Business Intelligence has a very broad meaning. The system is mostly defined as „integrated set of tools, technologies and software products used to collect data from different diffused sources, to integrate, analyze and share them”. Thanks to the ability to connect and analyze data including the whole area of a company activity (see more: ETL Process) according to the accepted business operations they allow to manage the knowledge in an organization, symulate and forecast the consequences of operations and improve decision-making processes thanks to interactive reports and management dashboard. In ERP systems the way of data storage is optimized to manage current operations. However, in case of analitical queries it can cause significant elongation of processing time. The generated results are most often presented in a two-dimensional table which in case of advanced analysis containing bigger amount of variables may not be sufficient for accurate analysis. See more: What benefits does the implementation of Business Intelligence give?

Market Basket Analysis imitates human brain work – it associates components, unites them and finds mutual relations. This is the base of a unique technology, which makes doing all calculations in real time possible, in the same moment when a user is clicking. Searching for some information is as simple as in the popular browser Google. It is possible to make the analysis very fast, without need to reduce it to the predefined query paths only, always seeing all the dependences between the data. While building the classic BI system it is necessary to define relations between the data, especially in the hierarchy.

Creating a data model, it is almost always indispensable to analize them step by step to consider and configure all the relations. In the next step one should add essentials hierarchies, which are caused by the earlier analysis. They give the opportunity to drill. Every new need brings changes into the model and causes manual addition of relations and hierarchies. In Associative Logic all the data is automatically conected with each others. If any relation is unnecessary or wrong, it is removed. It speeds up the work during the unite data modeling to introduce them in reports.

As you can see on scheme, between selected objects all possible relations are defined. Thanks to this – choosing e.g. one of the administrative disctricts, the user automatically achieves information about its regions, sold products and the data of sales representatives working in this area.

Dashboards presents main data concerning the organization. They have a lot of interactive graphics, i.a.: sliders, drop-down menu, widgets, which allow to develop possibility of data analysis. They make possible e.g. analysis of KPI (Key Performance Indicators).
These tools allow to analyse the functioning of a company, to increase managers decisions pertinence, they facilitate management of information flow. They also allow to monitor the company results. Thanks to all of these the efficiency of the whole organization increases.

Thanks to the KPI (Key Performance Indicators) a user can check the level of business processes implementation (e.g. sale) and evaluate the effectiveness of their realization (e.g. cost, time, quality). KPI enable the efficient analysis of the results, thereby it is possible to quickly react to the emerging problems (e.g. fall in sales) or monitor the efectiveness of the introduced changes.
KPI are often presented as indicators or arrows, what you can see below.

ETL process (Extraction, Transformation and Loading) integrates data which come from different sources to ensure high quality and coherent data. This process is central to construct and maintain data warehouse. Only properly integrated and transformed data will be useful in business analysis.
See more: Which data sources can you connect with Business Intelligence system?
See more: Is it possible to successively add new source systems to Business Intelligence system?

DWH (Data Warehouse) is a base where the data is stored, in a way that makes fast and efficient analysis possible. The results can be used in decision-making process.

OLAP (Online Analytical Processing) – a class of IT systems to suport tactical and strategic organization activities, in opposite to transactional systems which are supporting current operating activity. There are different types of OLAP in use. The most popular implementation of this type of system is data warehouse, often called relational OLAP – ROLAP. Data warehouse is based on the same solution as transactional database of more denormalize structure – like e.g. a star or a snowflake. Intentional denormalization allows to efficiently query big groups of data, e.g. to make reports. Multidimensional cube is also the OLAP type of solution. Mostly it is another layer of abstraction set on data warehouse, where the data is storaged in files of special multidimensional structures. MOLAP has its own engine of processing, which is an for intuitive and fast way of quering data in mentioned files. Earlier calculated aggregations are also storaged in multidimensional structures. Thanks to the database engine does not have to process the data on high level of details. In fact OLAP is often identified with multidimensional analytic cube. A lot of tools like SQL Server let us create a hybrid version between relational and multidimensional OLAP.

In-memory is one of leading technologies in IT development systems. Until now traditional IT tools, connected with databases and Business Intelligence, were based on downloading the data from files located on the hard drive. During the years speed of readout has increased, thanks to indexes and introduction SSD memories. In-memory greatly increased effectiveness. This disk is used to store, not to process, data. During reading from the disk, all data is loaded to the memory. Then data processing is going on. RAM memory is much faster than all availables hard drives. It is because of the overhead time elimination, what cause that data is generated faster. Using tools based on the In-memory technology, the use of RAM memory increases, so machines mus be equipped with an adequate amount of memory. This technology is used e.g. in Qlik View, Microsoft Power Pivot or SAP HANA.

