BI systems are analytical systems designed for business analysis that are able to combine data from completely different sources information. Data software systems process information and provide a report in a convenient interface for detailed study and subsequent evaluation of the information obtained in the process.
The obtained reporting data and its optimal use help in achieving the set business goals. Data analysis in a complex is the acquisition of knowledge, a kind of squeeze from a mass of sources, including the direction of the business, which can significantly increase the efficiency of the process and significantly reduce costs.
BI systems are a single, extremely transparent and complete source of all data about the company's business for its administrative resource, but mainly for management.
Today, reporting generation and competent analysis are no longer a luxury, but rather a necessity for companies; reporting documentation is required both within a business and in every constituent element of the entire process.
The solutions provided by the BI system are optimal for the preparation of all reporting, including covering all aspects of the business without exception, the presence of such capabilities is already considered mandatory and is considered, together with other basic technologies, as a corporate standard.
- BI tools. These tools are divided into query and report generators, BI analytical processing tools, corporate BI platforms and BI suites. The bulk of BI tools consists of enterprise BI suites and BI platforms. The tools provided for generating queries and reports are mostly being absorbed, or corporate BI suites are replacing them. OLAP engines - online analytical data processing or servers, including relational ones. OLAP engines are the infrastructure for BI platforms and BI tools. Most of the tools are used by users for access as well as analysis, including the generation of reports, which in most cases are located in warehouses, a data mart or an operational warehouse for data.
- BI applications. Applications that are not considered as tools. An example is EIS − Information system for the leader.
Characteristic features of BI systems
- The systems use portal technologies that provide a single entry point to the Internet and the information space of enterprises.
- The interface is presented in the form of a control panel or dashboard displaying several key indicators. This makes it possible to quickly assess the situation. It also provides the ability to quickly access key indicators by departments and divisions, they are stored in a separate folder located on the dashboard.
- Layered: All data is displayed in multiple layers, with each subsequent layer presenting more and more detailed information about indicators, events or processes.
- The interactivity of BI systems, which allows the user to quickly navigate, including viewing data in various sections and sections, as well as “drilling” data, moving through various kinds of measurements. Users can directly perform operations on data.
- manageability and relevance. Proactivity, which contains a rule engine that allows users to define targets and thresholds for various indicators and determine at what data values an alert should be issued. The system provides the ability to set parameters or indicators: if they reach critical values, alarm signals are displayed on the monitor - visual and / or sound.
- Customization of BI-systems - individual configuration of the remote control or dashboard for the control level and user role. Personalization allows the user to independently select objects from authorized lists and arrange data on the dashboard according to their importance.
- Flexible access allows users to intuitively access the data and reports they need from a huge range of results reports and graphs, including remote access and mobile apps.
- Collaboration involves the simultaneous collaboration of a large group of employees, including viewing reports.
Magic quadrants
Competently assessing the state of the modern market, as well as giving an exhaustive objective description of its main players, is a rather non-trivial task. There are many manufacturers on the market, which differ from each other in the size of their business, organizational structures, management style, strategy and other factors.
This state of affairs greatly complicates the process of comparing them, and the direction of movement and development of the market is extremely ambiguous and difficult to predict. To solve this problem, a "magic quadrant" of BI systems was developed, in which 2 indicators are used, one of them is the completeness of vision. The other is the ability to realize.
business intelligence or abbreviated BI- business analysis, business analytics. This concept most often means software created to help a manager in analyzing information about his company and its environment. There are several ways to understand this term.
- Business analytics are methods and tools for building informative reports on the current situation. In such a case, the purpose of business intelligence is to provide necessary information the person who needs it at the right time. This information may be vital for making management decisions.
- Business intelligence is the tools used to transform, store, analyze, model, deliver, and trace information while working on evidence-based decision-making tasks. At the same time, with the help of these tools, decision makers should receive the right information at the right time using the right technologies.
Thus, BI in the first sense is only one of the business intelligence sectors in the broader second sense. In addition to reporting, it includes data integration and cleansing (ETL) tools, analytical data warehouses, and Data Mining tools.
