BI processes and tools analyze business data, transform it into meaningful information, and help organizations make better-informed decisions.
Business Intelligence Overview Most companies collect a huge amount of business data every day – coming from their enterprise resource planning (ERP) software, e-commerce platform, supply chain, and many other internal and external sources. To truly benefit from this data and use it to make data-driven decisions, they need a modern business intelligence (BI) system.
Business intelligence refers to the processes and tools used to analyze business data, transform it into actionable information, and help everyone in an organization make better-informed decisions. Also known as a decision support system (DSS), a BI system analyzes current and historical data and presents findings in easy-to-understand reports, dashboards, graphs, charts, and maps that can be shared across the company.
BI is sometimes called "descriptive analytics" because it describes how a business is operating today and how it has operated in the past. It answers questions like "What happened?" and "What needs to change?" – but it doesn't address why something happened or what might happen next.
Business intelligence and business analytics are two terms that are often used interchangeably. Is there a difference? Currently, there is no consensus. That said, a common distinction is that business intelligence focuses on what has happened in the past and what is happening now (descriptive analytics). While business analytics focuses on:
Why something happened (diagnostic analytics) What is likely to happen next (predictive analytics), and What actions need to be taken to ensure the best possible outcome (prescriptive analytics)
Regardless of the label applied, what is important is that organizations have the tools and technology they need to get answers to their business questions, solve the problem at hand, or achieve a specific goal. That's why several major software vendors have begun to combine BI with business analytics into a single cloud platform, giving organizations all the analytics capabilities they need in one place—and making the whole taxonomy discussion moot.
Key benefits of business intelligenceA successful BI program illuminates ways to increase profits and performance, uncover issues, optimize operations, and more. Here are just a few of the many benefits of BI: BI tools help executives, managers, and employees uncover information relevant to their roles and areas of responsibility—and use it to make decisions based on facts, not guesswork.
Gain and maintain a competitive advantage. With timely BI, organizations can quickly identify and act on new trends and opportunities. They can also assess their own capabilities, strengths, and weaknesses compared to competitors and use this information to their advantage. Measure and track performance. BI dashboards make it easy to track key performance indicators (KPIs), track progress against goals, and set alerts so you know where and when to focus improvement initiatives.
Identify and set benchmarks. BI solutions enable organizations to compare processes and performance metrics to industry standards, determine where improvements are needed, set important benchmarks, and track progress toward goals. Identify problems so they can be resolved. With BI, users can identify potential business problems before they cause financial damage—such as production or distribution issues, rising customer churn, rising labor costs, and more.
Operate more efficiently. Business intelligence systems allow everyone to spend less time hunting for information, analyzing data, and creating reports. They can also identify areas of overlap, duplication, or inefficiency between departments or subsidiaries to streamline processes. Make data and reports more efficient accessible to everyone. BI software offers intuitive interfaces, drag-and-drop reports, and role-based dashboards that team members can use themselves—without the need for coding or other technical skills.
Improve customer and employee experiences. BI users can mine data to identify patterns in customer and employee behavior, analyze feedback, and use insights to adjust and improve experiences. Increase revenue and profitability. Ultimately, it leads to a better understanding of where risks and opportunities lie, so teams can make profitable adjustments.
BI reporting—the presentation of data and information to end users in a way that is easy to understand and actionable—is fundamental to any business. Reports use summaries and visuals, such as graphs and charts, to show user trends over time, relationships between variables, and more. They are also interactive, so users can slice and dice the tables or drill down into the data as needed. Reports can be automated and sent on a regular, pre-defined schedule – or ad hoc and generated on the fly.
Search Search tools allow users to ask business questions and get answers through intuitive interfaces. With modern search tools, asking a question can be as simple as asking Google (or even Siri) a question – like (Where are shipping delays occurring?), “Did quarterly sales meet their goals?”, or How many widgets were sold yesterday?
Dashboards are one of the most popular BI tools. They use constantly updated charts, graphs, tables, and other types of data visualization to track predefined KPIs and other business metrics – and provide an overview of performance at a glance in near real time. Managers and employees can use interactive features to customize what information they want to see, drill down into the data for further analysis, and share the results with other stakeholders.
