home Exchange rates Business intelligence systems example of work. Business Intelligence (BI) systems for business analysis

Business intelligence systems example of work. Business Intelligence (BI) systems for business analysis

AT modern world there are certain classes software, which is focused mainly on the corporate segment (large and medium business) and therefore not widely used. But some software systems have quite interesting functions that can be applied not only in the field of small business, but also as a personal tool. That's 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 bias. If you want to read information on the product, focused on business users, then you are offsite IBM.

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 a lot of experience 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 clearer, below is a list of the main functions that have modern systems BI class:

the 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 work transparently with different data sources (for example, Excel and SQL Server) with full processing of relationships between them
the possibility of interactive work with data (on-the-fly reporting)
the ability to represent relational data as multidimensional
the ability to distribute access rights using both internal sources of authentication and external (NTLM, LDAP, etc.)
the ability to start generating reports both manually and automatically according to a schedule
Possibility of automatic distribution of generated reports
the ability to build reports in various formats (Excel, HTML, PDF, etc.)

In simple Russian, 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).

Ability to use 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 statistics for home accounting.

Here, of course, one can object, something in the spirit of “I analyze statistics perfectly with ordinary SQL queries” or “the built-in Excel functions are quite enough to analyze all home accounting”, but “everything is known in comparison”. As practice shows, it is much easier to simply drag the necessary data elements with the mouse and get the result in finished form than fiddling with writing SQL queries or reconfiguring Excel functions.

Again, everything written is my personal opinion, with which you are not required to agree.

IBM Cognos BI Architecture

The architecture of the system is relatively simple (as for an enterprise-class system). So, key element system is an IBM Cognos BI server (see diagram below) that 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 follow several basic steps:

Create a data source connection
Generate a description of the data source, i.e. create metadata
Create and publish a metadata package to the IBM Cognos BI server
Create report

Structure of the test data source

Before proceeding with the implementation of the steps described above, 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 complicated than a simple one. excel sheet. All data in the source is synthetic (generated by algorithms based on random numbers), because of this, 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 -> Trade point”, “Year -> Half year -> Quarter -> Month -> Date”; 2 flat (one-dimensional) measurements: "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 linked to the “Country” level of the “Outlet” dimension by a many-to-many relationship (it is understood that one manager can manage different countries).

Connecting to a data source

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

Development of metadata

The development of metadata is one of the most difficult and crucial moments. The quality of the metadata determines both the performance of the system (the speed of generating reports, the correctness of the generated results, etc.) and the convenience of developing reports. 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, it is enough to launch the metadata build 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 the metadata is the "Query Subject" objects and the relationships between them. The "Query Subject" object is a synonym for "View" from relational DBMS. That is, the "Query Subject" is based on a request to the DBMS that determines the structure of the source object, and the links between the "Query Subject" are a description of the logical interaction between these requests.

IBM Cognos BI uses a separate IBM Cognos Framework Manager application to create metadata (the only non-Web application in the IBM Cognos BI suite). After launching the 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 a Framework Manager project (also referred to as a Framework Manager model) is a set of local files that a local program works with, and a metadata package is a result that is located on an IBM Cognos BI server (if we draw an analogy with programming, then a project is source code, and a package is a compiled application). You can create multiple sets of packages based on a single Framework Manager project.

Once the Framework Manager project has been created, it's best to start 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 will allow you to select the necessary objects for import. In the simplest case (for example, when the data source is an Excel file, which in 99.9% of cases contains data in a denormalized form), you will need to set the fields of the “Query Subject” object to the correct usage type (“Usage” attribute) and work with the model Framework Manager, you can finish and start building and publishing the metadata package. In a more complex version (as in our test case), it will be necessary to check the correctness of the imported relationships between the Query Subject objects, correct the incorrect ones, and add the missing ones. In more professional versions, it is possible to create calculated fields, change the structure of the "Query Subject", create a multidimensional (multidimensional) representation, define security algorithms, etc.

