Is there a way to define measure group on fact1-details-table using TimeDim. Date info is only in fact1 table and not in details table.
Is namedquery joining the 2 fact tables the best solution in this case? There is so much redundancy using one fact table, so underlying sqldb uses 2 tables.
I am modelling two fact tables of Actuals and Budget which are at different granularity, Actuals are at day, customer and product sub category level. Budgets are at month, Region and Product category level.
Month, Region and Product Category is present in Date, Region and Product Category dimension respectively. I have only three dimensions as Customer, Product and Date. Linking those dimensions to Actual Fact table is not an issue, what is the best way and options are there to link budget fact table to those three dimensions.
Say you have a fact table with a few columns that all reference the same key column in a dimension table, you want to write a view to return the information for those keys?
USE MyTestDB; GO SET NOCOUNT ON; IF OBJECT_ID ('dbo.FactTemp' ,'U') IS NOT NULL DROP TABLE dbo.FactTemp;
[Code] ....
I'm using very small data at the moment, and the query plan and statistics don't really say which way.
Hi, I use lookups to map surrogate of level 1 dimensions to my fact tables in SSIS. But how to handle a level 2 dimension with a ValidFrom and a ValidUntil date field? I do not use an IsCurrent column, because this could problem with late arriving facts.
- In dts I used an SQL statement like this:
update SA SET SA.DimProdRef = Dim.RecordID FROM SAWarenEingang SA, DimProd Dim where SA.ProduktNumber = Dim.ProduktNumber and SA.ArtikelkontoBewegungsdatum between Dim.ValidFrom and Dim.ValidUntil
Now in SSIS I want to handle the whole thing in the data flow without using a staging table: - Using Lookups: I would have to pass the date column for each inside the fact table into the lookup. That does not work. - Using Execute SQL in the data flow: would be very slow, because the statement will be executed for any line in the dataflow
I am relatively new to SSIS/SSAS. I have searched the forums but cannot find an answer to my question.
I created a cube in SSAS and have deployed it. Now I am trying to use SSIS to populate the cube. I have setup a DS that points to the SSAS instance - it uses OLEDB Provider for Analysis services 9.0.
When I try to use a data flow task OLE DB source to truncate the dimension/cubes I do not see the DS in the list to select?
I am finding it hard to get into the SSIS way of organizing the processing.
I am building a health care application that marries transaction-level data (health care services provided) with person-level characteristics that have a time-dimension. The person-level characteristics are diseases that the person has (these disease all have a start and some have an end date). The diseases are stored in a table in which the foreign keys are a person-identifier, a time identifier (month/year) and a surrogate for the disease. Persons can have more than one disease at a time (the diseases are NOT mutually-exclusive). There are no measures in this table. The transaction table has a foreign key for person and time (month/day/year), a procedure code (the type of service rendered) and money (the cost of the services).
How do I answer the following questions:
What is the total cost of care (the sum of all service costs) last year for persons with "disease A"?
What is the total cost of care last year for persons with "disease A" AND "disease B"?
What is the total cost of care last year for persons with "disease A" OR "disease B"?
I've tried a factless fact table but can't get it to work. If anyone has the right solution and can communicate to me before I slit my wrists, I would be greatly appreciative!!!
What are the general guildlines for choosing these settings, like paralle vs. sequential, different error configurations? The default selection for processing multiple dimensions is paralle and use default error configuration. But the default for processing multiple partitions is sequential. I cannot find anything helpful other than the definitions from the online help. TIA.
I built my first tabular model and see that my fact tables are also appearing as dimensions. In Multi dimensional mode i could choose which are the dimensions. How do i do that in tabular model.
I am working on a model where I have a sales fact table. Each fact record has four different customer fields (ship- to, sold-to, payer, and bill-to customer). I have one customer dimension table that joins to the sales fact table four times (once for each of the customer fields above). When viewing the data in Excel, I would like to have four hierarchies (ship -to, sold-to, payer, and bill-to customer) within Customer.
Is there a way to build hierarchies within my Customer dimension based on the same Customer table? What I want is to view the data in Excel and see the Customer dimension. Within Customer, I want four hierarchies.
I have a fact table with one column storing string values. I need to use this column as a measure, but as different measure. Here's a snapshot of the fact ( with 4 columns)
#1 #2 #3 #4(value) 1 1 2007-12-20 Male 2 1 2007-12-20 French 1 2 2007-12-20 Female 2 2 2007-12-20 English
I have a dimension which is like id name 1 Gender 2 Language
Is there a way to get measures from column 4 in fact table - so that I can give reports like how gender graph during a time period or language usage during a time period. The design will have more than 2 dimension members, so fact column can hold more data like location, etc...
