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1 bi business process management technologies. What is Business Intelligence. BI, EIS, DSS, e-business and commerce

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 associated with this. Today we will talk about what Business Intelligence (BI) is in an accessible and in clear language. The topic is undoubtedly huge and cannot be covered with 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 a comprehensive list of next steps.

Article structure

Why is all this needed: from the life of an analyst

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Let’s imagine that we (a certain analyst Petrovich at the supplier Flower) are tasked with assessing the sales of a number of stores (where we supply goods) and each store keeps its own records of goods sold. The reality is that the accounting forms will be filled out by no one knows how or by whom, that is, they will have a different structure and different storage format (some form of tables). This task is shown schematically in the diagram above.

It would seem that the task is not difficult, so let’s consider a straightforward solution: let us 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.

Disadvantages of this approach:

  • it is necessary to support N scripts simultaneously (where N is in the order of thousands);
  • when the structure of store reports changes over time (for example, a store has new employee) it is necessary to search and rewrite individual scripts;
  • when a new store appears, you need to write a new script;
  • when our reporting (supplier Flower) changes, it is necessary to make changes to all scripts;
  • Difficult to debug and support, since stores do not notify about structure changes and do not follow any specifications.

If we level up the whole organization, then we will see that there are even more problems.

What is the challenge: the problem is at the company level

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The manufacturer Flower does not actually work directly with stores, but through some intermediaries. Intermediaries visit stores and directly try to stimulate sales through their actions. Accordingly, they are materially interested parties and the information they give out has to be double-checked.

Fundamentally, the problem looks similar: let’s say we have N stores and K distributors, can we aggregate the stores’ data and compare them with the results of the distributors? (Everyone's data has a different structure and format.)

Here, in addition to tables, we can already encounter a whole zoo of formats, to which distributor reports are added. As a rule, the task is characterized by very low quality data, including duplication, inconsistency and errors. Based on the results obtained and data comparison, the purchasing department makes decisions on how much, to whom and at what price to ship what. That is, the solution to this problem directly affects financial indicators company, which is definitely important.

Let's consider several solution options at the company level:

  • self-written solution: the manufacturing company 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 who can support the software and the quality will directly depend on the hired specialist;
  • To purchase 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 also require significant employee time. Choosing a 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 from the point of view of integration time, price and quality of the solution, the service looks like the best option, since pricing is dynamic and integration is minimal via the web. As a rule, the advantage of enterprise software is its customizability (every 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 it can be found for each individual.

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.
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Let’s summarize the problem: all these are links in one chain

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What is the difference between analytics, data mining and business intelligence (BI)? The former include a set of methods for analyzing already clean data, but in practice, cleaning and converting data into a format convenient for analysis is an important and integral process. Also, in addition to working with data transformation and consolidation, the main task of BI is making business decisions.

Analytical review: BI in Russia 2009

TAdviser center analysts have completed the preparation of an open review of the market for business intelligence (BI) platforms presented at Russian market. On this page you can read the most interesting sections of the review.

Benefits of using a BI system

Business analysis systems solve a very wide range of problems. Thus, the “near horizon” is monitoring, analysis and adjustment of operational goals:

    support for the development of business processes and structural changes in the enterprise;

    the ability to simulate various business situations in a single information environment;

    conducting operational analysis on non-standard requests;

    reducing routine workload on staff and freeing up time for deeper analytical work;

    stable operation with increasing volume of processed information, scalability.

In terms of supporting the strategic development of enterprises, BI systems provide:

    assessing the effectiveness of various business areas;

    assessing the achievability of set goals;

    assessment of the efficiency of resource use, including by subsidiaries;

    assessment operating efficiency, investment and financial activities;

    business modeling and evaluation of investment projects;

    cost management, tax planning, capital investment planning.

Today, according to experts from Gartner, only 15-20% of business users actively work with BI applications, while the rest consider business analysis systems too complex to use. However, the active development of tools for interactive data visualization and the further spread of Internet technologies should soon improve the situation.