Create and publish a metadata package

After the metadata has been created, the metapackage must be generated and published to the IBM Cognos BI server. As I mentioned earlier, a metapackage is a subset of metadata that is published on the server and that all Web applications of the IBM Cognos BI suite work with. The metapackage 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 source data processing logic (is the link between the country and regional director), but is of no value when developing reports, so 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 “Packages” section in the “Packages” section and select the “Create -> Package” item, after which the wizard for creating a metapackage will appear. After the metapackage is created, the system will immediately offer to publish it on the server. A novice user can not go deep into the options of the package publishing wizard (just click the Next and Publish buttons). 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 “Verify package before publish” checkbox, it determines whether the metapackage should be checked for logical ambiguities before publication and displays a list of these ambiguities if they are found. I strongly recommend that you never skip this step and correct any ambiguities found before publishing.

Reporting (data analysis)

So we slowly got to the most interesting and regular process - this is the creation of reports. It so happened that the tools for creating regular reports and tools for quick data analysis in IBM Cognos BI are the same (despite the fact that some are more convenient for quick analysis, while others are more convenient for generating 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 versatile 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 the fact of sales by country, commodity group and frequency per quarter. This fairly simple report can be made by following these steps:

launch the IBM Cognos Report Studio web application
in the welcome window, click the "create" button
in the list of basic templates, select "crosstab" ("corsstab")
place the data elements according to the diagram below
run report for execution

After running the report for execution, the result will be something like this.

Looking at the resulting report, we can safely say that it is frankly badly designed, the numbers are not formatted, the economic meaning is 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, to 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 re-register it in a dark color scheme, I spent somewhere else 10 minutes.

Conclusion

I hope that in this article the reader has been able to get general information about BI systems and how they work. Of course, within the framework of a short article, it is impossible to consider in any detail any of the affected aspects (for example, you can write a whole book about 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 expect a result.

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) will draw on a separate article.

A little about licenses

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

Analytical review: BI in Russia 2009

Analysts of the TAdviser center completed preparation of the open review of the market of the platforms for the business analysis (BI) presented on Russian market. On this page you can read the most interesting sections of the review.

Benefits of using a BI system

Systems for business analysis solve a very wide range of tasks. Thus, the “near horizon” is monitoring, analysis and adjustment of operational goals:

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

the possibility of modeling various business situations in a single information environment;

conducting operational analysis on non-standard requests;

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

stable operation with an increase in the volume of processed information, the possibility of scaling.

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

evaluation of the effectiveness of various business areas;

assessment of the feasibility of the goals set;

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

assessment of the effectiveness of operating, investment and financial activities;

business modeling and evaluation of investment projects;

cost management, tax planning, capital investment planning.

To date, according to experts from Gartner, only 15-20% of business users are actively working with BI applications, while the rest consider systems for business analysis too complicated 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 introduction of an independent BI system in an organization provides a number of advantages over using analytical tools built into other corporate information systems. Some of the benefits of a BI system include:

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

the ability to use several analytical solutions for different areas of activity on an enterprise-wide scale, and not within individual departments;

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

is 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 to solve various and varied analytical tasks, both from a business and IT perspective;

provides access to data and analytical tools to more users.

The use of analytical tools built into other corporate information systems, for example, the ERP or CRM class, as a rule, has the following limitations:

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 are then exported and analyzed in Excel;

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

transactional systems usually do not contain all the indicators necessary for analysis, do not include tools such as dashboards, which have already become the 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 obtaining a detailed and comprehensive idea of the real state of affairs and does not answer many questions that arise;

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

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

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

Data storage

If a 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 they should think carefully about organizing ETL operations to load data into data warehouses.

If a company or any of its departments needs to analyze information on a monthly or weekly basis, then optimal solution there will be allocation 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 near real-time mode (that is, updated several times during the day), then it may be necessary to abandon the organization of the data warehouse and pay attention to the development of integration tools based on the intermediate virtual metadata layer with elaboration appropriate interfaces and algorithms (according to the EII principle).