Can you please suggest a way to handle such kind of fact table?
When I try to create a measure based on that column (and 'no aggregation') - I get error like - "Error 1 Errors in the metadata manager. The data type of the 'value' measure is not valid because the data type of the measure is a string type."
Iam new to SQLl2005. Iam using DTS to transfer data from my source to the warehouse. I have a couple of tables in my source whein I have to join these to tables fields and insert the same in teh warehouse fact table. I have used a Join query in my Oledb source component, What other component needs to be used to insert the data into the fact table. I also need to extract same data with aggregation and insert the same into an another Fact table.
As u can see there is two company references in my fact table, and the schema is in snowflake. My customer requirements state that the Contracts' amounts can be aggregated/filtered for/by, ServiceProviderCompany, its city/profession or ClientCompay, its city/profession.
First thing came in to my mind is to dublicate whole dimension structure (one for serviceproviders, one for clients), which i thought that there should be another way around?
I'm new to MDX, and most of the time I customize existing queries rather than writing new ones. I currently have a MDX query like this
SELECT [Measures].[Fees Billed] on 0, except([Age].[Day Buckets].members, {[Age].[Day Buckets].[All], [Age].[Day Buckets].&[Unknown]}) on 1 FROM MyCube WHERE ([Fiscal Period].[Fiscal Year].&[2015], [Customer].[City].&[Auckland] )
Which brings the fees billed by age buckets where the customer's city is Auckland. I also have another dimension called [Sales Agent] with a member [City] in it, and there is a member in [Customer] called [Customer].[Sales Agent]
I am trying to retrieve the same information where the customer's sales agent's city is Auckland rather than the customer's city.
If it is SQL, I will join Customer and SalesAgent on Customer.SalesAgentUno = SalesAgent.SalesAgentUno and bring in the desired data. Any way in MDX to do this?
I'm trying to create a DM model using TS algorithm, to predict sales for different products and channels but I can only get it to work using one of those two "dimensions" or columns the other one is ignored (This is, my fact table contains a key for time, a key for channel a key for product and the metrics and the model only seems to allow working with time, the metrics and only one of the other dimensions product or channel ..) Am I missing something?
I have one dimension and one measure group. I deployed and processed the cube. Now I am able to browse the data. Now I added one more dimension. I deployed and reprocessed again the Cube. Now I am not able to see any values. I am getting like below.
Our business model involves a lot of dates and the business owners frequently want reports based on each of these different dates. For example in any given order there are as follows:
- Order created date - Client due date - Order first payment date (an order can have multiple payments) - Order fully paid date - Date assigned to vendor - Vendor return date - Date delivered to client
On top of that we have other areas of the business, the data from which ties into the above. Here we have more dates e.g.
- Date vendor recruited - Date vendor reviewed
At any given point the manager may want a report based on any of these dates. For example;
- Product type by order creation date (fiscal year / month) - Product type by first payment date (fiscal year / month) - Product type by client due date (fiscal year / month)
and so forth. I have been asked to create a report using all of the above on at least one occasion, many of them far more frequently. At the moment I have created a standard date table and then duplicated that for each type of date that I need however this is becoming excruciating to work with as I have approximately 10-12 date tables in my data model. Is there a better way of doing this now, in Excel 2013? If not, is there an improvement in 2016 that may make life easier?
I am modelling cube in SSAS. Cube has around 20 dimensions and 6 fact tables. Some of the dimensions are common among the fact tables. e.g. Time dimension. Fact_PNL has 3 date columns for those we have 3 role playing dimensions in the dimension usages.
Another fact table has 5 date columns for them as well we have separate role playing dimensions in dimension usage tab. We have a common dimension Company which is foreign key in all fact tables. We might need to combine the data from multiple facts to get final output.
Should i create 6 role playing dimension for each of the fact table or use the same dimension for all fact tables?
Role playing dimensions should be created when we have multiple columns pointing to the same dimension ?
I'm currently setting up a Tabular Model to do some research between several fact tables. In this example i have two fact tables (table 1 and table 2) which I've created a 1 to 1 relationship on phone number. Typically I create a relationship between these tables to find common data between the two. However, in this case I am trying to figure out the best way to model the data so that I can easily surface data from one table that does not exist in the other. I would liken this to a LEFT JOIN or a WHERE NOT EXISTS in SQL.
