I use PSW 3.5.11. I have a classic dimension for people (sex, ethnicity, religion, study level, etc.) and people code.
How can I create this dimension to use each attribute alone and not as a level?
I know how create a dimension with hierarchy, like
geography: Country -> Province - > Region -> City
but Geography dimension not has same structure of People dimension.
How analyze my data by sex in a report, by ethnicity in another report? How can I create the People dimension?
Thanks for the help.
You can reference the same table multiple times.
Define one dimension gender, pointing to the table and a single level gender given by column gender; set another dimension ethnicity, pointing to the same table and a single level ethnicity given by column ethnicity. Etc.
If you prefer, you can instead set multiple hierarchies, one for each attribute, all within a single dimension People, but in practice there isn’t much difference (the MDX changes just a bit).
Related
As we know When a cube is built, tuples are created by dimensions and some aggregations applied. Know I faced with a special type of dimension that it's members aren't collectable. For example please consider actor type dimension:
Code Desc
----------------------------------
1 Vendor
2 Employee
3 Unemployed
The point is that I never want to aggregation for Vendor or Employee or Vendor or Employee or Unemployed. My problem is just about comparing these items with together. I only want to compare Vendor with Employee or Employee with Unemployed. So I think in cube there are some aggregations that I don't need to them.
Is there any way to handle this dimension? Is there any dimension type?
Thanks
For the beginning you don't need ALL member in attribute hierarchy, so you could set IsAggregatable property to false.
But, this will not prevent aggregation if you select for example two members (Employee and Vendor) in the filter. For this purpose you will need some kind of scope assignment against your dimension.
I have country, region, county, town data and I'm currently deciding between 2 schema designs (if there's a better one, do tell).
I first thought
Country
Id
Name
Region
Id
CountryId
Name
County
Id
RegionId
Name
Town
Id
CountyId
Name
Does the job however to get all towns in a country you have to 3 inner joins to do the filtering. I guess this could be ok but potentially expensive?
The other design was:
Country
Id
Name
Region
Id
Name
County
Id
Name
Town
Id
CountryId
RegionId
CountyId
Name
This way all hierarchical data so to speak is at the bottom and you can go back up however if you want all regions in a country you're a bit screwed which makes we wonder whether the first design is best.
What do you think is the best schema design?
The best database design depends on how the data is being used.
If this is pretty static data that will all be updated at one time and external references are all to towns, then I would probably go for a denormalized dimension. That is, store the information all in one row:
Town Id
Town name
County name
Region name
Country name
Under the above scenario, the ids for county, region, and country are not necessary (by assumption).
If the data is being provided as separate tables with separate ids, and these tables can be updated independently or row-by-row, then a separate table for each makes sense. Putting all the ids into the towns table may or may not be a good idea. You will have to verify and maintain the hierarchies when data is inserted and updated.
If ids for each level are necessary for your, then you should have appropriate table structure for declaring foreign key constraints. But, this can get complicated. Will an external entity have a "geography" attribute that can be at any level? Will an external always know what level it is going to refer to as?
In other words, you need to know how the data is going to be used in order to define an appropriate data model.
I have 5 tables that have the same structure and same columns: id, name, description. So I wonder what is the best way to design or to avoid having 5 tables that have the same columns:
Create a category table that will include my three common
columns and another column "enum" that will differentiate my categories
ex (city, country, continent, etc.)
Create a category table that will include my three common
columns and create the other five tables that will just include an
id.
Note that I would have an assocation table that should include the id of cities, id countries, id continents, etc. so i can display them into a report
Thank you for your advice.
The decision on how many tables to have under these circumstances simply depends.
The most important factor is whether the five things are independent entities or whether they are related. A simple way to understand this is by understanding foreign key relationships: Will other tables have a column that could refer to any of the five (say "geoid")? Or will other tables have a column that generally refers to one of the five ("cityid", "countryid")? The ability to define helpful foreign key constraints often drives the table structure.
There are other considerations. If your data is at the geographic level, then it might represent hierarchies . . . cities are in countries, countries are on continents. Some databases (such as MySQL) do not support hierarchical queries at all. Under these circumstances, you might consider denormalizing the data for querying purposes.
Other considerations can also come into play. If your application is going to be internationalized, then having all the reference tables in a single place is handy -- for providing cultural-specific information (language, currency symbol, and so on). One way of handling this situation is to put all such references in a single table (and perhaps using more sophisticated foreign key relationships).
The column names are not important, just the data in the columns. If City description, country description and continent description are different information then you are already doing this the right way. The only time you would aim to reduce this data would be if you were repeating information but for the titles of the data it's fine.
In fact. You are doing this correctly. Country will have different values from city for every field mentioned. Id is just an id, every table should have one. Name and description wont be the same across country and city.
Also, this way if you want a countrys name you dont have to go through every country, continent and city. You only have 192 or so entries to go through. If you had all of that in one massive table you would have to use it for everything and go through every result every time you want data. You would also have to distinguish between cities, countries and continents in some other way than the separate tables.
