision-making and strategic planning.
The ultimate goal of BI systems is to drive better business decisions that enable organizations to increase revenue, improve efficiency and gain competitive advantages over business rivals. To achieve that goal, BI includes a combination of analytics, data management and reporting tools, and a variety of data management and analysis methods.
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A business intelligence architecture encompasses more than just BI software. Business intelligence data is often stored in an organization-wide data warehouse or in smaller data marts that hold subsets of business information for individual departments and business units, often with responsibilities in the enterprise data warehouse. Additionally, data pools based on Hadoop clusters or other big data systems are increasingly used as warehouses or landing pads for BI and analytics data, especially for log files, sensor data, text and other types of unstructured or unstructured data.
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BI data can include historical information and real-time data collected from source systems as they are generated, allowing BI tools to support both strategic and tactical decision-making processes. Before it can be used in BI systems, raw data from disparate source systems must often be combined, combined and cleaned using data integration and data quality management tools to ensure that BI teams and business users are analyzing accurate and consistent information.
Initially, BI tools were mainly used by BI and IT professionals who asked questions and generated dashboards and reports for business users. Increasingly, however, business analysts, managers and employees are using business intelligence platforms themselves, thanks to the development of self-service BI and data discovery tools. Self-service business intelligence environments allow business users to query BI data, create data visualizations and design dashboards on their own.
BI systems often include forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical analysis and big data analytics. A common example is a forecasting model that allows the analysis of different business scenarios. However, in many cases, advanced analytics projects are performed by separate teams of data scientists, statisticians, predictive modelers and other skilled statisticians, while BI teams oversee the specific querying and analysis of business data.
Overall, the role of business intelligence is to improve the business performance of the organization by using the right data. Companies that successfully use BI tools and techniques can translate their collected data into valuable insights about their business processes and strategies. Such insights can be used to make better business decisions that increase productivity and revenue, leading to faster business growth and higher profits.
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Without BI, organizations cannot take advantage of data-driven decision making. Instead, managers and employees are largely left to base important business decisions on other factors, such as accumulated knowledge, past experience, intuition and gut feelings. While those methods can lead to good decisions, they are also fraught with the potential for error and missteps due to a lack of supporting data.
A successful BI program generates various business benefits for the organization. For example, BI enables C-suite executives and department heads to continuously monitor business performance to act quickly when problems or opportunities arise. Analyzing customer data helps make marketing, sales and customer service efforts more effective. Supply chain, production and distribution issues can be detected before they cause financial damage. HR managers are better able to monitor employee productivity, labor costs and other personnel information.
BI measures also provide small business benefits — among them, making it easier for project managers to track the status of business projects and for organizations to gather competitive intelligence. In addition, BI, data management and IT teams themselves benefit from business intelligence, which they use to analyze various aspects of technology and performance analytics.
Business intelligence includes a broad set of data analysis applications designed to meet different information needs. Most are supported by both self-service BI software and traditional BI platforms. The range of BI technologies available to organizations includes the following:
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Ad hoc analysis. Also known as ad hoc querying, this is one of the cornerstones of modern BI applications and a key feature of self-service BI tools. It is the process of writing and applying questions to analyze specific business issues. Although ad hoc queries are often created over time, they are often run regularly, with statistical results compiled into dashboards and reports.
Online analytical processing (OLAP). One of the first BI technologies, OLAP tools allow users to analyze data in multiple dimensions, particularly suitable for complex queries and calculations. In the past, data had to be extracted from a data warehouse and stored in multidimensional OLAP cubes, but it is increasingly possible to apply OLAP analysis directly to a columnar database.
Mobile BI. Mobile business intelligence makes BI applications and dashboards available on smartphones and tablets. Often used more for viewing data than analyzing it, mobile BI tools are often designed with an emphasis on ease of use. For example, mobile dashboards may only display two or three data visualizations and KPIs for easy viewing on the device screen.
Real-time BI. In real-time BI applications, data is analyzed as it is created, collected and processed to provide users with an up-to-date view of business performance, customer behavior, financial markets and other areas of interest. The real-time analytics process often involves streaming data and supports the use of decision analytics, such as credit scoring, stock trading and targeted promotional offers.
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Operational Intelligence (OI). Also called operational BI, this is a form of real-time analysis that delivers information to managers and front-line employees on business operations. OI applications are designed to aid decision-making and operations and enable quick action on issues — for example, helping call center agents resolve issues with customers and logistics managers to ease distribution bottlenecks.
Software-as-a-service BI. SaaS BI tools use vendor-hosted cloud computing systems to deliver data analytics capabilities to users in the form of a service typically priced by subscription. Also known as BI cloud, the SaaS option provides continuous multi-cloud support, allowing organizations to deploy BI applications to different cloud platforms to meet user needs and avoid vendor lock-in.
Open source BI (OSBI). Open source business intelligence software typically includes two versions: a public edition that can be used free of charge and a subscription-based commercial release with vendor technical support. BI teams can also access source code for development use. In addition, some vendors of proprietary BI tools offer free plans, especially for individual users.
Embedded BI. Embedded business intelligence tools put BI functionality and data visualization directly into business systems. That enables business users to analyze data within the applications they use to do their work. Embedded analytics features are often included by application software vendors, but enterprise software developers can also add them to home applications.
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Collaborative BI. This is a more technical process. It involves a combination of BI applications and collaboration tools so that different users can work together on data analysis and share information with each other. For example, users can explain BI data and statistical results with comments, questions and highlights using online chat and discussion tools.
Local intelligence (LI). This is a special type of BI that allows users to analyze spatial and geospatial data, with integrated map-based data visualization functionality. Location intelligence provides insights into location factors in business data and operations. Potential applications include site selection for stores and corporate services, location-based marketing and inventory management.
Self-service BI and data visualization tools have become the standard for modern BI software. Tableau, Qlik and Spotfire, now part of Tibco Software, led the development of early self-service technologies and became dominant competitors in the BI market in 2010. Most vendors of traditional BI query and reporting tools have followed suit since then. Now, almost all major BI tools include self-service features, such as virtual data discovery and ad hoc queries.
BI tools are available from many vendors. Major IT vendors that provide BI software include IBM, Microsoft, Oracle, SAP, SAS and Salesforce, which bought Tableau in 2019 and is also selling its tools developed before the acquisition. Google is also in the BI market with its Locker unit, acquired in 2020. Other notable BI vendors include Alteryx, Domo, GoodData, Infor Birst, Information Builders, Logi Analytics, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot and Yellowfin.
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While fully featured BI platforms are the most widely used business intelligence technology, the BI market also includes other product categories. Some vendors offer specialized tools for embedded BI applications; examples include GoodData and Logi Analytics. Companies such as Locker, Sisense and ThinkSpot manage complex and selective data analysis applications. Various
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