According to analysts at MiPro Consulting, the implementation of an independent BI system in an organization provides a number of advantages over the use of analytical tools built into other corporate information systems. Among the advantages of the BI system:

    greater visibility and ease of working with information for business users, including top management;

    the ability to use several analytical solutions for various areas of activity throughout the enterprise, and not within individual departments;

    allows you to extract, analyze and consolidate data from almost any source;

    based on an industrial, supported and developed BI platform;

    has the status of an independent, strategic, business-critical application;

    provides the necessary scalability, efficiency, performance;

    allows you to build and maintain end-to-end procedures and processing processes, unified centralized analytical models and projects throughout the organization;

    contains built-in tools for solving various and varied analytical problems, both from a business and IT point of view;

    provides access to data and analytical tools to more users.

The use of analytical tools built into other corporate information systems, such as ERP or CRM, usually has the following restrictions:

    a limited set of implemented analytical tools that are the same for all users, regardless of their roles and tasks;

    the ability to use only your own internal data for analysis, while information from other systems remains inaccessible, and data from various sources cannot be consolidated;

    the lack of developed built-in tools for analysis leads to the fact that the system is used only to extract the data stored in it, which is then exported and analyzed in Excel;

    ERP and CRM systems, as a rule, have a limited number of users, which “cuts off” from analytics a large number of company employees who would find this information useful and interesting (a significant increase in the number of users reduces the productivity of transactional systems);

    transactional systems usually do not contain all the indicators necessary for analysis and do not include tools such as dashboards, which have already become a standard for presenting analytical information;

    the results of analysis in such systems are usually presented in the form of tabular reports or diagrams, which does not allow one to obtain a detailed and comprehensive picture of the real state of affairs and does not answer many questions that arise;

    the ability to create flexible custom (ad-hoc) queries is limited;

    the use of large volumes of accumulated historical information is limited.

When choosing or updating a system for business analysis, you should consider ways to store and integrate data, visualization and analytics tools.

Data storage

If the company is faced with the task of identifying long-term or periodic trends, that is, users need to analyze historical data coming from various departments over the past 3-5 years, then, most likely, it is necessary to carefully consider the organization of ETL operations for loading data into data warehouses.

If a company or any of its divisions needs to analyze information monthly or weekly, then optimal solution There will be a selection and organization for these purposes (for each of the departments or for solving specific problems) of separate data marts, also using ETL tools.

If the company plans to analyze operational data in a mode close to real time (that is, updated several times during the day), then it may be necessary to abandon the organization of a data warehouse and pay attention to the development of integration tools based on an intermediate virtual layer of metadata with elaboration corresponding interfaces and algorithms (according to the EII principle).

Data Integration

As noted above, if the goal of implementing a BI system is to solve individual, specific problems, then it is advisable to limit ourselves to organizing data marts. In this case, the use of no separate integration algorithms is required.

If, on the contrary, BI is implemented with the goal of obtaining a single, holistic view of general state business, then it’s probably impossible to do without creating a centralized data warehouse and, accordingly, implementing the necessary ETL tools. In addition, to obtain a truly adequate picture of the business, it is necessary to pay special attention to ensuring the high quality of the analyzed data, and this will require the introduction of an expanded set of tools for “cleaning” them - identifying incomplete or erroneous data, duplicate information, bringing data from various sources to a single one format.

If the company places an emphasis on studying operational data, then it is necessary to consider means of replication and access.

Visualization and analytics

Depending on the tasks assigned, as well as on the qualifications of the users, tools for data visualization are selected - control panels, scorecards, reports, OLAP cubes.

For experienced, qualified users, the optimal tool will be OLAP cubes, which will allow them to conduct deep and detailed business analysis, with the required degree of detail.