Data integration

As noted above, if the purpose of implementing a BI system is to solve individual, specific tasks, then it is advisable to limit ourselves to organizing data marts. In this case, the use of any separate integration algorithms is not required.

If, on the contrary, BI is implemented in order to obtain a single, holistic view of the overall state of the business, then it is probably impossible to do without creating a centralized data warehouse and, accordingly, introducing the necessary ETL tools. In addition, in order 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 their "cleaning" - identifying incomplete or erroneous data, duplicate information, bringing data from various sources to a single format.

If the company focuses on the study of operational data, then you should consider means of replication and access.

Visualization and analytics

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

For experienced, qualified users, OLAP cubes will be the best tool, 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 adopt management decisions, as well as business performance analysis, are interested in organizing a workplace in the form of a control panel, which displays the state of the business as a whole in the form of visual scales and indicators, with the ability to switch between individual areas of activity.

Ordinary managers need funds to solve their current tasks, control the progress of certain types operations, as well as to control the activities of their employees (each individual employee and the team as a whole). In addition, in order to organize clear interaction with related departments (or regions), it is necessary to be able to get an idea of the progress of the implementation of interrelated tasks.

Vertical or horizontal solution

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

The advantage of horizontal solutions can be seen as their ability to grow with the organization. Such solutions are usually scalable and can cover all areas of activity and all departments of a large company, and are also easier to change. The downside of this breadth of possibilities is the need for a longer and more thorough adjustment of solutions, adaptation to specific requirements. Implementation projects are becoming more costly and the demands on IT professionals are becoming higher.

Vertical solutions, for their part, do not require separate lengthy and time-consuming 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 it may be necessary to master and integrate several different systems for business analysis.

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

Everyone big business and most medium-sized structures are faced with the problem of providing management with inaccurate data on the state of the company. The reasons may be different, but the consequences are always the same - wrong or untimely decisions that adversely affect the effectiveness of financial transactions. To avoid such situations, a professional business intelligence or BI system is designed ( from English. - business intelligence ). These high-tech "assistants" contribute to building a system of managerial control of every aspect within the business.

At its core, BI systems are advanced analytical software for business analysis and reporting. These programs can use data from various sources of information and provide them in a convenient form and section. As a result, management gets quick access to complete and transparent information about the state of affairs of the company. A feature of the reports obtained with the help of BI is the ability of the manager to independently choose in which context to obtain information.

Modern Business Intelligence systems are multifunctional. That is why in large companies they are gradually replacing other ways of obtaining business reporting. Their main capabilities include:

Connections to various databases;
Formation of reports of varying complexity, structure, type and layout with high speed. It is also possible to set a schedule for generating reports on a schedule without direct participation and data distribution;
Transparent work with data;
Ensuring a clear link between information from different sources;
Flexible and intuitive configuration of access rights for employees in the system;
Saving data in any format convenient for you - PDF, Excel, HTML and many others.

The capabilities of business intelligence information systems allow the manager not to depend on the IT department or his assistants to submit the required information. It is also a great opportunity to demonstrate the right direction of your decisions not with words, but with exact numbers. Many large network corporations in the West have been using BI systems for a long time, including the world-famous Amazon, Yahoo, Wall-Mart, etc. The above-mentioned corporations spend decent money on business intelligence, but the implemented BI systems bring invaluable benefits.

The benefits of professional business intelligence systems are based on principles that are supported in all advanced BI applications:

visibility. The main interface of any business analysis software should reflect key metrics. Thanks to this, the manager will quickly be able to assess the state of affairs in the enterprise and begin to do something if necessary;
Customization. Each user should be able to customize the interface and function keys in the most convenient way for themselves;
Layering. Each data set should have several cuts (layers) to provide the detail of information that is needed at a particular level;
Interactivity. Users should be able to collect information from all sources and in several directions at the same time. It is necessary that the system has the function of setting alerts by key parameters;
Multithreading and access control. The BI system should be able to implement simultaneous work of a large number of users with the ability to set different access levels for them.