The basic difference between these technologies is a place where the data is storaged and processed. The traditional approach claims that there exists the central data repository, where client tools are strictly connected with the server repository.
Self-Service BI (often called as Personal BI) is something different. It doesn’t need central object in its architecture, but the role of client tools is enhaced. Using these tools it is possible to create analytical models. The user can also modify existing solutions or even create them, without need to involve a lot of people. Self-Service BI, in contrast to the traditional approach, doesn’t require expensive investment in machines. But it also doesn’t guarantee “the only one version of the truth” and easy documents sharing.

The existence of several different solutions of the same business area can cause a real implementational problem. However, both solutions may exist simultaneously giving an opportunity to eliminate defects and emphasize advantages. One of the hybrid solutions is rearing Pover Pivot model on Sharepoint server. Thereby, a lot of final users can use a specific model, modify it and share with others.

Presently a lot of software providers allow to create Self-Service BI solutions, e.g. Microsoft Self-Service BI or QlikView.
Self-Service BI conception in Microsoft technology is based on MS Excel.

Business Intelligence Systems are great fulfillment of existing database and reporting systems. Reports in ERP systems are often insufficient and don’t allow for advanced and cross-sectional analysis, especially when report should include data from different sources. Integration of exisisting tools with BI system open an acces to all data, it allows to epitomize of the company situation. The unified data is a great source of reports and dashboards. They can be easily distributed to many consumers. A cooperation with professional business partner is indispensable. It will help to identify all necessary attributes and key measures for indicated analysis and represent them clearly It will facilitate decision-making process by giving the right to inspect the key operational information. It also allows to define critical problems.

Business Intelligence system implementation doesn’t require intervention of any used systems. An additional configuration of systems in sometimes necessary to connect them with BI tools.

Business Intelligence systems providers know how important the integration of data from different systems is. They use a lot of dedicated drivers to connect directly with other systems and databases. A list of available drivers is growing with every new Business Intelligence system version. The list, however, depends on every specific solution.

This decision is a very complex task. The implementation of a new system will have significant impact on the functioning and organization of a company. The choice of a provider should be preceeded with the company’s needs analysis. It is very important to specify funcional requirements of the system and determine its meaning in organization. Then it is possible to create an offer inquiry and mechanism of offers evaluation. The solution can may include tools from differents software producers. For example, the data warehouse may be created with the use of Microsoft tools and the dashboards – Qlik View. when choosing appropriate tools, the best idea is to consult with the experienced Business Intelligence specialists. They will help to choose optimal and well integrated set of components.

IT market is very dinamic and new Business Intelligence systems constantly appear. It is very hard to indicate which system is the best one. See more: How to choose Business Intelligence software provider?

Some of Business Intelligence providers have prepared models adapted to different lines of business, which significantly shortens the time of their implementation. BI specialists present implementations examples in the form of descriptions or case studies.

In most cases Business Intelligence systems have both web and desktop tools. The tools targeted at analysts and used for making reports and analyze data, almost always have web interface. The tools targeted at people working on integrating or modeling data mostly have desktop interface.

It depends on the project size. The implementation of BI software can last from a few weeks to several months. A lot of companies, after the BI implementation, start to observe benefits and decide to extend their system by adding new areas and functionality.

Which business area should be developed/extended first?
Business Intelligence systems should be implemented according to the priorities and importance of data sources. Starting from the implementation of the functions most important for company. The most popular is sales area and financial module.

High quality of data in Business Intelligence has significant impact on further data analysis and successful implementation. The preparation of data is a very complex process. The data from many source systems have to be properly cleaned and integrated. Cleaning the data is based on standarization of the forms of records and data types. The integration process involves combining of the previously cleaned data. To do this experts use ETL/DQ processes.

Business Intelligence systems implementation is a complex process. Its effectiveness depends on many factors. The most important one is the team experience, solid requirement analysis, a proper choice of technologies and training for the future system users.