Data Visualization The ability to visualize data and see it in context is one area where BI really shines. Charts, graphs, maps, and other visual formats bring data to life in a way that can be quickly and easily understood. Trends and deviations are more apparent. Colors and patterns paint a picture of the story behind the data in a way that columns and rows in a spreadsheet never could. Data visualization is used in a BI system - in reports, as answers to queries, and in dashboards.
OLAP Online analytical processing (OLAP) is a technology that enhances the data discovery capabilities of many business intelligence systems. It enables rapid, multidimensional analysis of vast amounts of information stored in a data warehouse or other central data store.
Data preparation Data preparation involves collecting multiple data sources and generally preparing them for data analysis. Using a process called extract, transform, and load (ETL), the raw data is cleaned, categorized, and then loaded into the data warehouse. Good BI systems automate many of these processes and allow for the definition of dimensions and measures.
Datawarehouse A data warehouse contains aggregated data from multiple sources that has been cleansed and formatted to be accessible by BI and other analytical tools. Examples of Business Intelligence in Action Today's BI tools make it easy for everyone in an organization to access, analyze, and act on current and historical data. Here are some examples of BI use cases in different business areas: BI for marketing: Marketers can use business intelligence to track campaign results, such as email open rates, click-through rates, and landing page conversions—and then adjust future promotions to make them more effective.
Business intelligence for finance: Finance departments can consolidate financial data and track cash flow, margins, expenses, revenue streams, and more in real time. They can closely monitor the profitability and make decisions that improve the bottom line. BI for HR: HR teams can use BI to track metrics like time and attendance, productivity rates, staff turnover, and engagement. They can use BI to make better hiring decisions, identify training needs, optimize staff schedules, and more.
Business intelligence has been around for over 30 years and was traditionally driven by IT. Questions were asked to IT and answers were provided to the business in the form of a static report. If there were follow-up questions, they were resubmitted to IT and usually put at the back of the queue. This time-consuming process has been replaced by modern BI – which is much more interactive.
Modern, self-service BI tools allow business users to search data themselves, create dashboards, generate reports, and share their findings from any web browser or mobile device – all with minimal IT involvement. Recently, artificial intelligence (AI) and machine learning technologies have made this process even simpler and faster, automating many BI processes, including data discovery and the creation of reports and visualizations.
Business Intelligence FAQ Business Intelligence vs. Data Science Business intelligence focuses on analyzing past and current data to paint a picture of the current state of the business. Data science takes an interdisciplinary approach to analyzing the same data, using statistical algorithms and models to uncover hidden and predictive insights from structured and unstructured data.
Business intelligence vs. data analytics Business intelligence is descriptive, providing insights into what is happening now and what has happened in the past. Business analytics is a general term for data analysis techniques that can also predict what will happen and show what is needed to create better outcomes.
What are business intelligence (BI) tools? Business intelligence tools work together to transform data into useful information. Many of them work “under the hood” to prepare, mine, store, and process data so that it can be accessed by BI systems. Others focus on helping business users interact with data and interpret results through interactive dashboards and data visualizations.
What is a business intelligence analyst? A BI analyst, as the title suggests, gathers and analyzes data and then identifies areas where businesses can improve. They generally maintain tools and databases, develop BI strategies, and communicate findings to stakeholders.
A BI developer is responsible for creating, developing, and managing business intelligence reporting tools and interfaces designed to solve specific problems within the company. A typical BI developer is skilled in software engineering, databases, and data analysis. Responsibilities include translating business requirements into technical specifications, assisting with data model design, creating technical documentation, and more.
Although modern business intelligence tools offer a cutting-edge self-service experience to enable business analysts and technical users a chreiázontai gia na kyvernísoun kai na epekteínoun tin parochí axiópiston etairikón anaforón kai pinákon ergaleíon se kathimerinoús epicheirimatikoús chrístes - ergazómenous pliroforión kai ypéfthynous lípsis apofáseon - chorís aftó to technikó ypóvathro.
Ti eínai i anaforá VI? I anaforá VI eínai to méros tis epicheirimatikís effyḯas pou epikentrónetai stin parousíasi ton analyménon dedoménon me ti morfí pinákon ergaleíon, anaforón kai optikopoiíseon dedoménon pou boroún na synopsistoún kai na koinopoiithoún éfkola se ólo ton organismó.
