These first ten videos have a combined duration of 59.1 minutes. They explain how to build a first tiny data warehouse in complete detail: from installation and activation of DWiz, through design of warehouse schema and staging ETL, all the way to compiling an ETL group. Although this first tiny data warehouse will only have one fact table and two dimensions, it will be complete and functional, and will have the fundamental star-schema design that is used in actual implementations. In addition to watching the videos, you can actually duplicate the exercises by using the Free Trial of DWiz while you pause the videos. This additional "keyboard time" is estimated at 60 to 120 minutes, including the time needed to download and activate Data Warehouse Wiz. Thus, with a 2 - 3 hour time investment, you can start from "scratch" and design a complete (tiny) data warehouse and, in so doing, evaluate our friendly Data Warehouse Wiz. You can also use the same techniques, demonstrated here in Part I, to build a basic warehouse for your own business. After being duely impressed, proceed to Part II to learn advanced skills.
20 MB, 00:09:41
Installing and activating DWiz; preparing the databases.
3 MB, 00:01:49
Simple steps to define a new project for a data mart/data warehouse.
8 MB, 00:05:33
Download tables hold the changed data extracted from tables in the source databases.
This video shows the design of the DownloadCustomer table from source "Customer".
To continue with the tutorial, please also design DownloadInvoice from the source table "Invoice",
as described in the tutorial pdf section "Design DownloadInvoice".
7 MB, 00:04:38
Flat tables hold the transformed data that has been prepped for the warehouse tables.
This video shows the design of the FlatCustomer table from DownloadCustomer.
To continue with the tutorial, please also design FlatInvoice from the table DownloadInvoice,
as described in the tutorial pdf section "Design FlatInvoice".
10 MB, 00:07:10
Demonstrates the basic features commonly used in Flat Procedures which transform the data and prep it for Flat Tables.
This video shows the design of the flat procedure FlatCustomer_upd for the FlatCustomer table.
To continue with the tutorial, please also design FlatInvoice_upd for the table FlatInvoice,
as described in the tutorial pdf section "Procedure for FlatInvoice".
7 MB, 00:04:39
Dimension tables hold dimensional info in the star schema of your data warehouse.
This video shows the design of the DimCustomer table.
To continue with the tutorial, please also design DimInvoice,
as described in the tutorial pdf section "Design DimInvoice".
8 MB, 00:04:44
Dimension Procedures select the appropriate data changes from a Flat Table to update Dimension Tables in the data warehouse.
This video shows the design of the dimension procedure DimCustomer_upd for the DimCustomer table.
To continue with the tutorial, also please design DimInvoice_upd for the table DimInvoice,
as described in the tutorial pdf section "Procedure for DimInvoice".
If you have been re-creating the examples in videos 1 to 7, then you have seen how to start with the source Customer table and create the following tables and procedures: DownloadCustomer, FlatCustomer, FlatCustomer_upd, DimCustomer, and DimCustomer_upd.
Before re-creating the examples in videos 8 to 18, you must also use the same techniques to make the following tables and procedures based on the source table Invoice: DownloadInvoice, FlatInvoice, FlatInvoice_upd, DimInvoice, and DimInvoice_upd.
These tables and procedures are needed for the examples in videos 8 to 18.
8 MB, 00:05:32
Fact Tables hold facts in the center of a star of your star-schema data warehouse.
This video shows the design of fact table FactInvoice.
While the video also shows how to delete the new FactInvoice table, please do not delete the table if you continuing to follow the Tutorial.
The FactInvoice table is needed for the next step in the Tutorial.
12 MB, 00:06:43
Fact Procedures select the appropriate data changes and surrogate keys from Flat Tables to update Fact Tables in the data warehouse.
This video shows the design of the fact procedure FactInvoice_upd.
15 MB, 00:08:37
Demonstrates compiling the ETL designs from the above videos into one executable. This executable (stored procedure or SSIS package) can be scheduled to run periodically like any other SQL job (independent of DWiz).
These next eight videos have a combined duration of 76.9 minutes. They demonstrate techniques useful for constructing a high-performance data warehouse, such as: designing Bridge, Junk, and Outrigger warehouse tables; compiling an ETL Group into a high-performance SSIS package (Microsoft SQL Server Integration Services); easy pivoting and aggregation designs; merging column-data from multiple source tables; and powerful advanced features in Flat Procedures for the labor-saving design of complex transformations. As with Part I, these same techniques can be used to build a powerful and high-performance data warehouse for your own company, even by using the Free Trial of DWiz.
18 MB, 00:09:34
Expand your data warehouse with a Junk Dimension, efficiently handling miscellaneous low-cardinality fields.
23 MB, 00:13:13
Expand your data warehouse with a Bridge, handling many-to-many relationships in your star schema.
15 MB, 00:08:16
Expand your data warehouse with an Outrigger Dimension, efficiently allowing a secondary (outrigger) dimension on attributes within an existing primary dimension.
23 MB, 00:14:30
Optionally compile your ETL process into an SSIS package. While this option is a bit more complicated than just creating a Group Stored Procedure ("Compiling an ETL Group"), the resulting package has higher performance.
15 MB, 00:08:30
Easily pivot row data (from an existing Flat Table) into columns of a new pivot table.
11 MB, 00:05:50
Design aggregation (SQL "group by" clauses) into a Flat Table.
8 MB, 00:05:06
Demonstrates an example wherein a single Flat Table draws and merges data from multiple source tables for the same columns.
18 MB, 00:11:52
Advanced features available to transform data for Flat Tables.