Table 1 has all of the data and Table 2 Only has a subset of the data from Table 1. What I'm trying to do here is display what attributes in Table 1 may play a part in records not existing in Table 2. What is the best way to model this?
I cannot create a measure that returns results for dates that do not exist in the fact table despite the fact that the components included in the measure contain valid results for these same dates.Creature a measure that counts the number of days where the "stock qty" is below the "avg monthly sales qty for the last 12 months" (rolling measure).Here is the DAX code I have tried for the measure (note that filter explicitly refers to the date table (called Calendar) and not the fact table):
Below you can see the sub measures (circled in red) are giving results for all days in the calendar.Highlighted in yellow are dates for which the StkOutCnt measure is not returning a result. Having investigated these blank dates, I am pretty confident that they are dates for which there are no transactions in the fact table (weekends, public holidays etc...).why I am getting an "inner join" with my fact table dates despite the fact that this is not requested anywhere in the dax code and that the two sub measures are behaving normally?
I have run into an issue that seems very simple but I am new to SSIS and DBs in general and therefore cannot solve it. I would like to take data from a SQL Server table, lookup a key from a dimension table and update the same SQL Server table with this data. Is there anyway to do an update using SSIS?
I have a transaction table having about 40 crore rows in source. It don't have timestamp and unique key columns. It have only Bill_month and Bill_Year columns. Actually for loading this table into staging I have added a new datetime column by adding default bill_date as 01. Then
* First we delete last 3 month data from staging tables. * Get last 3 months data from source table. * Load that 3 months data from source to staging table.
We do this because we only get update for last three months data. Now I have to include this transaction table as Fact table in DW. What will be the best practice for loading the fact table by picking data form staging table. Also we have to look up with dimensions for Foreign Keys.
* Should I implement the same method of deleting last 3 months records and loading them again.
We need to Insert/Update a Fact Table from staging Table. currently we are using a SP which update Fact Table for Each region. this process is schedule, every 5 min job is run and Update fact table.but time of Insert and Update too long from staging to Fact, currently we are using merge statement for Insert and update.in my sp we are looping number how many region we need to update and at a time single Region we are updating using while loop in current SP.
I would like to know how to use a fact table so that when I insert or update a row with a word that the table will reference the fact table to make sure that the word I'm using is correct.
for example I have a table with column Fulltext and Abbreviation in the fulltext column I have a a word "Windows Server 2008" now in the abbreviation I would like to abbreviate this to "Win Srv 08" Now the Fact table would have to columns Fulltext and Abbreviation under Full text the full words would be in it like Windows, Server, and 2008 and under the Abbreviation column Win, srv, and 08
So I want it so that everytime the word Windows comes up and I need to type an Abbreviation for it that it will reference the fact table which is using the Abbreviation Win. To avoid different ways of abbreviating the word windows.
Is there a way to do this automatically so that I don't have to manually go back and forth between the fact table and the table that I'm updating?
we have a problem with "one-to-many relations between fact table and dimension table". Take the example of table "LOGGEDFLAW" which is related one-to-many to the table "LOGGEDREASON. "LOGGEDFLAW" includes the column "FLAWKEY" and "LOGGEDREASON" includes the column "REASONKEY" and essentiallay the column "FLAWKEY" as foreign key. Now assume that we have the following records in there:
Now assume, that "LOGGEDFLAW" is the facttable and "FLAWCOUNT" is the measure with the source column "FLAWKEY" in which we want to count the number of FLAWs. As you see in the example the number of FLAWs is 1 for "FLAW1" and "FLAW2". Microsoft Analysis Server generates the value of 2 for the number of FLAWs "FLAW1" because of the one-to-many relationship to the table "LOGGEDREASON". In the attached ZIP File you find :
- a MDB File with the described example - a screenshot from the cube constructed in AS - a screenshot from the result table generated with AS.
The question: How is it possible to calculate the measure "FLAWCOUNT" correctly, ignoring the records generated by the one-to-many relationship?