BI technologies make it possible to analyze large amounts of information, focusing users' attention only on key performance factors, simulating the outcome of various options for action, and tracking the results of making certain decisions.
The history of the term
The term first appeared in a 1958 paper by IBM researcher Hans Peter Lun. Hans Peter Luhn). He defined the term as: "The ability to understand the connections between presented facts."
BI as we know it today evolved from decision-making systems that emerged in the early 1960s and were developed in the mid-1980s.
In 1989, Howard Dresner (later an analyst at Gartner) defined Business intelligence as general term describing "concepts and methods for improving business decision making using business data-driven systems."
Notes
Links
- Is Business Analytics replacing Business Intelligence? (j-l PC Week/RE No. 41 (599) November 6 - November 12, 2007)
- BI as a Marketing Campaign Optimization Tool (PC Week Review: Business Intelligence, May 2010)
- Business Intelligence: Today and Tomorrow (Intelligent Enterprise Magazine No. 2 (212), February 2010)
- Business Intelligence on Russian Soil (Journal PC Week Review: Business Intelligence, May 2010)
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See what "Business Intelligence" is in other dictionaries:
business intelligence- (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information and sometimes to the information itself. The purpose of business intelligence a term that dates at least… … Wikipedia
Business Intelligence 2.0- (BI 2.0) is a loose term referring to some new (2006 7) trends and advances in Business Intelligence (BI). The 2.0 version number alludes to version numbers assigned to software even though it is only an abstract concept not a specific… … Wikipedia
business intelligence- Der Begriff Business Intelligence (deutsch etwa betriebswirtschaftliche Erkundung oder Geschäftsaufklärung), Abk. BI, wurde Anfang bis Mitte der 1990er Jahre populär und bezeichnet Verfahren und Prozesse zur systematischen Analyze (Sammlung,… … Deutsch Wikipedia
business intelligence- Der Begriff Business Intelligence (engl. etwa Geschäftsanalytik Abk. BI) wurde Anfang bis Mitte der 1990er Jahre populär und bezeichnet Verfahren und Prozesse zur systematischen Analyse (Sammlung, Auswertung und Darstellung) von Daten in… … Deutsch Wikipedia
business intelligence- Informatique décisionnelle Pour les articles homonymes, voir DSS et BI. L’informatique décisionnelle (Management du système d information, en anglais: DSS pour Decision Support System ou encore BI pour Business Intelligence) désigne les… … Wikipédia en Français
business intelligence- noun Any information that pertains to the history, current status or future projections of a business organization … Wiktionary
business intelligence- / bɪznɪs ɪnˌtelɪdʒ(ə)ns/ noun information that may be useful to a business when it is planning its strategy … marketing dictionary in english
business intelligence- Sammelbegriff für den IT gestützten Zugriff auf Informationen, sowie die IT gestützte Analyze und Aufbereitung dieser Informationen. Ziel dieses Prozesses ist es, aus dem im Unternehmen vorhandenen Wissen, neues Wissen zu generieren. Bei diesem… … Lexikon der Economics
business intelligence tools- are a type of application software designed to report, analyze and present data. The tools generally read data that have been previously stored often, though, not necessarily, in a data warehouse or data mart. Types of business intelligence tools Wikipedia
Business Intelligence Development Studio- (BIDS) is the IDE from Microsoft used for developing data analysis and Business Intelligence solutions utilizing the Microsoft SQL Server Analysis Services, Reporting Services and Integration Services. It is based on the Microsoft Visual Studio ... ... Wikipedia
Books
- business intelligence. Data Mining and Optimization for Decision Making , Carlo Vercellis , Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better… Publisher:
There are a huge number of terms: analytics, data mining, data analysis, business intelligence and the difference between them is not always so obvious even for people who are connected with this. Today we will talk about what is Business Intelligence (BI) in an accessible and understandable language. The topic is certainly huge and cannot be covered in just one short article, but our task is to help take the first step and interest the reader in the topic. The interested reader will also find an exhaustive list for further steps.