The key performance indicators of Business Intelligence implementation strategy are:

– utility – solution fulfill it is function
– efficiency – system is working quickly and efficiently
– reliability – system works without failure
– accordance with the expectations – the system corresponds with the users expectations

Moreover, before the implementation of BI system it is possible to specify KPIs. It will help to evaluate the results of implementation. Quantitative and qualitative measures can be used.

Typical threats connected with the implementation of Business Intelligence systems are:

– badly estimated costs and time of realization
– badly estimated implementation aims
– lack of client commitment
– lack of employees responsible for implementation
– lack of support for project and low awareness of changes
– communication problems
– employees non approval of software

Main problems, with the biggest impact on project, usually appear in the beginning of realization. Their consequences lengthen the time of achieving aims and they have negative impact on the involvement and the realization of the project.

Business Intelligence specialists implement the system with company employees within the earlier established area. They can implement it completely or just the selected parts. After the contracted work the specialists give professional training concerning using the self-service software. Technical support to some extent is also provided (SLA contract, post-implementation support, helpdesk ect.).

Designing and implementing BI systems is a very complex process. It requires a great amount of experience and knowledge in the topic of IT system constructions and analytical tools. People form IT departments not always have the same type of skills as external BI specialists. Using their experience and skills developed during many professionals trainings, BI specialists can successfully implement Business Intelligence systems. However, a cooperation with IT department is very important. Client’s IT team can be significantly involved in the implementation work.

The cooperation during the entire project is indispensable to succeed. The most important part in implementation is the analysis of reporting/business requirements for BI system. It is necessary to speak with the responsibles to clarify their expectations. It is very important to establish infrastructure and an access to source systems. An evident part of project, with the cooperation of both teams, is the solution receipt stage. Trainings for final users and administrators is also one of the most importants stages in the whole process.

Designing and implementing BI systems is a very complex process. It requires a great amount of experience and knowledge in the topic of IT system constructions and analytical tools. People form IT departments not always have the same type of skills as external BI specialists. Using their experience and skills developed during many professionals trainings, BI specialists can successfully implement Business Intelligence systems. However, a cooperation with IT department is very important. Client’s IT team can be significantly involved in the implementation work.

ETL tools are part of Business Intelligence systems. They allow to integrate the data from different sources using dedicated drivers. Thereby these tools can be connected with distinct IT systems (e.g. ERP, CRM), data bases and external files (e.g. Excel and CSV files). When it is necessary to integrate the data from sources which don’t have predefined drivers, it is possible to use ODBC or OLE DB interface.

ETL tool selection is a very important part of Business Intelligence system designing. It is worth to benefit from specialists’ experience who have done a lot of implementations and know this type of tools.

All implemented Business Intelligence systems allow to import and export data from Excel – both older and newer versions. Most frequently, the tools used in ETL service have a predefined driver to operate .xls and .xlsx files because it is a very common data source.

One of the Business Intelligence systems construction metods is an incremental method, which assumes system extension by adding new sources and functionalities.
This approach enables to implement priority system elements, so users have an acces to the key functions and the most relevant data, then they can extend it by adding additional components. System extention concerns also the appearance of new data sources. It is strictly connected with ETL processes rebuilding, which allows to take advantage of many different data sources (see more: Which data sources can you connect with Business Intelligence system?).
You may exchange one source system with another without need to rebuild the whole BI solution. It is enough to correct some ETL processes (in most cases reports and managers dashboards can remain unchanged). It is a very imporatnt BI system feature which ensure the continuity of reporting in organization.

A high quality of data is crucial for Business Intelligence analysis. Therefore, there appear more and more solutions supporting the data management process (such as Microsoft SQL Server Data Quality Services). It helps solve problems of completeness, accuracy, uniqueness and integrity.

While creating a report the most common drill directions (beyond new BI tools, are programmed which use e.g. associative logic; see more: associative logic). Report drilling is one of the ways of effective data binding in BI system (achieving detailed data – drill down, more general data – drill up or analyzed in different way).

It depends on data quantity. Report generation can last from fractions of a second to several minutes (when generating detailed report on a long period). BI tools are based on the fact that the source data, downloaded from the source system, are prepared especially for the reports. Therefore “best practices” minimize report generating time. On the other hand, if no of these practices can be used (what happen extremely rare), it is possible to generate report in advance using the tools for scheduling. The final user can receive the most recent report when needed.

Reports created through Business Intelligence systems create a possiblity to analyze trends. Advanced BI tools, apart from historical trends presentation, provide predictioning which is based on more or less complex mathematical models.

