How do you handle late arriving dimensions in Informatica?

How do you handle late arriving dimensions in Informatica?

Using a special “unknown” dimension

1. When the dimension data eventually does arrive, you have to remember to go back and update any fact records which are pointing at “Not known yet”.
2. You would be forced to store the natural key alongside the surrogate key in the Fact record.

How late arriving facts are handled in ETL process?

In Data Warehouse ETL process, Late Arriving Dimension represents the detection of record(s) arrives in a fact table and its corresponding dimension doesn’t exists. As a result, a late arriving dimension has a natural key which exists in the new fact data, which does not yet exist in the dimension.

What is early arriving facts or late arriving dimension?

Late-arriving dimensions (sometimes called early-arriving facts) occur when you have dimension data arriving in the data warehouse later than the fact data that references that dimension.

How do you handle early arriving facts?

Handle Early Arriving Facts in SQL Server Integration Services

1. Problem. We typically use the Lookup Data Flow Transform to retrieve the surrogate key for a dimension row based on the natural key in a fact table.
2. Solution. The situation you describe is often referred to as early arriving facts.
3. Next Steps.

What is late arriving fact?

A fact row is late arriving if the most current dimensional context for new fact rows does not match the incoming row. This happens when the fact row is delayed. In this case, the relevant dimensions must be searched to find the dimension keys that were effective when the late arriving measurement event occurred.

What is factless fact table why we need it?

Factless fact tables are only used to establish relationships between elements of different dimensions. And are also useful for describing events and coverage, meaning tables contain information that nothing has happened. It often represents many-to-many relationships. The only thing they have is an abbreviated key.

How does SSIS handle late arriving dimensions?

1. Use Filtered Index on Fact Tables. Since the unknown surrogate key is well-defined subset of data, use Filtered Index to fetch fact records that have unknown SK.
2. Use Skinny Staging Tables. Fact tables usually do not store the Natural Key of the dimension.
3. Avoid Row-by-row updates.

Can you load fact table before dimension?

If you have sales fact table which is loaded first with a record with a sale of $5000. So, as an order dimensions should be loaded first before the facts. Reason, is to have the related key value (Surrogate Key or the Primary key/Foreign Key) from the dimension (product) to the fact (sales).

How do you load time dimension?

Time dimensions are usually loaded by a program that loops through all possible dates that may appear in the data. It is not unusual for 100 years to be represented in a time dimension, with one row per day. Time dimension are used to represent the datas or measures over a certain period of time.

How can we load the time dimension in data warehouse?

Bhargava Kudligi

1. Bhargava Kudligi.
2. U can load time dimension manually by writing scripts in PL/SQL to load the time dimension table with values for a period.Ex:- M having my business data for 5 years from 2000 to 2004, then load all the date starting from 1-1-2000 to 31-12-2004 its around 1825 records.

Why is it a good practice to load the dimension tables before the fact tables?

The example above is using only 2 dimensions but in the real practice we would have to deal with more dimensions. 10 to 15 dimension key columns on the fact tables are common occurance.

What is late arriving Dimension Data?

Late arriving dimension data also occurs when retroactive changes are made to type 2 dimension attributes. In this case, a new row needs to be inserted in the dimension table, and then the associated fact rows must be restated.

How to handle Dimension Data that is not known yet?

When the dimension data eventually does arrive, you have to remember to go back and update any fact records which are pointing at “Not known yet”. Updates like these tend to be computationally expensive and are prone to errors in logic. You would be forced to store the natural key alongside the surrogate key in the Fact record.

What happens when dimension lookup fails to work?

In this approach, even if dimension lookup fails, facts are dumped into fact tables with default values in the dimension columns and have a hydration process to periodically hydrate the missing dimension data in the facts table.

How to handle late-arriving dimensions?

Often there’s no need even to do a lookup, because the special records are allocated meaningful (usually negative) surrogate keys. Similarly, for late-arriving dimensions, you can use a specially-created dimension record with description “Not known yet”. This works well for late-arriving dimensions, although with two main drawbacks: