Let’s discuss briefly what a Time dimension is, and then we’ll dive right into the Warehouse Builder Design Center and create one. A Time dimension is a key part of most data warehouses. It provides the time series information to describe our data. A key feature of data warehouses is being able to analyze data from several time periods and compare results between them. The Time dimension is what provides us the means to retrieve data by time period.
Do not be confused by the use of the word Time to refer to this dimension. In this case, it does not refer to the time of day but to time in general which can span days, weeks, months, and so on. We are using it because the Warehouse Builder uses the word Time for this type of dimension to signify a time period. So when referring to a Time dimension here, we will be talking about our time period dimension that we will be using to store the date. We will give the name Date to be clear about what information it contains.
Every dimension, whether time or not, has four characteristics that have to be defined in OWB:
- Levels
- Dimension Attributes
- Level Attributes
- Hierarchies
The Levels are for defining the levels where aggregations will occur, or to which data can be summed. We must have at least two levels in our Time dimension. While reporting on data from our data warehouse, users will want to see totals summed up by certain time periods such as per day, per month, or per year. These become the levels. A multidimensional implementation includes metadata to enable aggregations automatically at those levels, if we use the OLAP feature. The relational implementation can make use of those levels in queries to sum the data. The Warehouse Builder has the following Levels available for the Time dimension:
- Day
- Fiscal week
- Calendar week
- Fiscal month
- Calendar month
- Fiscal quarter
- Calendar quarter
- Fiscal year
- Calendar year
The Dimension Attributes are individual pieces of information we’re going to store in the dimension that can be found at more than one level. Each level will have an ID that identifies that level, a start and an end date for the time period represented at that level, a time span that indicates the number of days in the period, and a description of the level.
Each level has Level Attributes associated with it that provide descriptive information about the value in that level. The dimension attributes found at that level and additional attributes specific to the level are included. For example, if we’re talking about the Month level, we will find attributes that describe the value for the month such as the month of the year it represents, or the month in the calendar quarter. These would be numbers indicating which month of the year or which month of the quarter it is.
The Oracle Warehouse Builder Users’ Guide contains a more complete list of all the attributes that are available. OWB tracks which of these attributes are applicable to which level and allows the setting of a separate description that identifies the attribute for that level. Toward the end of the chapter, when we look at the Data Object Editor, we’ll see the feature provided by the Warehouse Builder to view details about objects such as dimensions and cubes.
We must also define at least one Hierarchy for our Time dimension. A hierarchy is a structure in our dimension that is composed of certain levels in order; there can be one or more hierarchies in a dimension. Calendar month, calendar quarter, and calendar year can be a hierarchy. We could view our data at each of these levels, and the next level up would simply be a summation of all the lower-level data within that period. A calendar quarter sum would be the sum of all the values in the calendar month level in that quarter, and the multidimensional implementation includes the metadata to facilitate these kinds of calculations. This is one of the strengths of a multidimensional implementation.
The good news is that the Warehouse Builder contains a wizard that will do all the work for us—create our Time dimension and define the above four characteristics—just by asking us a few questions.