The majority of delivered solutions give opportunity of exporting reports to PDF.

Using Business Intelligence it is possible to analyze a lot of company areas, e.g.:

– financial area – sale costs and income, profitability analysis
– marketing area – income from advertising, markups, orders time
– customer service area – clients profitability
– production area – results comparision, problems and delays identification
– payroll data area – payment, personal data

It depends on the project size. The implementation of BI software can last from a few weeks to several months. A lot of companies, after the BI implementation, start to observe benefits and decide to extend their system by adding new areas and functionality.

Business Intelligence systems should be implemented according to the priorities and importance of data sources. Starting from the implementation of the functions most important for company. The most popular is sales area and financial module.

High quality of data in Business Intelligence has significant impact on further data analysis and successful implementation. The preparation of data is a very complex process. The data from many source systems have to be properly cleaned and integrated. Cleaning the data is based on standarization of the forms of records and data types. The integration process involves combining of the previously cleaned data. To do this experts use ETL/DQ processes.

Business Intelligence systems implementation is a complex process. Its effectiveness depends on many factors. The most important one is the team experience, solid requirement analysis, a proper choice of technologies and training for the future system users.

The key performance indicators of Business Intelligence implementation strategy are:

– utility – solution fulfill it is function
– efficiency – system is working quickly and efficiently
– reliability – system works without failure
– accordance with the expectations – the system corresponds with the users expectations

Moreover, before the implementation of BI system it is possible to specify KPIs. It will help to evaluate the results of implementation. Quantitative and qualitative measures can be used.

Typical threats connected with the implementation of Business Intelligence systems are:

– badly estimated costs and time of realization
– badly estimated implementation aims
– lack of client commitment
– lack of employees responsible for implementation
– lack of support for project and low awareness of changes
– communication problems
– employees non approval of software

Main problems, with the biggest impact on project, usually appear in the beginning of realization. Their consequences lengthen the time of achieving aims and they have negative impact on the involvement and the realization of the project.

Business Intelligence specialists implement the system with company employees within the earlier established area. They can implement it completely or just the selected parts. After the contracted work the specialists give professional training concerning using the self-service software. Technical support to some extent is also provided (SLA contract, post-implementation support, helpdesk ect.).

Business Intelligence tools are dedicated for business users. Easy and fast operation, transparent design and intuitive interface let the analysts and managers efficiently search for necessary information and make the data analysis. It is worth to remember that correct implementation requires specialist knowledge in the field of Business Intelligence. It deals with data cleaning layer and their integration and preparation in warehouse structures (to facilitate and speed up the reporting).

Business Intelligence system doesn’t require programming knowledge and is dedicated to business users. In BI systems user can create reports of different complexity levels. IT companies offer trainings acquainting with basics of creating reports and techniques used to construct more complex reports.

Business Intelligence systems are designed for business users. Software producers deliver as simple and intuitive tools as possible. These systems offer a lot of data analysis possibilities – from simple to complex operations such as complex statistical and predictive functions. Their usage doesn’t require advanced software knowledge.

Business Intelligence systems producers employ different ways of license managing. That is why we help to choose the right system, its version and possible ways of license. Some of tools available in the market allow to use license per server (without any user limits) or license per user (a limited number of named or simultaneously active users). Which gives many opportunities of choosing the license. A lot of Business Intelligence systems offer data export to different formats (e.g. .pdf, .xls). Therefore, a bigger group of users can have an access to reports, unless the license prohibits.

To use Business Intelligence systems the basic computer literacy is necessary. The most important is the subject matter knowledge (What do I expect from report?), not the technical one (How to make report?). (see more: Do you need information technology knowledge to make analysis?)
The use of Business Intelligence tools is presented in very simple and accurate way during training. Participants practise and learn how to use system efficiently.

ETL tools are part of Business Intelligence systems. They allow to integrate the data from different sources using dedicated drivers. Thereby these tools can be connected with distinct IT systems (e.g. ERP, CRM), data bases and external files (e.g. Excel and CSV files). When it is necessary to integrate the data from sources which don’t have predefined drivers, it is possible to use ODBC or OLE DB interface.

ETL tool selection is a very important part of Business Intelligence system designing. It is worth to benefit from specialists’ experience who have done a lot of implementations and know this type of tools.

