When talking about user types in terms of data warehousing, we should keep in mind the target group who uses our BI-applications. Dashboards, reports and cubes are addressing a bunch of employees. These are either more focused on the decision-making process or responsible for the running business. Therefore, aligning applications to end-users demands as well as technical experience is very essential for a sustainable BI solution. Plenty of sources are classifying users in different ways. This article will provide an insight into some possible clustering.
As a result of a best practice BI-project the online journal SearchBusinnesAnalytics has publishes a pyramid who classifies different user types according to their sophistication (chart 1) (http://searchbusinessanalytics.techtarget.com/news/2240036691/Categorizing-business-intelligence-users). Users are separated in four groups and related to demands written on the right-hand site next to them. The first and biggest group consists of casual users, who are consuming standard reports, dashboard and scorecards. Their aim is to easily gain an overview about the running business processes including KPI and metrics. The second group is called investigators. OLAP cubes are presenting predefined data structures and are providing multidimensional analysis. The investigators are used to tools which support this type of data enquiry. They want to solve a specific problem and can empower themselves. In contrast, explorers are not challenged by a business use case. They have access to the source systems and can retrieve mandatory data for explorative analysis purposes. Statistical methods are used as well as non-SQL tools for BI-applications. Aggregated and categorized data is often preferred to increase velocity and reduce complexity. The last category of user types is named investors. Members are specialized in advanced mathematical methods and comprehensive exploration tools. They are the innovation drivers and good at finding new fields of data prediction.
Furthermore, there are other schemes, which are simple to understand and applicate. Gluchowski identifies only three fields of user types. The information consumer, business analyst and the specialist. The information user is similar to the casual user described before. He just wants to access prepared business information easily. The usage isn’t focused on analysis just on frequent reporting. The business analyst is like the investigator who wants step by step disaggregation. The explorer or investor roles are referencing the specialist who is familiar with advanced mathematical methods and tools. Moreover, technical consultants differentiate between business users and power users. Here self-service-BI or managed-self-service-BI is implemented.
Building a BI-platform is very complex and not easy to deploy. Acceptance and integration variety is demanding high costs. Thus, a concept of user experience is mandatory to suite the needs of internal and external clients. Segmentation of user types is often realized by some characteristics. Wayne W. Eckerson states four dimensions that are essential for estimating the type of usage (http://download.101com.com/pub/TDWI/Files/TDWI_Monograph_KeystoEBI_June2005.pdf). Business roles, analytical need, access and delivery preferences and technical and analytical literacy. Creating a chart (chart 2) with depth of analysis and breadth of reporting enables companies to identify fields of BI-authors and -consumers with same attributes. Power users can either be in the role of a creator who develops parametrized reports or multidimensional analysis. Or he can consume these applications for his own needs in the role of an user. Getting an overview of the explained indicators helps the enterprise to focus on the necessary features a complex data warehouse solution has to provide.
Ultimately, a classification of users is very important for the company and the technical orientation of BI solutions. Understanding the user´s needs and skills can solve problems and save costs.