The entire IT community agrees that business intelligence information systems are one of the most promising areas for the development of the industry. However, their implementation is often hampered by technical and psychological barriers, uncoordinated work of managers and the lack of prescribed areas of responsibility.

When considering the implementation of class BI systems, it is important to remember that the success of the project will largely depend on the attitude of the company's employees to the innovation. This applies to all IT products: skepticism and fear of downsizing can thwart all implementation efforts. Therefore, it is very important to understand how the business intelligence system makes future users feel. The ideal situation will be when the company's employees will treat the system as an assistant and a tool for improving work.

Before starting a project to introduce BI technology, it is necessary to conduct a thorough analysis of the company's business processes and the principles of managerial decision-making. After all, it is these data that will be involved in the analysis of the situation in the company. It will also help to make a choice of a BI system along with other main criteria:

Goals and objectives of the implementation of BI systems;
Requirements for data storage and the ability to operate with them;
Data integration functions. Without using data from all sources in the company, management will not be able to get a holistic picture of the state of affairs;
Visualization capabilities. For each person, the ideal BI analytics looks different, and the system must meet the needs of each user;
Universality or narrow specialization. In the world there are systems aimed at a certain industry, and universal solutions, allowing to collect information in any context;
Requirement for resources and price for software. The choice of a BI system, like any software, depends on the capabilities of the company.

The above criteria will help management make an informed choice among the variety of known business intelligence systems. There are other parameters (for example, data storage structure, web architecture), but they require skills in narrow IT areas.

It is not enough just to make a choice, buy software, install and configure it. Successful implementation of BI systems of any direction is based on the following rules:

Data correctness. If the data for analysis is incorrect, then there is a possibility of a serious system error;
Full training for each user;
Rapid implementation. It is necessary to focus on the correct formation of the necessary reports in all key places, and not on the ideal service for one user. Adjust appearance report or add another section for convenience, you can always after implementation;
Understand the return on investment in your BI system. The effect depends on many factors and in some cases is visible only after a few months;
The equipment should be designed not only for the current situation, but also for the near future;
Understand why the BI implementation was started, and do not demand the impossible from the software.

According to statistics, only 30% of company executives are satisfied with the implementation of BI systems. Over the long years of the existence of software for business analysis, experts have formulated 9 key mistakes, which can reduce efficiency to a minimum:

Implementation of BI systems - important step to help take your business to the next level. But this will require not only a fairly large infusion of finance, but also the time and effort of each employee of the company. Not every business is ready to competently complete the project of implementing a business analysis system.

At most enterprises, sales and production are still falling, credit resources are becoming more expensive, and consumption is decreasing. All this requires urgent changes in the company, and in particular, cost reduction. That is why, now the manager is required to use modern IT tools. One can even say that the use of modern analytical systems (Business Intelligence) is today one of the conditions for the company's survival.

Business Intelligence - Information Driven Management

Back in the eighties of the last century, the first analytical applications appeared that were intended to support decision making. These tools were very different from transactional accounting applications, which were primarily focused on operations. The amount of information that was generated through the use of such systems gave a serious impetus to the development of a new class of applications designed to support management decision-making. These systems have been called online analytical processing systems ( Online Analytical Processing, OLAP). Already in the early nineties, the Gartner Group introduced the term business intelligence, which is now widely used to refer to analytical applications.

« Business Intelligence (BI) has evolved into a strategic initiative and is now recognized by CIOs and business leaders as a means to improve enterprise performance and innovation,” said Andreas Bitterer, vice president of research at Gartner.
The company's survey of over 1,000 CIOs ranked BI as a Technology Priority in 2008. At the same time, interest in business intelligence has been maintained for more than three years in a row. And only this year showed a change in the trend of interest in this topic, in 2009 business intelligence became the eighth in terms of priorities, and this is due to the fact that most foreign companies have already included this instrument in the practice of their activities.

