Business Intelligence

Business Intelligence is software that supports decision making by using data analysis. Local government handles a great amount and variety of data which not only can, but should be analyzed. This is important both for generating reports and for progressing towards the ideal of the intelligent office. Business intelligence concerns not only forecasting but also up-to-the-minute reporting and the monitoring of the work that goes on in local government.

Business Intelligence for local government is an opportunity for a revolution in local government’s approach to decision making. It has the great advantage of collecting all the data together in one place and making it almost instantly available in the form of straightforward analytical and reporting operations. The system is limited analytically only by the data available at the local government level.

Business Intelligence for local government

These are the major areas covered by Business Intelligence for local government:

General Uses

General Uses

An important element in a system of this type is the central metadata repository that ensures contextualization in business intelligence terms so that the data being processed is correctly understood and effectively used. Access to data must always be possible via the same business metadata no matter which tools are used to prepare the reports or analyses.

Comprehensive Solution

Comprehensive Solution

We offer comprehensive Business Intelligence project roll-outs covering business analyses, designing and building data warehouses, ETL procedures (Extraction, Transfer, Loading), selecting, supplying, integrating and implementing data access tools, and preparing reports analyses and statistics including data mining.

Quality and Analysis

Quality and Analysis

The analytical functions in Business Intelligence projects first of all carry out the basic reporting functions required by the majority of the organization’s users. Next, there are the more complex Business Intelligence subsystems that use statistics packages or data visualization applications designed for specialist analysts.

Metadata

Metadata

An important element in a system of this type is the central metadata repository that ensures contextualization in business intelligence terms so that the data being processed is correctly understood and effectively used. Access to data must always be possible via the same business metadata no matter which tools are used to prepare the reports or analyses.

Solutions

Comarch BIS

Comarch BIS is a Business Intelligence Solution created for local government, and represents an innovative combination of reporting and analytical tools in the user friendly and familiar form of a standard office application.

It has a look very close to these applications too, and this provides an intuitive and user-friendly feel while creating new reports, and while conducting analytical and reporting work whose nature and scope have already been determined. There is no need for specialist IT knowledge! With Comarch BIS, users who have not previously been familiar with data base technology can easily conduct advanced data analyses and present the results, as they become available, in the form of professional reports.

Business and Operational Benefits:
  • makes management more effective by using analyses and reporting at the overall and team organizational levels
  • taking decisions and processing large amounts of data is faster and cheaper
  • employees have rapid access to automatically updated information
  • reporting functionality can be added to other applications

Data Warehouse and Meta Source

It is now possible to compare and aggregate all the data concerning the same issue, which were previously collected in various specialist or departmental systems. It is also now possible to replenish data warehouses with one-off data streams from systems that are no longer used, which has been very difficult to achieve up to now. The data warehouse’s potential also arises directly from its periodical replenishment using ETL processes (Extraction, Transfer, Load). This makes the data uniform by assigning them identical analytical dimensions and storing the information in fact tables as additive measures. But the effective use of even a very well constructed data warehouse is not possible without a concrete understanding – within the business context – of the information collected in the system.

To achieve this it is essential to introduce a central metadata repository, which is a place that contains a substantive description of the data collected in the data warehouse. This repository will also have a special place to collect additional information about data, and include a range of information that will help in accessing the data you are interested in, for example:

  1. Which source system does the data come from?
  2. How long has the data been loaded into the warehouse?
  3. What is the legal status and context of the information collected?
  4. On what paper form and in which version was the information first registered?

The metadata context allows end users to effectively access the information they need and means that they can be sure of the quality of the data they are selecting for analysis. No matter the application they were created in, all the reports or analyses use the same metadata. What is more, since they have a single metadata repository and a single management application (MetaSource), it is a logical step to prepare data sets for reports or analyses in that application and send the finished data base query to the analytical tool. One extremely important question concerns the metadata’s freshness. For this, the system has a two-level procedure for managing metadata renewal.  Information interchange standards based on XML, CWM, and using SQL, mean that the repository and application are easily integrated.