Users who in their daily activities are faced with the need to accept management decisions, as well as analyzing business performance, are interested in organizing a workplace in the form of a control panel, on which the state of the business as a whole is displayed in the form of visual scales and indicators, with the ability to switch between individual areas of activity.

Ordinary managers need tools to solve their current tasks and monitor progress individual species operations, as well as to control the activities of its employees (each individual employee and the team as a whole). In addition, to organize clear interaction with adjacent departments (or regions), it is necessary to be able to obtain an overview of the progress of interrelated tasks.

Vertical or horizontal solution

There are both horizontal BI solutions on the market, which implement a set of generally applicable tools, and specialized vertical solutions, “tailored” for specific industries or tasks. Both have their advantages and disadvantages.

The advantage of horizontal solutions can be considered their ability to grow with the organization. Such solutions are usually scalable and can cover all areas of activity and all departments large company, and are also easier to change. The downside of such a breadth of capabilities is the need for a longer and more careful setup of solutions and adaptation to specific requirements. Implementation projects are becoming more expensive and the demands on IT specialists are becoming higher.

Vertical solutions, for their part, do not require separate time-consuming and labor-intensive configuration to solve specific problems and to comply with the requirements of industry regulatory organizations (financial, medical, etc.). However, it may turn out that different departments within the same structure will not be able to use a single solution, and several different business analysis systems will need to be mastered and integrated.

Those organizations that currently and in the future plan to engage in their specific activities that require compliance with certain strict regulations are likely to benefit from the implementation of vertical solutions. If there is no confidence in such a commitment to a certain type of activity in the future, and there is a high probability that the company’s specialization will expand significantly, then choosing a vertical BI solution is a certain risk.

IN modern world There are certain classes of software that are aimed mainly at the corporate segment (large and medium business) and accordingly is not widely used. But some software systems have quite interesting functions that can be used not only in small businesses, but also as a personal tool. Here's about one of these software systems and will be discussed in this article.

Note

I am a technical specialist, so the article has a more technical slant. If you want to read information on the product aimed at business users, then go to the IBM offsite.

The main purpose of this article is to show you how to make your first “Hello World” (similar to programming) in IBM Cognos BI.

I also want to note that I have extensive experience in writing step-by-step instructions with screenshots of each step. But this article will not be another step by step instructions, here I want to show the concept of working with the system, and not make another manual.

What is BI?

So, what is a BI system? In three words, this is an advanced reporting system. To make it more clear, below I will list the main functions that modern BI class systems have:
  • ability to connect to various data sources (from an Excel file to a universal ODBC connection)
  • the ability to build both simple reports (such as a graph or table) and complex parameterized reports with a combined structure and reference links (Drill-Trough, Drill-Up/Drill-Down)
  • the ability to transparently work with different data sources (for example, Excel and SQL Server) with full processing of connections between them
  • possibility of interactive work with data (generating reports “on the fly”)
  • the ability to present relational data as multidimensional
  • the ability to distribute access rights using both internal sources authentication, and external (NTLM, LDAP, etc.)
  • the ability to start generating reports either manually or automatically according to a schedule
  • possibility of automatic distribution of generated reports
  • ability to generate reports in various formats (Excel, HTML, PDF, etc.)
In simple Russian language, a BI system is a program that provides the user with convenient tools for analyzing virtually any data (be it an Excel file or an industrial data warehouse).

Possibility of using the BI system as a personal tool

The question immediately becomes, how can you use this system as a personal tool? I will answer from a personal example, I use IBM Cognos BI as a tool for analyzing statistics in my projects and a tool for analyzing home accounting statistics.

Here, of course, you can argue something along the lines of “I can analyze statistics very well with ordinary SQL queries” or “the built-in functions of Excel are quite enough to analyze the entire household accounting,” but “everything is learned by comparison.” As practice shows, it is much easier to simply drag and drop the necessary data elements with the mouse and get the result in finished form than to fiddle with writing SQL queries or reconfiguring Excel functions.