However Russian practice The use of BI tools is still in its infancy, and for the next couple of years you can not worry about the decline in interest in these technologies. After all, unfortunately, despite the rather high level of existing automation of Russian companies, most CEOs still do not have a computer at their workplaces, and certainly do not make decisions based on the analysis of information from analytical systems. The ERP systems implemented in many companies made it possible to plan the company's resources and make it more transparent. But this did not make it easier to make decisions at the highest level, and such a quality of a leader as intuition is still the most important.

Oddly enough, but the main result of the past boom in the automation of Russian companies is the cost of millions of dollars, while strategic decisions are still made the old fashioned way. Many CEOs are now asking the question, "We've spent millions on automation, but why can't I see tangible results in my activities." In most cases, this is due to the fact that in many companies there is a CIO in charge of information technology, but there is no CIO. Indeed, now most companies have accumulated "oceans of information", and in order to process it and apply it to support decision-making, specialized technologies are needed -.

Practice shows that at present the volume of stored and analyzed information is growing at a tremendous speed in all industries, while some of them can be called clear leaders. Banks, insurance companies, telcos, and retailers process terabytes of data, and the right use of this data determines the level of customer satisfaction, and hence competitive advantage. Those who are the first to be able to convert the accumulated data into the information necessary for making informed decisions will be able to win the competition.

At the same time, along with the volume of information, the speed of its generation, as well as its diversity, is growing, which requires a strategic approach to information management and the implementation of BI tools. After all, choosing technologies for solving today's problems without taking into account future needs, you can face their unsuitability in a couple of years. Another difficulty for most companies is the low quality of data, and hence the lack of reliability of the information received. After all, if information is entered into the system once a month and from unreliable sources, then the decision made on the basis of such information is likely to be “posthumous”. In such a situation, it is impossible to work the old fashioned way; sooner or later, specialized tools for verifying and analyzing information will be needed.

That is why the analytical company Gartner has noted worldwide interest in analytical applications for several years, and the Russian market has seen a huge number of projects for the implementation of these tools. This is due to the fact that the implemented ERP systems do not yet have the return that everyone was counting on. And now only BI technologies make it possible to automate the collection and analysis of information, as well as its presentation in a form convenient for management.

The tasks of information analysis are so diverse that, in addition to industry specialization, BI tools have differences in the class of tasks they solve. At the same time, no matter how much you would like to solve all the problems with a single and universal BI tool, this is impossible. Currently, there are many different BI tools on the Russian market that cover certain needs of companies. However, buying a BI tool often does not give the expected results, because you need not only to buy a toolkit and deploy it in your company, but also devote a lot of time to the quality of existing data and ways to verify it. Unfortunately, many companies do not yet have that single version of the truth that is necessary for making a decision.

That is why, buying tools Business Intelligence (BI) will not lead the company to success. For the effective implementation of BI tools in a company, it is necessary to create the appropriate conditions, and first of all, this is the support of managers. After all, the users of these applications should be the first persons of the company, and if this is not the case, then the tools will most likely “gather dust on the shelf”. Breaking the habit of managing the old fashioned way is what needs to be done in a company, and it is not so easy.
In addition to changes in management, it is necessary to harmonize measures for the use of BI tools with the existing business strategy companies.

What and when to measure? On what indicators should strategic and tactical decisions be based? Who is responsible for specific indicators? Without answers to these questions, the implementation and development of BI tools can go the wrong way.

And of course, for the rapid and efficient deployment of business analysis technologies, it is necessary to determine the responsible employee and the corresponding center of competence, otherwise nothing will come of it. After all, in order to bring together all the needs of many functional customers and create an appropriate information infrastructure, it is necessary to constantly work and make many managerial decisions at the level of top managers. The strategy for using BI should go through the entire company and start from the processes of collecting primary data and ending with the processes of making strategic decisions, otherwise there will be no trust in the information received, which means that analytical information will not be used in decision making.

