Data warehouse (DW) is a structured set of data accumulated from a wide range of sources within a company, used for fast, easy and comfortable reporting and data analysis. DW provides cleaned and sorted data, which are always available on many different combinations. DW combines historical and operative data, data from social networks and sensors and so on. Data can be loaded to DW either in real time or by nightly updates. Thanks to DW, accessing the data we need is easier, faster and flexible.
Reporting and data analysis systems
The system of data analysis (may exist independently or be part of data warehouse) creates flexible environment for analyzing and visualizing data, for predicting future trends and making forecasts. For additional benefit, you get clearer business processes, unified terminology and unified interpretation of data.
Performance management systems
The base of performance management system is Balanced Scorecard (BSC). This is a method of management, which relates daily activities of a company to its vision and strategic goals through a selection of carefully selected performance indicators (measures). For selecting the key performance indicators, the performance of a company is evaluated from four different perspectives: financial management, clients, business processes, personnel and development of the company. The system gathers the information about the most important performance indicators from departments or business areas to a central dashboard.
Data quality analysis and systems
There are always biases and numerical inconsistencies in data, having influence on values of management decisions and to the development of the entire organization. These must be identified, analyzed and fixed or hided before a report is produced. Data quality analysis gives a good review of data and potential data errors in database, analyzes why the data errors occur and gives suggestions for fixing and reducing their impact. We need to think about the data quality analysis before building data warehouse solutions, i.e. before the data errors start to influence the accuracy and usefulness of data analysis reports. The value of seeing the current picture and possible problems with the data gathered in the organization, obtained by performing data quality analysis, can be made permanent through implementing a data quality monitoring system.
Statistical analysis and data mining
Data mining is the process of sorting through large data sets to establish important relationships. The purpose of data mining is to find answers to the following questions:
- Who are the most profitable clients now and who should be in the future?
- Which clients most likely leave and go over to the competitors?
- How it is possible to maximize the profit per client?
- Who are the best candidates for buying new products?
Resta professional consultants and trainers can help you to choose and implement software for statistical data analysis and data mining. We can help you to form a suitable sample of clients or data, choose data analysis approach and accurate statistical methods for obtaining the desired results.
Clinical trials give the best results when they are carefully planned. The team of Resta will help to put together the plan of trial and to estimate how many participants are needed. Using typical data analysis methods for medical statistics, it is possible to find important information from the data. We help to identify suitable approaches for data analysis and most appropriate statistical methods obtaining reliable results.