Article structure
Why all this is needed: from the life of an analyst
(clickable)Let's imagine that we (a certain analyst Petrovich at the supplier Flower) are tasked with evaluating the sales of a number of stores (where we supply goods) and each store keeps its own records of the goods sold. The reality is that the accounting forms will be filled in no matter how and no one understands by whom, that is, they will have a different structure and different storage format (some form of tables). Schematically, this task is depicted in the diagram above.
It would seem that the task is simple and therefore we will consider a frontal solution: let's say we have N tables and we need to collect them together into one table, then we will write N scripts that convert these tables and one collector that collects them together.
Cons of this approach:
- it is necessary to support N scripts at the same time (where N is in the order of thousands);
- when changing the structure of store reports over time (for example, a store has new employee) it is necessary to search for and rewrite individual scripts;
- when a new store appears, you need to write a new script;
- when changing our reporting (supplier Flower), it is necessary to make changes to all scripts;
- difficult debugging and support, since stores do not notify structure changes and do not follow any specifications.
If we rise to the level of the whole organization, we will see that there are even more problems.
What is the problem: a problem at the company level
(clickable)
The Flower manufacturer actually does not work directly with stores, but through some intermediaries. Intermediaries visit stores and directly by their actions try to stimulate sales. Accordingly, they are materially interested parties and the information they give out has to be double-checked.
Basically, the problem looks similar: if we have N stores and K distributors, can we aggregate store data and compare it with the results of distributors? (All data have a different structure and format.)
Here, in addition to tables, we can already encounter a whole zoo of formats to which distributors' reports are added. As a rule, the task is characterized by very low data quality, including duplication, inconsistency and errors. Based on the results obtained and the comparison of data, the purchasing department makes decisions about how much, to whom and how much to ship what. That is, the solution of this problem directly affects financial indicators companies, which is very important.
Consider several solutions at the company level:
- self-written solution: the manufacturer will need to hire a specialist not in the company's profile and critical software will depend on this specialist. If he leaves, the company will be forced to urgently look for a replacement that can support the software and the quality will directly depend on the hired specialist;
- buy software from a third party, there are three key factors: price, quality and integration time. As a rule, the price and integration time are too high for the average manufacturer, and it also requires a significant amount of time for employees. The choice of supplier is also not trivial;
- SaaS solutions: the methodology is still new to the market and many companies are skeptical about such services.
In general, if we are talking about a small or medium-sized manufacturer, then in terms of integration time, price and quality of the solution, the service looks like the best option because pricing is dynamic and integration is minimal via the web. As a rule, the advantage of corporate software is customizability and customization (each business considers itself unique), but the described task is quite typical and standard for a fairly wide range of companies. Of course, there is no single solution for everyone, but for each individually it can be found.
The process itself at the company level looks similar: data is consolidated, transformed (aggregated) in a certain way and loaded into the system for analysis.
(clickable) 
We generalize the problem: all these are links of one chain
(clickable)
What is the difference between analytics, data mining and business intelligence (BI)? The former include a set of methods for analyzing already clean data, and in practice, cleaning and converting data into a format convenient for analysis is an important and integral process. Also, in addition to working with the transformation and consolidation of data, the main task of BI is decision making for business.
Business loves specifics. If there are sales, then management needs to know exactly how much product was sold today, how much last month, how much more or less it is compared to last year. What is the turnover, how much was the profit, what is the dynamics of costs? Such questions, adjusted for industry specifics, arise in any company.
All the necessary information is in corporate systems, and it is available to managers. In a small company, you can maintain spreadsheets in Excel, in a larger one, you can upload data from numerous systems that help manage production, supplies, warehouse, customer relations and other areas.
But why do businesses need this information? View reports and give the command to optimize everything, reduce costs, and increase profits? In fact, something like this is the case, only the content of managerial decisions depends entirely on the depth of analysis of the available information. And, unfortunately, the analysis of “flat” data, when numbers are considered in only one single section, because there are no others or it takes a long time to calculate, does not allow flexible management of the company.