Implementation of Business Intelligence

In fact, for the successful implementation of BI technologies in a company, it is necessary to create BIG team – Business Intelligence Governance, – i.e. center of competence for information management at the level of the entire company. The creation of such a center of competence for BI allows you to centralize the responsibility and competence for information management in the company, as well as to put things in order among the tools used by BI.

The BI Competence Center can have a standard structure that brings together business customers and employees whose area of responsibility lies in the field of management information technology and information (CIO, information architect, business intelligence, etc.). At the same time, the following can be distinguished as the main tasks of the competence center: managing the needs of business customers, choosing information management technologies, methodological guidance, standardizing work and used technologies, accumulating competence, data quality management.

The ways of organizing such a center of competence can also be different:
Functional subdivision reporting to the IT subdivision;
department subordinate to operational management;
distributed structure with subordination to CEO;
a virtual organization.

The form of organization can be any, the main thing is that the company should have people responsible for information management and business analysis. According to Gartner, most often the BIG team is located in the IT department, which does not always allow you to give the necessary priorities to these works. After all, the creation of such a center of competence is primarily necessary to centralize responsibility for information management and the use of BI applications. Therefore, it is most effective if the competence center reports directly to the general director or his deputy. Wherein fundamental question, from the point of view of the effectiveness of the created unit, is the assignment of appropriate powers to it. In practice, these structures exist in no more than one percent of Russian companies, which once again confirms the low maturity of Russian management in the field of information management.

To understand the development strategy of this area, the first result of the work of the created competence center should be a strategy in the field of information management and the use of business analysis tools. Without such a systemic view, there is a strong possibility that business customers will use different BI tools with overlapping functionality, which in turn will increase costs and not achieve the expected benefits. Now it makes no sense to spend money without defining a clear development strategy, otherwise there will be a zoo of BI applications that will be unmanageable.

The current trends in the development of the BI applications market are in the growth of industry and functional specialization of BI platforms, as well as an increase in their number. Thus, a clear understanding of their needs and the choice of appropriate BI applications is necessary on the part of the company, and given the increase in the number of users of BI tools in the company, this is becoming more and more critical.

As already noted, the past wave of implementations of ERP systems in Russian companies created a platform on the basis of which, with the help of BI tools, you can and should select the information necessary for making decisions. Therefore, with the deterioration of the internal situation, companies turned their attention to the issues of their internal organization and efficiency, and began to actively use BI applications, which used to be more of a toy for business analysts than a real tool.
One problem that now needs to be addressed when implementing BI tools is the quality of data in a company. Analyst company Gartner offers the following classification of data quality by levels: optimized, managed, proactive, reactive, knowledgeable. At the same time, the higher the quality of data in the company, the greater the benefit for the business, which in turn allows you to move from management based on intuition to management based on good feeling.

Benefits of Business Intelligence

The following are the advantages of using BI applications. Primarily, Business Intelligence (BI) reduces the cost of information management, as it eliminates redundant data extraction processes and the existing duplication of information. BI systems save employees time due to more efficient information processing, and the ability to analyze large amounts of data reduces the number of employees required to process information.

As business intelligence tools are deployed in a company, users begin to perform analysis and make predictions, and then the benefits of BI applications become even more noticeable. For example, application Business Intelligence (BI) at a strategic level can allow reaching new market, change the direction of the company or launch a new line of services.
From the point of view of the development of BI applications, the development trend of these systems is aimed at increasing specialization. There are already real-time business analysis systems Business Activity Monitor (BAM) that allow you to provide decision-making data that appeared a few minutes ago. These systems are of great help to the middle level of management, as they allow them to support the adoption of operational decisions. Also, business process analysis systems - Process Intelligence, which allow monitoring and analysis (controlling) of executable business processes, as well as analysis of the organizational effectiveness of employees, stand out in a separate class.