Again, everything written is my personal opinion, with which you do not have to agree.

IBM Cognos BI architecture

The system architecture is relatively simple (as for an enterprise-class system). So, the key element of the system is the IBM Cognos BI server (see diagram below), which works with data sources using a user-created description (called metadata). Further, through Web access, the IBM Cognos BI server provides access to all the main functions of the system.

Conceptual architecture of the IBM Cognos BI complex (the diagram turned out to be very cumbersome)


Stages of working with the system

To make your first report you need to complete several basic steps:
  1. Create a connection to a data source
  2. Generate a description of the data source, i.e. create metadata
  3. Create and publish a metadata package to the IBM Cognos BI server
  4. Create report

Structure of the test data source

Before proceeding with the implementation of the above steps, I want to say a few words about the test data source. On the one hand, the structure of the test data source is relatively simple (as for an industrial data warehouse); on the other hand, it is somewhat more complex than simple Excel sheet. All data in the source is synthetic (generated by algorithms based on random numbers), which is why the aggregate indicators look very even.

As you can see in the diagram above, the test database contains 3 hierarchical dimensions: “Product Group -> Product”, “Continent -> Country -> City -> A store", "Year -> Half-year -> Quarter -> Month -> Date"; 2 flat (one-dimensional) dimensions: “Cashier”, “Regional Manager”; and 2 fact tables: “Sales”, “Sales plan”.
Moreover, the “Cashier” dimension is located in one of the fact tables in a denormalized form, and the “Regional Manager” dimension is tied to the “Country” level of the “Retail Point” dimension by a “many to many” relationship (it is implied that one manager can manage different countries).

Connecting to a data source

Everything in IBM Cognos BI required parameters to connect to data sources are stored in special system objects called “Data Source Connections”. To create a new connection, you need to do a few things: simple steps: go to the IBM Cognos BI portal, go to the “Administration” section, open the “Configuration” tab, select the “Data Source Connections” subsection and click the “New” button data source" (“New Data Source”) in the toolbar. Next, a series of dialog boxes will appear in which you will need to set several parameters, such as connection name, connection type, server, login, password, etc.

Metadata development

Metadata development is one of the most difficult and responsible moments. Both the performance of the system (the speed of generating reports, the correctness of generated results, etc.) and the convenience of developing reports depend on the quality of metadata. But despite the above, the complexity of developing metadata is directly proportional to the complexity of the data source. For example, to build a relational description of our test data source, just launch the metadata creation wizard, click the “Next” button several times, and the metadata is ready.

So, as I wrote earlier, metadata is a description of the data source. In IBM Cognos BI. The foundation of metadata is Query Subject objects and the relationships between them. The “Query Subject” object is a synonym for “View” from relational DBMSs. That is, the “Query Subject” is based on a query to the DBMS that determines the structure of the source object, and the connections between the “Query Subject” are a description of the logical interaction between these queries.

To create metadata in IBM Cognos BI you use separate application IBM Cognos Framework Manager (the only non-Web application in the IBM Cognos BI suite). After launching Framework Manager you will be prompted to create new project(you will need to enter the name of the project and its location in the local file system).

It should be understood that the Framework Manager project (also referred to as the Framework Manager model) is a set of local files with which the local program works, and the metadata package is the result, which is located on the IBM Cognos BI server (if we draw an analogy with programming, then the project is source code, and the package is the compiled application). You can create multiple sets of packages from a single Framework Manager project.

Once the Framework Manager project is created, the best place to start is by running the Metadata Import Wizard (Action -> Run Metadata Wizard...). The Import Wizard will prompt you to select an existing data source or create a new one and allow you to select the necessary objects to import. In the simplest case (for example, when the data source is an Excel file, which in 99.9% of cases contains data in denormalized form), you will need to set the fields of the “Query Subject” object to the correct type of use (the “Usage” attribute) and then work with the model Framework Manager can finish and begin generating and publishing the metadata package. In a more complex version (as in our test example), it will be necessary to check the correctness of the imported relationships between “Query Subject” objects, correct incorrect ones and add missing ones. In more professional options, it is possible to create calculated fields, change the “Query Subject” structure, create a multidimensional representation, define security algorithms, etc.

