SSRS, SQL, SSAS, SSIS, Sharepoint, MDX

1. Hong-Bing Li
Hongbingli88@gmail.com

2. Slide Contents
 3 SQL Server Integration Services (SSIS)
 8 SQL Programming
 15 SQL Server Reporting Services (SSRS)
 20 Dashboard: Scorecard & KPI (SharePoint)
 31 SQL Server Analysis Services (SSAS)
 38 MDX Programming
This portfolio contains examples of my business intelligence
projects using Microsoft BI Product Stack.

3. SQL Server Integration
Services (SSIS)
3

4. A new database “All Works” is setup as the staging area for the ETL process. A
thorough understanding of the relationships between the tables in the following
data diagram is important in determining the sequence of tables to be loaded and
in enforcing referential integrity.
4

5. A Script Task is utilized to maintain multiple sets of variables with scripts in C#, for
instance, one for keeping track of row counts of data processed dynamically at the
folder level, one for row counts at the file level.

6. One SSIS package is created to do ETL for one target table. The following illustrates
the data processing within the Job Timesheets package: the data process pipeline
starts by extracting data from a CSV file. The data is then conversed, processed and
transformed (filter, remove duplicates, lookups, validate) as it passes through the
pipeline, and is finally loaded into the target job timesheets table either as inserts
or updates. It logs any rows that error out for review and correction. Similarly,
seven more packages are generated for seven target tables.
6

7. 7
A Sequence Container is deployed to run the eight ETL packages in sequence based on the
relationships between the tables in the “All Works” Database to ensure referential integrity. If the
eight packages are processed successfully, data maintenance tasks are performed. A success or
failure notice email will be sent out depending on whether the data maintenance tasks are all
successfully completed or not.
A Master Package is created to contain the Sequence Container, the maintenance tasks and the
email notices; then a SQL Server Agent Job is setup to run the Master Package on a predefined
schedule to automate the entire data processing procedure.

8. SQL Programming
SQL Programming covers a broad range of content: Data Types and
Variables, Specialized Functions, Stored Procedures, Control-Of-Flow Operations,
Error Handling, Etc. Due to time/space constraints, I will illustrate only some of
the relatively new SQL functions/procedures/ programs that I have used in my
projects in the following:
1. Data Modification: OUTPUT clause, MERGE, select TOP(with ties) option
2. Aggregation: RANK() OVER (Partition by), GROUPING SETS
3. SQL Functions: PIVOT, CROSS APPLY
4. Common Table Expression (CTE), Correlated and Recursive Queries
5. User Defined Functions (UDF) that returns TABLE type
6. Error Handling Routine:
Begin Try...End Try
Begin Catch...End Catch

15. SQL Server Reporting
Services (SSRS)
15

16. 16

17. 17
Continued: Primary Dashboard

18. 18

19. 19
Whenever users make a selection on the "City" parameter, the cascading parameter "Product
SKU" is processed immediately. Its values are filtered dynamically based on two factors:
A. Selected cities B. Product SKU with dollar Sales greater than “0 “
The technique to implement cascading parameters in SSRS using MDX, which is based on OLAP,
is somewhat more complex than that using SQL, which is based on regular OLTP RDBMS.

20. Dashboard: Scorecard & KPI develope
using SharePoint
20

21. 21
Large Scorecard with Multiple KPIs and their Hotlinks to a
supporting report (Part 1). Right click a KPI, a supporting chart or table will
pop up to the right of the Scorecard, as shown in the next two slides.

22. 22
Large Scorecard with Multiple KPIs and their Hotlinks to a supporting
report (Part 2 with partial Supporting Chart)

23. Large Scorecard with Multiple KPIs and their Hotlinks to a supporting
report (Part 3 with the complete Supporting Chart)

24. This dual Y-axis chart created in PPS can be a great tool for data analysis as: 1. Two
different types of measures can be analyzed simultaneously against dimensional data on the
X-Axis, such as Dollar Sales (left Y-axis) and Product Percent of Parent Sales (right Y-Axis)
shown below; 2. These two measures can be broken out further to provide more detail in
tables or charts as in the report below where the right Y-Axis measuring Product Percent is
further explained by the Product Siblings breakout; 3. Data can be explored at different
levels of the Hierarchy family (see the top Product Hierarchy dropdown list) which functions
as a filter, allowing one to obtain summary and detail statistics at different levels
accordingly and export them to Excel or PowerPoint; and 4. Data points in the chart can be
drilled down to various dimensions as demonstrated below, allowing for the creation of
additional charts (see chart in next slide) which permit one to investigate the contribution of
various factors.

25. Continued: this chart is generated by drilling down from the
previous slide. For example, the 21.32% of health and fitness
sales of parents in Aug. 2005 is broken out by region.

26. 26
Price Line-Chart

27. 27
Top 5 Cities with Monthly Sales Chart

28. 28
My Performance Point Server Dashboard Project for
Generating Above Reports

29. Employee Labor Report
Deployed to a SharePoint Server

30. configure security settings: give users/
groups appropriate permissions.

31. SQL Server Analysis
Services (SSAS)
31

32. 32
The Development and Deployment of the All Works SSAS Cube
Data Source View of the Star Schema

33. 33
Browsing the All Works Cube Data

34. 34
Definition of Calculated Members

35. 35
Definition of Key Performance
Indicators (KPIs)

36. 36
This is an example of a KPI developed from the AllWorks.cube, which is deployed to
the Excel Spreadsheet for the end users. All the data in the cube, including all KPIs,
can be explored through the Pivot Table Field List.

37. Partitions Performed for the “All Works” Cube

38. MDX Programming
38

39. MDX query for the primary dashboard
(Slide 15 and 16 in SSRS Section)

40. This MDX Query shows two measures, Internet Sales Amount and
Internet Freight Cost, are sliced against three dimensions:
Date (FY Year), Product and Customer (Country)

41. ---The End---
Hong-Bing Li, February, 2015
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