This intersection of business process management technologies (Business Process Management) and business intelligence systems (Business Intelligence) allows not only to see the problem, but also to find its cause, which in turn makes it possible to correct it before the consequences occur.
As a conclusion, it can be noted that the market for BI tools is growing, and serious acquisitions are taking place on it. Major players such as SAP, Microsoft, Oracle buy the most promising BI technologies and integrate them into their solutions. And this is a clear sign of the demand for BI tools and an indicator that in the coming years the development of companies will go in this direction.

Andrey Koptelov, Magazine General Director

Translation

When trying to evaluate various BI platforms, it is often difficult to understand where is the myth and where is the truth, since each vendor positions its product as “the best on the market”, citing hundreds of subjective reviews flooding the Internet as an argument. If you want to figure out which tool is right for your company without scrolling through hundreds of pages of “honest” opinions, then below is what you need.

We'll take a look at the most popular platforms such as QlikView, Klipfolio, Tableau, and Power BI and compare their key features: usability, price, ease of installation, support, work with different data types, and more. So go ahead!

All this, together or separately, opens up huge opportunities for analyzing various metrics, creating and customizing unique visualizations in order to ultimately extract useful information for business from any data.

The platform also focused on compatibility with various devices, from smartphones and tablets to Smart TVs in conference rooms.

Peculiarities

Klipfolio is best suited for real-time monitoring and control of continuous data streams, when data dynamics are important and important decisions need to be made quickly.

Key Features

Integration of various data sources into one report.
Unlimited number of potentially connected users.
Management of rights and restrictions on access to important information.
Availability on mobile operating systems (iOS, Android, BlackBerry, Windows).
Flexible REST connector for connecting special data sources.
Support for Excel, CSV, JSON, XML, etc.
The ability to add convenient annotations to reports that will be visible to end users.
Automatic KPI setting system.
Ability to easily add threshold indicators to charts.

The convenience of use

You can build dozens in Klipfolio various types charts, including pie charts, bar charts, area charts, and many more combinations. Also, a user who knows HTML and CSS can create their own, unique visualizations by applying all the necessary components to the dashboard through a WYSIWYG editor, and more complex chart elements can be added using various formulas and functions. Thus, with the help of Klipfolio, you can present information in almost any form, but first you need to think about how to prepare the data.

Price

As one of the oldest players in the BI industry with vast experience, today Klipfolio is betting on its cloud solutions. Klipfolio Dashboard (as a SaaS) is offered at a per user price starting (with some variations) at $19/month. This plan can be customized and add additional options. A 14-day trial period is also possible.

tableau

Another big platform is Tableau. Like most BI tools, Tableau specializes in data analysis through data visualization. It is easy to create interactive dashboards that allow you to explore the dynamics, trends and structure of data using convenient and simple, but no less effective charts.

Like many other services, Tableau supports many different sources data organized in file format (CSV, JSON, XML, MS Excel, etc.), relational and non-relational databases (PostgreSQL, MySQL, SQL Server, MongoDB, etc.) and cloud systems (AWS, Oracle Cloud, Google BigQuery, Microsoft Azure).

The key difference between Tableau and its competitors lies in its special function - data mixing - combining data from different databases and sources. Tableau also allows multiple users to work on a real-time report at the same time. Also, the platform implements several ways to share reports: 1) by publishing them on the Tableau server; 2) via e-mail Tableau Reader; 3) via link access. This diversity adds flexibility and removes many restrictions.

Distinctive features

Tableau has the widest visualization capabilities: the platform's rich library includes word clouds, bubble and tree charts that allow you to achieve a higher level of understanding of your data and its context.

As already mentioned, Tableau dashboards are extremely flexible. The main functions of the service allow you to place elements on the dashboard in an incredible way and combine and overlay them in any way, which is very useful in the era of workplace ergonomics.

Tableau is quite friendly to beginners, the platform is aimed at those who have not yet gone into the technical details of the visualization process. This goal is achieved through an intuitive interface: everything you need is most often achieved in no more than 2 mouse clicks, filters are easy to find, and all operations are clearly documented.