In my data modell I have defined the 2 tables "Person" and "Category":
Table "Person" ---------------- [PersonID] [int] IDENTITY(1,1) NOT NULL [CategoryID] [int] NOT NULL [FirstName] [nvarchar](50) [LastName] [nvarchar](50)
Table "Category" ---------------- [CategoryID] [int] IDENTITY(1,1) NOT NULL [CategoryName] [nvarchar](50)
Now I like to read my first row from the source and lookup a value for the CategoryID "sailing". As my data tables are empty right now, the lookup is not able to read a value for "sailing". Now I like to insert a new row in the table "Category" for the value "sailing" and receive the new "CategoryID" to insert my values in the table "Person" INCLUDING the new "CategoryID".
I think this is a normal way of reading data from a source and performing some lookups. In my "real world" scenario I have to lookup about 20 foreign keys before I'm able to insert the row read from the flat file source.
I really can't belief that this is a "special" case and I also can't belief that there is no easy and simple way to solve this with SSIS. Ok, the solution from Thomas is working but it is a very complex solution for this small problem. So, any help would be appreciated...
I have a large flat file that comes to me. I first import the flat data in to a SQL table for ease of use. Then i put it into a more permanent table with the proper references to dimension tables. I want to build a dimension table out of information from my flat file. I have a dimension table with columns, [Org Client], and [Client#] where [org client] is the name of the client. Both of these columns appear in my flat file but i want to use only the client# in my permanent table. How extract distinct values of client # and [org client] into a dimension table?
My idea was to select distinct values of client# and use some type of foreach loop to go through each client# and use a query to select the TOP(1) values of [org client] where client# = x. Would this work and if so how do I go about setting this up?
I'm really hoping there is a simpler way than this. Thank you all for your time.
I am writing a BI solution for a recruitment company. In their business, the can be n number of participants from different dimensions linked to the same fact record. For example, a client can be sent the CV of 50 candidates. That's my first problem. My second problem is the variety of dimension participant types for a given fact record. This results in the need for nullable dimension FK's - which I'm trying to avoid. For example, consider the following two business events. In the first one, a candidate fills a job. Easy, we have a record in the fact table where the fact table has the following columns: DateKey, EventType, CandidateKey, VacancyKey. No nullable columns, great. But there are other events that I want to store in the fact table too. Let's go back to my first example: The client is sent CV's of 50 candidates in one transaction. So there is one client linked to the fact, but 50 candidates. So now I need to extend the fact table and add another column: CandidateGroupKey (which links to and Intermediate Fact Table). But in this case there was no vacancy involved. So do I now have to make the VacancyKey column nullable? That doesn't seem like a good idea... Or do I have to go for a completely different approach and have different fact tables instead of just one?
Now I have to populate the fact & dimension tables by writing sql scripts. Now I have already populated the dimension tables by writing sql script, But I have to populate the fact table taking into account, here I am facing problem in wriring sql script
(i) unit_price is taken from the book base table with reference to the isbn (ii) sales_quantity is taken from the order_detail.quantity with reference to table cust_order(via orderid & orderdate) (iii) discount_price is determined dependent on the quantity. if the quantity > 20 then discount 20 %(i.e discount_price = 0.8 * unit_price). if quantity < 10, no discount i.e normal price. if quantity between 10 and 20, discount 10%. Note that the quantity is determined based on each order of each customer, thus if the same book appears at multiple positions in an order, those positions shall be grouped together. This could happen because the pk of the order_detail table is order_id + item no, not order_id + isbn (iv) sales_amount is sales_quantity * discount_price
Hi,this is easy with OLAP tools, but I need to do it just with MS-SQLserver:fatTableyeartypeval97a197b297c398a498b598c6....yeartype_atype_btype_c971239845699...The problem is number of different types - not just 3 like a,b,c butmore than 100, so I don't want to do it manually likeselectyear, a.val, b.val, c.valfrom(select year, val from factTable where type='a') afull join (select year, val from factTable where type='b') bon a.year = b.yearfull join (select year, val from factTable where type='c') con a.year = c.yearis it possible somehow with DTS or otherwise? I just need to presentthe data in spreadsheet in more readable form, but I cannot find anyway how to export the result from MS-SQLserverOLAPservices to Excel...Martin
l've a fact table DEVICE with following structure,
DEVICE_NAME VARCHAR(50) DEVICE_DATE DATETIME DEVICE_NUMBER INT Where DEVICE_NAME and DEVICE_DATE form a PRIMARY KEY
So l would like to import a text file with same information into this table.
My problem is, text file contains records which will violate my primary key constraint. In that case, l would only insert the record with DEVICE_NUMER not equal to ZERO and discard and log the others.
In case of the records violtae primary key constraints have DEVICE_NUMBER not equal to ZERO, discard both and log it.
