MicroStrategy (MSTR) is the Business Intelligence tool Maxxton is using to provide our customers more information about their business. All data we're using is gathered out of Maxxton Software (or Newyse) and is updated every night, so the most recent data is used.
We have created three datasets to work with in MSTR, these are:
- The Accommodation Daily Dataset
- The Reservation Dataset
- The Reserved Resource Dataset
In the Accommodation Daily dataset you will find all information related to the Accommodations in Maxxton Software (& Newyse). This dataset gives information per unit per day, the unit is in this dataset the lowest level to give insight in your business. The Reservation dataset will give you detailed information based on the reservation per day as lowest level. This means even though 2 or 3 accommodations will be booked in one reservation, you will only see this as one reservation. This means the accommodation daily dataset is more detailed, which you will see reflected in our further design of the BI-tool. The Reserved Resource dataset gives information about extra services customers have booked beside the accommodation, such as bedlinnen, bikes or breakfast.
All data shown in MSTR is divided into two object-types, these are:
- Metrics and
- Attributes
Metrics are objects based on calculated business data, such as revenue or occupancy and Attributes represent contextual data, they give information about the metric. For example in what country the revenue is achieved or in which month.
Attributes represent a business concept, such as Employee, Month, Resource and so on.
Attribute provides a context for the data calculations(metrics) that are usually the core of business reporting.
Attribute Elements are the unique values or contents of an attribute. For example, if City is the attribute, then Chicago and Miami are elements of City.
Attribute forms are additional descriptive information about a business attribute.
An attribute can have many other forms. For example, the attribute customer has the forms like ID, Last Name, First Name, Address and Email
Understanding a dataset
The editor panel
The format panel