Eg:
method 1, with 5 tables:
SELECT * FROM country
does the same as
method 2, 1 table:
SELECT * FROM table WHERE enumvalue = 'country';
If you have tables representing city, country and continent, and they all have exactly the same fields, you have a fundamental problem. In real life, every city is in a country and every country is in at least one continent (more or less) but your data structure does not reflect that. Your city table should look something like this:
id (primary key)
countryId (foreign key to country)
name
other fields
You'll need a similar relationship between countries and continents. However, before you do so, you have to decide what to do about countries like Russia which is in two continents and Palau which isn't really in any.
You may also want to have a provinceStateTerritory table to help you sort out the 38 places in the United States named Springfield. Or, you may want to handle that situation differently.
In SSAS is there a way to have a dimension relate to a fact table based on two columns in the fact table?
We have two tables: Location (Dimension) and Sales (Fact). The Location dimension has one column: "state". The Sales table has three columns: "saleAmount", "customerState" and "billingState" (because our customer can be in California but wants us to bill a company or branch in New York).
In SQL, if we want to see all the sales in California, we write our SQL query as:
select sum(saleAmount) from Sales where customerState = 'California' or billingState = 'California'
Is there a way to accomplish this in SSDT when building my cube so that when I'm using Excel as an end user tool and I select the state attribute from the Location dimension and the saleAmount measure, the saleAmount will be based on customerState or billingState? (I do not want to have role playing dimensions here - where one Location dimension is based on customerState and another Location dimension is based on billingState. I want one dimension matching up with both columns at once.)
Not the way you're thinking, but you can achieve what you want by doing this:
Create a view on your fact table, that is a UNION of facts related to customerState and facts related to billingState. This means the view will only have 1 State column, and if a fact has different values for customerState and billingState, then it will have two rows in the view.
Use the view instead of your table to populate your measure group in the cube.
Link the measure group to the Location dimension on the single State column in the Fact view.
Builder beware, this results in duplicate counting of facts when rolling up states where a single fact is in two different states.
I am developing an intranet application for my company. The company has a complicated structure in which there are many business lines, departments, divisions, units and groups. I have to take care of all of these things. Some employees work under department level, some of them work under unit level and so on. The problem now is with database design. I am confused about how to design the database. At the beginning, I decided to design it as following:
Employees: Username, Name, Title, OrgCode
Departments: OrgCode, Name
Divisions: OrgCode, Name
Units: OrgCode, Name
but the problem as I said before, some employees are working under departments, so how to make relations between all of these tables. Is it possible to have OrgCode in Employees table as a foreign key to OrgCode in Departments, Divisions and Units tables?
Could you please recommend me how to design it?
UPDATE:
#wizzardz put a nice database design. All what I need now is to have an example of data that fit this database design
Here's a set of data that I am using in the database:
let us assume that we have Employee with the following information:
Username: JohnA
Name: John
Title: Engineer
OrgCode: AA
And let us assume we have department AA, how I will distribute this data into the database design?
You could do a design something like this
rather than going for separate tables for Departments, Divisions etc try to store them in a single table with a TypeId to distingush Departments , Divisitions etc.
Could you try a design like this
In the Level table you need to enter the values like 'Deparments,Divisions', Groups, etc (By keeping it in a separate table you can handle any future addition of new levels by your organisation.)
In the OrganisationLevels table you need to store Department Names,Division Name, GroupName etc.
The Employee table has a forigen key reference with the table Organisation level, that will store which Level an employee is working in the organisation.
If you wants to store the work history of a particular employee/ there is a chance that an employee can be moves to one level to another I would suggest you to go for this design
Sample data wrt the design
Level
Id LevelType
1 Department
2 Division
3 Group
OrganisationLevels
Id Name LevelId Parent*(Give a proper name to this column)*
13 AA 1 NULL
.
.
21 B 2 13 (This column refer to the Id of department it belongs to.)
Employees
Id UserName Name Title
110 JohnA John Engineer
EmployeeWorkDetails
Id EmployeeId OrganisationLevelId StartDate EndDate IsActive
271 110 13 20/09/2011 NULL true
OrgCode from the Employee Table can be removed, because I thought it is the employee code of the employee with that organisation.
I hope this helps.
Employees: Username, Name, Title, OrgCode
Departments: OrgCode, Name
Divisions: OrgCode, Name
Units: OrgCode, Name
To the above mentioned DB design, have one more table called Org containing OrgCode and another column as type (which we give insights on which type of org is it i.e. Departments,Divisions and Units)
then you can have employee table's OrgCode to have refer the OrgCode of Org table(parent-child relationship).
I suggest that you learn the difference between analysis and design. When you design a database, you are inventing tables, columns and constraints that will affect how the data is stored and retrieved. You are concerned with ease of update and query, including operations you will learn about later.
When you analyze the data requirements, you aren't engaged in inventing things, you are engaged in discovering things. And the things you are discovering are things about the "real world" the subject matter is supposed to represent. You break the subject matter down into "entities" and relationships among those entities. Then you relate every value stored in the database to an instance of an attribute, and every attribute to some aspect of either an entity or a relationship. This results in a conceptual model.
In your case, the relationships between employees, departments, units, etc. sound quite complex. It's worth quite a bit of effort to come up with a model that reflects this complex reality accurately.
Once you have a good conceptual model, you can create SQL tables, columns, and constraints that adequately represent the conceptual model. This involves design skills that can be learned. But if you have a lousy conceptual model, you're doomed, no matter how good you are at design.