Business Intelligence Business Software Designer Return To – Business intelligence (BI) is a technology-based process for analyzing data and delivering actionable information that helps executives, managers, and employees make informed business decisions. As part of the BI process, organizations collect data from internal IT systems and external sources, prepare it for analysis, run queries against the data, and create data visualizations, BI dashboards, and reports that communicate the results of this analysis to the business. provides users with quick decision making. creation and strategic planning.
The ultimate goal of BI initiatives is to make better business decisions that enable organizations to increase revenue, improve operational efficiency, and gain a competitive advantage over business competitors. To achieve this goal, BI includes a combination of analytics, data management, and reporting tools, as well as different methodologies for data management and analysis.
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Business intelligence architecture involves more than just BI software. Business intelligence data is typically stored in a data warehouse built for the entire organization or subsets of business data for individual departments and business units, often smaller data linked to an enterprise data warehouse. stored in warehouses. In addition, data lakes based on Hadoop clusters or other big data systems are repositories or repositories for BI and analytics data, especially log files, sensor data, text, and other types of unstructured or semi-structured data. are increasingly being used as niche sites.
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BI data can include historical information and real-time data collected from source systems at the time of creation, enabling BI tools to support strategic and tactical decision-making processes. Before being used in BI applications, raw data from disparate source systems must typically be integrated, combined, and cleaned using data integration and data quality management tools to ensure that BI teams and business users can analyze accurate and consistent data.
Initially, BI tools were primarily used by BI and IT professionals who ran queries and produced dashboards and reports for business users. However, business analysts, executives and workers 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 applications often include advanced forms of analysis such as data mining, predictive analytics, text mining, statistical analysis, and big data analytics. A common example is predictive modeling, which allows analysis of various business scenarios. In many cases, advanced analytics projects are handled by separate teams of data scientists, statisticians, predictive modelers, and other skilled analysts, while BI teams oversee more granular querying and analysis of business data.
In general, the role of business intelligence is to improve the business performance of the organization through the use of relevant information. Companies that effectively use BI tools and techniques can turn their collected data into valuable insights into business processes and strategies. Such insights can then be used to make better business decisions that increase efficiency and profits, leading to faster business growth and higher profits.
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Without BI, organizations cannot easily take advantage of data-driven decision making. Instead, leaders and workers must primarily base important business decisions on other factors such as accumulated knowledge, prior experiences, intuition, and emotions. Although these methods can lead to good decisions, they are fraught with errors and missteps due to the lack of data for them.
A successful BI program provides various business benefits in an organization. For example, BI enables C-suite executives and department managers to continuously monitor business performance so that they can act quickly when problems or opportunities arise. Analyzing customer data can help make marketing, sales, and customer service efforts more effective. Bottlenecks in supply chain, manufacturing and distribution can be identified before they cause financial damage. HR managers can better monitor employee productivity, labor costs and other workforce data.
BI initiatives also provide narrower business benefits, including making it easier for project managers to track the status of business projects and for organizations to gather competitive intelligence about their competitors. In addition, BI, data management, and IT teams use business intelligence to analyze various aspects of technology and analytics operations.
Business intelligence combines a wide range of data analysis programs designed to meet various information needs. Most are supported by self-service BI software and traditional BI platforms. A list of BI technologies available to organizations includes:
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Special analysis. Also known as ad hoc queries, this is one of the key elements of modern BI applications and a key feature of self-service BI tools. It is the process of writing and executing queries to analyze specific business issues. Although ad hoc queries are usually created quickly, they are often run regularly, with the results of analysis included in dashboards and reports.
Online Analytical Processing (OLAP). One of the early BI technologies, OLAP tools allow users to analyze data across multiple dimensions, which is particularly suitable for complex queries and calculations. In the past, data had to be extracted from data warehouses and stored in multidimensional OLAP cubes, but it is increasingly possible to perform OLAP analyzes directly against columnar databases.
Mobile BI. Mobile business intelligence makes BI applications and dashboards available on smartphones and tablets. Often used more for data visualization than analysis, mobile BI tools are typically designed with an emphasis on ease of use. For example, a mobile dashboard can display only two or three data visualizations and KPIs, so they can be easily viewed on the device screen.
BI in real time. In real-time BI applications, data is analyzed as it is generated, collected, and processed to provide users with an up-to-date view of business operations, customer behavior, financial markets, and other areas of interest. The real-time analytics process often includes data streams and supports the use of decision analytics, such as credit scoring, stock trading, and targeted advertising offers.
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Operational Intelligence (OI). Also called operational BI, it is a form of real-time analytics that delivers information to managers and front-line workers on business operations. OI applications are designed to help make quick decisions and enable faster action on issues, such as helping call center agents solve problems for customers and logistics managers to ease distribution problems.
Software as a Service BI. SaaS BI tools use cloud computing systems hosted by vendors to deliver data analysis capabilities to users in the form of a service typically priced on a subscription basis. The SaaS option, also known as cloud BI, increasingly offers multi-cloud support, allowing organizations to deploy BI applications on different cloud platforms to meet user needs and avoid vendor lock-in.
Open Source BI (OSBI). Open source business intelligence software typically comes in two versions: a free public edition and a subscription-based commercial edition with vendor-supported technical support. BI teams can also access the source code for development use. In addition, some vendors of proprietary BI tools offer free editions primarily for individual users.
Embedded BI. Embedded business intelligence tools put BI and data visualization functionality directly into business applications. It allows business users to analyze data from the applications they use to do their jobs. Built-in analytics features are often included by application software vendors, but enterprise software developers can also include them in native applications.
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Collaborative BI. It’s more of a process than a specific technology. It includes a combination of BI applications and collaboration tools that allow different users to work together on data analysis and share information with each other. For example, users can annotate BI data and analysis results with comments, questions, and highlights by using online chat and discussion tools.
Location Intelligence (LI). It is a specialized form of BI that allows users to analyze location and geospatial data, with built-in map-based data visualization functionality. Location intelligence provides insight into geographic elements in business data and operations. Potential uses include site selection, location-based marketing and logistics management for retail stores and corporate facilities.
Self-service BI and data visualization tools have become the standard for modern BI software. Tableau, Qlik, and Spotfire, now part of Tibco Software, took the lead in developing self-service technology and by 2010 had become prominent competitors in the BI market. after. Almost every major BI tool now includes self-service features such as visual data discovery and custom queries.
BI tools are generally available from dozens of vendors. Major IT vendors offering BI software include IBM, Microsoft, Oracle, SAP, SAS, and Salesforce, which acquired Tableau in 2019 and sell their own tools developed before the acquisition. Google is also in the BI market through its Looker unit, which it acquired in 2020. Other prominent BI vendors include Alteryx, Domo, GoodData, Infor Birst, Information Builders, Logi Analytics, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot, and Yellowfin.
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While full-featured BI platforms are the most common business intelligence technology, the BI market includes other product categories. Some vendors offer special tools for using embedded BI; examples include GoodData and Logi Analytics. Companies like Looker, Sisense, and ThoughtSpot target sophisticated data analytics software. Various
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