Today, it is difficult to achieve great business results without continuous tracking, reliable monitoring and precise business analysis.

Business Intelligence (BI) is a process of collecting and reviewing company business data and their representation in a clear and understandable form, which significantly facilitates managers' choices of business strategies.

The add.BI solution enables integration, transfer, analysis and a quick view of data in a clear graphical form at any moment. It enables you to track company data, information on your competition, market, products, etc., which, among other things, facilitates the detection of weak points and enables business improvements.

Business Intelligence System components

The ETL process includes:

• data collection from external sources (Extract)
• data transformation in compliance with business needs (Transform)
• data loading into the data warehouse (Load)

The ETL process is very important because it determines the method of loading the data into the data warehouse. The name ETL can also be used to designate the loading process into any database.

Data Collection (Extract)

The first stage in the ETL process is the collection of data from various system sources. Each individual system can use a different organization or data format. There are many different formats of data sources; most often, relational databases or unlinked files are used. After data collection has been completed, the data are collected in columns that are often called "fields". Now, each separate row of data can be processed.

Transformation (Transform)

The transformation stage refers to a series of commands or functions applied to the collected data which enable their loading. Some data sources require very little e-data processing. In some cases, however, any processing combination given below can be required:

• Loading of a specific chosen data column
• Translation of the coded value (e.g. the system source saves M for Masculine, and F as Feminine)
• Ensuring the new translated value
• Concurrent joining of data from various sources
• Summarizing additional data rows (e.g. total sales for all regions)

Loading (Load)

During the loading stage, the data is loaded into the data warehouse. The process scope depends on the size of the company or organization. Some data warehouses substitute the old data with the new data, and complex systems can even store data from the past, or track the changes.

Data Warehouses

Data warehouses are databases that represent a company's business in previous periods. Analysts use this data in business analyses on several levels – from strategic planning to the performance assessment of various business units within the company. The data from such databases support the process of analysis, and are usually not used in current business operations.

OLAP Technology

OLAP technology is used most efficiently in data warehouses for current analysis and for providing quick answers to complex analytical questions. Its multidimensional data model quickly accesses the organized data and forwards the information through simple graphical views. The response to the analyst’s query on prior business items provides the possibility of accessing further details. OLAP systems support the company's current business analysis quickly and reliably.

Data Mining

Data mining is one the key links in the data analysis system, or the Business Intelligence system. Data mining enables you to detect hidden patterns in the data collected during the years of operation from various data sources: Business Information systems, CRM systems and other data collection applications. The main target of data mining is to find patterns and connections in the collected data, show their value, transform them into information, and use them in processes (segmentation, forecasting). Data mining allows automated searching for information in this huge amount of data. The objective is to find rules and patterns that allow you to find links among causes and consequences. For example, forecasting based on many facts concerning a specific issue collected in the past. Data mining is used for segmentation (sorting) of clients (which adverts to send and to whom), price optimization, product distribution in a store, finding the right text and image on the Internet, but also for weather forecasts, trends or stock exchange prices.

Most frequently used analytical solutions

Management information system (DIS)

Our DIS system is used for regular and periodic structured reporting (routine or automatic). It enables management to efficiently monitor all company activities.

Business Intelligence System

This is an upgrade to the Management Information System for linking individual intellectual capabilities with the computer’s capabilities in order to enhance the decision-making process.
It enables management to lead the company on a strategic level.

Marketing and market research analysis

The values that were provided to you by a marketing and research agency can be upgraded by creating new values based on existing data and statistical functions.

This system allows the user to compare data with prior information and calculate the trends, taking into consideration multiple periods of time. The data can be linked to internal information.

Client segmentation

The add.BI tool enables simple client segmentation. It provides the possibility of setting logical starting points for the creation of business strategies based on key company competences, desired features and forms of behaviour. This segmentation allows you to estimate the appropriateness and perspective of your business clients when buying specific products or groups of products. Based on segmentation, management is given client segments that are most appropriate for the company, and those with whom the relationship should be attenuated or terminated in the long run.

Cost statement

The cost statement contains the organizational scheme of the company with key business data. This solution includes an application designed for defining keys, groups and balances that determine how data from the General Ledger are distributed in the final statement. The whole system allows the company to create a reliable cost distribution calculation and a quick view of the statement.

Turn-key analytical systems

Through OLAP technology and based on the collected data, turn-key analytical systems enable the user to create table and graphical reports, ad-hoc analyses, to find trends and continually monitor the data.

Secondary sales monitoring system

This system enables users to compare primary sales and those organized through distributors (secondary sales). The OLAP system enables users to analyze and prepare reports at the management and operational level. The company is able to track market conditions, monitor their distributors and create supplier reports.

Power distribution tracking

This system is designed for analyzing power distribution information per individual measurement sites. The data is collected through remote scanning or measurement services. Besides power distribution data, the user can also access distribution site data. This information is linked to power supply information, which enables users to analyze the cost difference, sales and supply by segment. The data are stored in the data warehouse for years, thus enabling users to review prior events, and compare sales and supply growth, the shift from planned values, etc.