Create and publish a metadata package

After the metadata has been created, you need to create a metapackage and publish it to the IBM Cognos BI server. As I mentioned earlier, a metapackage is a subset of metadata that is published on the server and with which all Web applications of the IBM Cognos BI complex work. Metapack settings allow you to hide or not publish some metadata objects. For example, in the test metadata there is some “Query Subject”, which affects the logic for processing the source data (is the link between the country and regional director), but is of no value when developing reports; it makes sense to hide such a metadata object at the package level. Or, for example, fields with identifiers, it also makes sense to hide them from metapackage users.

To create a metapackage, you need to open the context menu in the Framework Manager in the “Packages” section and select “Create -> Package”, after which the metapackage creation wizard will appear. After the metapackage is created, the system will immediately offer to publish it on the server. A novice user does not have to delve much into the options of the package publishing wizard (just click Next and Publish). The only thing is that on the last tab (where there will be not a Next button, but a Publish button) there will be a checkbox “Verify package before publishing”, it determines whether the metapackage is checked for logical ambiguities before publishing and displays a list of these ambiguities if they are found. I strongly recommend that you never skip this step and correct any ambiguities you find before publishing.

Generating reports (data analysis)

Now we are slowly approaching the most interesting and regular process - the creation of reports. It so happens that the tools for creating regular reports and the tools for quick data analysis in IBM Cognos BI are the same (despite the fact that in some it is more convenient to carry out quick analysis, and in others it is more convenient to generate regular reports, all of them allow you to save your results in the form reports).

Personally, I prefer to use the IBM Cognos Report Studio tool for all BI tasks. This is the most universal tool that allows you to build reports of virtually any complexity and at the same time provides relatively convenient tools for quick data analysis.

Suppose we need to create a quick report containing sales facts by country, product group and frequency per quarter. This fairly simple report can be made by following these steps:

  1. launch the IBM Cognos Report Studio web application
  2. In the welcome window, click the “create” button
  3. in the list of basic templates, select “crosstab” (“corsstab”)
  4. place the data elements according to the diagram shown below
  5. run the report for execution

After running the report for execution, you will get something like this.

Looking at the resulting report, we can safely say that it is clearly poorly designed, the numbers are not formatted, economic sense frankly doubtful, etc. But all these design flaws can be removed by setting the properties of the corresponding settings elements, and to make the economic meaning more interesting, you can, for example, make a plan/fact analysis.

For example, to make the report shown below (on ready-made metadata), I, as an experienced specialist, spent about 20-30 minutes.

And to completely redesign it into a dark color scheme, I spent about another 10 minutes.

Conclusion

I hope that in this article the reader was able to get general information about BI systems and the principle of their operation. Of course, within the framework of a short article it is impossible to consider in relative detail any of the aspects raised (for example, an entire book could be written on how to correctly form metadata), but I think that if you decide to try, then this article will tell you where to start and what kind of expect results.

Also, I did not touch on some interesting mechanisms and functions at all (for example, the mechanism for representing a relational data source as multidimensional), but this is due to the fact that the number required material(a minimum of theory and a minimum of practice) would warrant a separate article.

A little about licenses

If you decide to purchase the IBM Cognos BI system separately for personal use or small company, then the prices will probably unpleasantly surprise you, but IBM has a special comprehensive system, IBM Cognos Express, which is designed for small organizations, contains several products (including BI) and is much cheaper.