All implemented Business Intelligence systems allow to import and export data from Excel – both older and newer versions. Most frequently, the tools used in ETL service have a predefined driver to operate .xls and .xlsx files because it is a very common data source.

One of the Business Intelligence systems construction metods is an incremental method, which assumes system extension by adding new sources and functionalities.

This approach enables to implement priority system elements, so users have an acces to the key functions and the most relevant data, then they can extend it by adding additional components. System extention concerns also the appearance of new data sources. It is strictly connected with ETL processes rebuilding, which allows to take advantage of many different data sources (see more: Which data sources can you connect with Business Intelligence system?).

You may exchange one source system with another without need to rebuild the whole BI solution. It is enough to correct some ETL processes (in most cases reports and managers dashboards can remain unchanged). It is a very imporatnt BI system feature which ensure the continuity of reporting in organization.

A high quality of data is crucial for Business Intelligence analysis. Therefore, there appear more and more solutions supporting the data management process (such as Microsoft SQL Server Data Quality Services). It helps solve problems of completeness, accuracy, uniqueness and integrity.

BI systems are composed of different tools providing effective data processing and sharing results for users on different levels of organization. BI tools allow for:

– easy access to data from different sources
– trends analysis and divergent values monitoring
– making key decisions in a real time
– analysis the effectiveness of the employees work
– improvement of managers and decision-makers work
– data analysis at different levels of detail at different time
– improvement of information receiving methods by fast and easy reports delivering to decision-makers
– reliable data collection at one place

Due to the data dispersion derived from non-integrated systems, the consolidation of companies with the use of a spreadsheet is very difficoult. Business Intelligence system can significantly help by reporting automation and reducing the risk of error. BI system, collecting data from the whole capital group, ensures coherent, correct and reliable reports. The implemented solutions can be developed by adding additional modules supporting the most advanced consolidation processes.

Business Intelligence system implementation gives benefits for whole organization. The most important are:

– data consolidation and analysis at different levels of detail
– efficient sales and financial analysis
– improving analytical processes
– increasing management efficiency
– supporting of achieving the business goals
– data presentation using diagrams
– time reduction of analysis and making important decisions

BI analysis are possible in Excel since the release of Microsoft Power Query as an add-in to the software in 2013 (currently it is an integral part of Excel). Analysts received a tool that allowed to significantly simplify and automate the generation of reports. In 2020, the BI Excel ecosystem consists of several additions:

– Power Query (responsible for ETL processes, i.e. data retrieval and transformation),
– Power Pivot (data model creation)
– PivotTables and Power Map.

Skilful use of BI – Excel add-ons allows extensive and reliable data analysis. Excel’s shortcomings are most noticeable in data visualization, the inability to build dashboards.

Business Intelligence systems offers more possibilities than Excel. They allow to conduct more detailed analysis, search for information easily and present results in more effective and transparent way. BI ensures the operation on the integrated data from the whole company and gives high level of safety. Using Business Intelligence system, the company has all the data in one place, not in non-integrated files.

A lot of Business Intelligence systems allow to save the reports results to Excel files. Some of the systems give opportunity to export not only the whole report, but also its individual components, such as tabs, charts, diagrams ect. It is worth asking a question – what for? It makes sense in order to provide the data to external users. Otherwise, the export is superfluous. BI system effectively substitute Excel funcionality and often has more advanced possibilities of data presentation than Excel. (see more: Does Business Intelligence works like Excel?)

All implemented Business Intelligence systems allow to import and export data from Excel – both older and newer versions. Tools used for ETL service have predefined driver to operate .xls and .xlsx files because it is a very common data source.

The Excel add-on for data visualization (Power View) was not a successful solution and Microsoft decided to create an independent software for data analysis and visualization (Power BI), which basically replaces the other add-ons. Similar to Excel, it uses Power Query and models data in DAX (Power Pivot), but the similarities end there. Data visualization, interactive reports and management dashboards are not the only advantages of Power BI over Excel BI. Data can be retrieved from various sources in real time, Microsoft has improved the creation of relationships between tables, supplemented the supported data sources and enabled access to online reports (in the PRO version, it is possible to edit the permission level for different people).

Power BI is a self-service tool, it’s implementation time is fast (compared to other BI tools), allows for independent data analysis, creating attractive visualizations and does not require specialized skills. Thanks to numerous automation and an interface consistent with Office 365 software learning basic analyzes does not require much work.