If top management is concerned about global issues, then line managers are more concerned about the state of affairs in their particular area. How will the profit from each car sent to counterparties A and B in different regions change if the price of fuel increases by 5%? What products need to be purchased by the cafe chain, taking into account the menu, price dynamics, costs, as well as terms and conditions of storage? Is it necessary to transfer the customer service contact center from Moscow to the region - and to which one, taking into account local rental rates, the cost of communication channels, the availability of a qualified work force and medium size wages? What product should be displayed next to the checkout in the supermarket?
By collecting data from disparate applications owned by different departments, the BI system gives the correct answer in uniform format. In fact, it provides visual information about what is happening in the business in the chosen direction and what will happen under the conditions specified by the analyst. Moreover, the system helps to ask the right questions.
The importance of BI is proven by the fact that the world's leading IT vendors are involved in these systems, including IBM, Microsoft, Oracle, SAP, SAS, QlikTech and others. In fact, all analytical reporting of companies is built on the multidimensional data that BI operates on.
What specific tasks do BI systems solve? With their help, a top manager sees profitable and unprofitable lines of business, the dynamics of income and expenses. Receiving the necessary data on certain sections, he can reasonably predict the development of the situation in directions and make decisions.
The sales department has a tool for planning and evaluating the implementation of plans. The reports show the effectiveness of each manager and the dynamics of sales to each client. The analysis also allows you to identify the dependence of sales on a number of related factors: the season, the presence of competitors in a particular area, etc.
Answers to these questions, as a rule, are needed quickly and without the participation of the IT service. To solve such problems, there are BI (Business Intelligence) systems. This is a class of applications that has been actively developing for a long time and allows you to take all the parameters that are important for business and build analytical reports on them independently, instantly and in any context.
Financiers can use the BI system to plan budgets, receive consolidated financial statements, analyze cash flow using the system, and control borrowers' repayment of loans.
Leaders production units and logisticians use business intelligence to develop production plan, management of deliveries, warehouse stocks, relations with suppliers, for the analysis of traffic routes Vehicle etc.
Once a business reaches a scale where Excel spreadsheets are no longer analytics because they don't help navigate a multidimensional world, they wonder which analytics system to use. However, as we mentioned at the very beginning, business loves specifics. And the question actually sounds something like this: “How will my profit change if one or more conditions of activity change, and who will help me decide what needs to be done to increase it?” For the answer, you should contact BI.
In Russia, companies from different sectors of the economy turn to solutions based on BI systems. According to the chief editor of the analytical publication TAdviser Alexander Levashov, BI systems are most in demand among customers from the financial sector, trade and the public sector. Also, these solutions are in demand among representatives of the pharmaceutical industry, the food industry, are used in the energy and telecommunications segments.
Dmitry Glushkov, consultant of the analytical department of Softline, also draws attention to the industry-specific demand for BI: “The largest number of BI projects are now being implemented in three industries: the financial segment, retail and the public sector. At the same time, in each of the segments, business intelligence makes it possible to solve specific problems.
For example, BI systems allow banks and insurance companies to automate the processes of collecting and generating reports, providing top managers with up-to-date information about the main performance indicators of organizations. This makes it possible to quickly make the necessary decisions to maximize financial performance.
segment retail analytical tools also provide many application possibilities. These are sales analysis, like-for-like reports, data visualization on various geographical maps, analysis of the grocery basket.
As for the public sector, requests for the implementation of forecasting mechanisms, automation of budgeting processes, and the construction of tools for monitoring various indicators are typical here.”
Is it different Russian market BI from western? According to Alexander Levashov, there are no major differences in terms of penetration or consumption of BI solutions. An important feature is that our country has developed its own expertise in the development of software for business analytics (we are talking about the Prognoz company). Few countries can boast of this.
Marketers acquire a tool for a specific, in numbers, analysis of the market as a whole and by sector, studying competitors, customer behavior, forecasting supply and demand, determining the most effective tools sales and analysis of the effectiveness of marketing campaigns.