BI systems- This analytical systems, designed for business analysis, which 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 resulting reporting data and its optimal use help in achieving business goals. Complex data analysis is the acquisition of knowledge, a kind of extraction from a mass of sources, including a business line, 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 a company’s business for its administrative resources, 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 the business and in each component 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.

  1. BI tools. These tools are divided into query and report generators, BI tools for analytical processing, corporate BI platforms and BI suites. The bulk of BI tools consists of enterprise BI suites and BI platforms. Query and report generation capabilities are largely being absorbed, or are being replaced by enterprise BI suites. OLAP mechanisms – operational analytical data processing or servers, including relational ones. OLAP engines are the infrastructure for BI platforms and BI tools. Most 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 data warehouse.
  2. BI applications. Applications that are not considered 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 is also possible to quickly contact key indicators by departments and divisions, they are stored in a separate folder located on the dashboard.
  • Multi-layered: all data is displayed in the form of several layers, with each subsequent layer presenting increasingly detailed information regarding indicators, events or processes.
  • Interactivity of BI systems, allowing the user to quickly navigate, including viewing data in various sections and sections, as well as “drilling” data, moving through various types of measurements. Users can directly perform operations on data.
  • Manageability and relevance. Proactivity, which contains a rules engine that allows users to define goals and threshold limits for various types of 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 issued to the monitor - visual and/or audio.
  • Customization of BI systems - individual configuration of the console or dashboard for the level of control 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 applications.
  • 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 a comprehensive objective description of its main players, is a rather non-trivial task. There are many manufacturers on the market that differ from each other in business size, organizational structures, management style, strategy and other factors.

This state of affairs significantly 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, which uses 2 indicators, one of them is the completeness of vision. The other is the ability to implement.

Business Intelligence

Business intelligence or for short B.I.- business analysis, business analytics. This concept most often means software created to help a manager analyze information about his company and its environment. There are several options for understanding this term.

  • Business analytics are methods and tools for building informative reports on the current situation. The purpose of business intelligence, then, is to provide necessary information to the person who needs it at the right time. This information may be vital for making management decisions.
  • Business analytics are the tools used to transform, store, analyze, model, deliver, and trace information while working on problems related to evidence-based decision making. At the same time, with the help of these tools, decision makers should, using suitable technologies, receive necessary information and at the right time.

Thus, BI in the first understanding is only one of the sectors of business analytics in the broader second understanding. In addition to reporting, it includes data integration and cleansing tools (ETL), analytical data warehouses and Data Mining tools.

BI technologies make it possible to analyze large volumes of information, focusing users’ attention only on key performance factors, modeling the outcome of various action options, and tracking the results of making certain decisions.

History of the term

The term first appeared in 1958 in an article by IBM researcher Hans Peter Luhn. Hans Peter Luhn). He defined the term as: "The ability to understand the connections between facts presented."

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 a Gartner analyst) defined Business intelligence as a general term describing "concepts and techniques for improving business decision making using systems based on business data."

Notes

Links

  • Is Business Analytics replacing Business Intelligence? (J-l PC Week/RE No. 41 (599) November 6 - November 12, 2007)
  • BI as a tool for optimizing marketing campaigns (PC Week Review: Business Intelligence, May 2010)
  • Business Intelligence: Today and Tomorrow (Intelligent Enterprise Magazine No. 2 (212), February 2010)
  • Business analytics on Russian soil (J-l PC Week Review: Business analytics, May 2010)

Wikimedia Foundation.

See what "Business Intelligence" is in other dictionaries:

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    business intelligence- noun Any information that pertains to the history, current status or future projections of a business organization … Wiktionary

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    Business intelligence tools- are a type of application software designed to report, analyze and present data. The previously tools generally read data that have been stored often, though, not necessarily, in a data warehouse or data mart. Types of business intelligence tools... Wikipedia

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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… Category: Mathematics Publisher: John Wiley&Sons Limited, eBook (fb2, fb3, epub, mobi, pdf, html, pdb, lit, doc, rtf, txt)

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