Ti eínai i optikopoíisi dedoménon? Optikopoíisi dedoménon eínai i anaparástasi dedoménon méso grafimáton, chartón, pinákon ergaleíon, grafimáton kai állon optikón morfón. Voithá tous epicheirimatikoús chrístes na optikopoiísoun táseis, timés ektós anamenómenou évrous kai motíva me mia matiá. I optikí análysi eínai kentrikís simasías gia tin anaforá tis epicheirimatikís effyḯas.
Ti eínai to sýstima ypostírixis apofáseon (DSS)?
Éna sýstima ypostírixis apofáseon anaféretai se opoiodípote diadrastikó ilektronikó sýstima pou boreí na synkentrósei kai na analýsei pliroforíes apó megála sýnola dedoménon, symperilamvanoménon anepexérgaston dedoménon, engráfon kai váseon gnóseon. Ópos ypodilónei to ónoma, ta systímata DSS ypostirízoun tous programmatistés kai tous diefthyntés sti lípsi tekmirioménon apofáseon me vási tis pliroforíes pou emfanízontai méso tis diadikasías análysis.
profitability and make decisions that improve the bottom line. BI for HR: HR teams can use BI to track metrics like time and attendance, productivity rates, staff turnover, and engagement. They can use BI to make better hiring decisions, identify training needs, optimize staff schedules, and more.Business intelligence has been around for over 30 years and was traditionally driven by IT. Questions were asked to IT and answers were provided to the business in the form of a static report. If there were follow-up questions, they were resubmitted to IT and usually put at the back of the queue. This time-consuming process has been replaced by modern BI – which is much more interactive.
Modern, self-service BI tools allow business users to search data themselves, create dashboards, generate reports, and share their findings from any web browser or mobile device – all with minimal IT involvement. Recently, artificial intelligence (AI) and machine learning technologies have made this process even simpler and faster, automating many BI processes, including data discovery and the creation of reports and visualizations.
Business Intelligence FAQ Business Intelligence vs. Data Science Business intelligence focuses on analyzing past and current data to paint a picture of the current state of the business. Data science takes an interdisciplinary approach to analyzing the same data, using statistical algorithms and models to uncover hidden and predictive insights from structured and unstructured data.
Business intelligence vs. data analytics Business intelligence is descriptive, providing insights into what is happening now and what has happened in the past. Business analytics is a general term for data analysis techniques that can also predict what will happen and show what is needed to create better outcomes.
What are business intelligence (BI) tools? Business intelligence tools work together to transform data into useful information. Many of them work “under the hood” to prepare, mine, store, and process data so that it can be accessed by BI systems. Others focus on helping business users interact with data and interpret results through interactive dashboards and data visualizations.
What is a business intelligence analyst? A BI analyst, as the title suggests, gathers and analyzes data and then identifies areas where businesses can improve. They generally maintain tools and databases, develop BI strategies, and communicate findings to stakeholders.
A BI developer is responsible for creating, developing, and managing business intelligence reporting tools and interfaces designed to solve specific problems within the company. A typical BI developer is skilled in software engineering, databases, and data analysis. Responsibilities include translating business requirements into technical specifications, assisting with data model design, creating technical documentation, and more.
Although modern business intelligence tools offer a cutting-edge self-service experience to enable business analysts and technical users to uncover the information needed to address challenges, BI developers still need to They need to govern and extend the delivery of trusted enterprise reports and dashboards to everyday business users - information workers and decision makers - without this technical background.
What is BI reporting? BI reporting is the part of business intelligence that focuses on presenting analyzed data in the form of dashboards, reports, and data visualizations that can be easily summarized and shared across the organization.
What is data visualization? Data visualization is the representation of data through charts, maps, dashboards, graphs, and other visual formats. It helps business users visualize trends, outliers, and patterns at a glance. Visual analysis is central to business intelligence reporting.
What is a Decision Support System (DSS)?
A decision support system refers to any interactive electronic system that can gather and analyze information from large data sets, including raw data, documents, and knowledge bases. As the name suggests, DSS systems support programmers and managers in making informed decisions based on the information presented through the analysis process.