Tableau is easy to work with, not only from the point of view of development and reporting, but also from the point of view of the end user - management. Additional filters, creation of new parameters, simple and understandable data interactivity - all this significantly speeds up decision making and makes them more efficient.

Key Features

Excellent opportunities for distribution of reports and dashboards.
Support for over 30 data types.
Mixing data from different sources.
Integration with R.
The most active community of users who create thousands of educational videos, blogs and forums.

The convenience of use

Amazing convenience and ease of use - main reason why Tableau is considered one of the easiest BI services to learn, and it performs best when analyzing structured information. Import data, build beautiful graphics, share it and publish it in the public domain - no other platform can provide users with such a wide range of possibilities with such simplicity. Moreover, a huge number of different manuals and guides practically nullifies the likelihood of encountering any difficulties.

Price

Tableau has 3 different products with 3 different pricing: Tableau Desktop, Tableau Online, and Tableau Server. Detailed information can be found.

Tableau Desktop is for individual users and costs $999 per person per year and $1,999 for corporate use including support. In the first case, it is supposed to connect up to 6 data sources, and in the second - up to 44.

Tableau Online is a web-based cloud platform that is free to use, but on the condition that all solutions are stored on a shared server and published to the public. The private version costs $500 per year per user.

Finally, Tableau Server is a monolithic business tool for companies that manage their servers and want to have complete control over their data flows and security. However, such pleasure will cost $ 10,000 per year for 10 users, and support will cost an additional 25% of this amount.

Power BI

Power BI is an online service developed by Microsoft for business intelligence with the ability to connect various data sources and third party applications. The platform has a web interface that allows you to create customized visualizations, and using a desktop application, you can standardize and clean data. Interestingly, there is also a mobile version of Power BI available on various operating systems to make decisions on the go.

Power BI is simple and minimalist, yet powerful and stable at the same time. Like any other software, it has both pros and cons.

Distinctive features

What makes Power BI different from other solutions?

Firstly, this is a Microsoft product, which means that it follows a philosophy, principles and architecture similar to other products of the IT giant. The interface of the program will be familiar to Windows users.

Secondly, belonging to Microsoft gives another advantage: Power BI is closely related to the main products of the company, such as MS Excel, Azure Cloud Service and SQL Server.

Generally speaking, Power BI was created to extend the functionality of MS Excel and pump it to a new level and use it to solve problems in which it was not previously involved.

Key Features

There is a free basic version, which allows you to first try working with Power BI.
Supports many ways to import data (streaming data, cloud services, Excel workbooks, and third-party applications).
Interactive dashboards with real-time data changes.
A simple API to integrate Power BI into your applications.
There are several ways to share reports and dashboards.
Multi-platform support (web, desktop or mobile app).

The convenience of use

The interface is simple and will be understood by anyone familiar with Windows (that is, almost everyone), so working with Power BI is usually a pleasure. Many buttons and functions look similar to MS Excel and other MS Office products.

Visualizations are created in the good old drag-and-drop way. All you need to create any graph is to click on the required element and drag it to empty place in the report. The same principle works when choosing what data to visualize - just select a piece of data and place it on the place where the graph is located.

Price

Microsoft Power BI is considered a high-quality business intelligence tool, and many are attracted by a fairly democratic pricing policy. It includes two options: a free version of the service with limited features and a volume license of Power BI Pro with a full range of features.

The free version is available to any individual user and has the following characteristics: 1 GB memory limit, 10,000 rows/hour streaming data processing rate, along with limits on updating and sharing reports.

Power BI Pro costs $9.99 per user per month and increases the memory limit to 10 GB per person along with a speed of 1M rows/hour. There is also the possibility of accessing data sources directly, linking them to these companies through the Data Connectivity Gateway. Finally, advanced tools become available joint work, such as Office 365 Groups, Active Directory groups, and the data directory.

Now, to structure everything that was said above, here is a comparative table of all the considered platforms:

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