Business IntelligencePortfolio

Eric ShieldsEric.Shields@SetFocus.com330-829-9836

Table of Contents

SSIS ETL Project Slide #3

SSAS OLAP Project Slide #7

Report Project Slide #12

Final Team Project Slide #16

SSIS ETL Project

• Introduction: Using Microsoft’s SQL Server Integration Services, SSIS to perform Extract Transform and Load, ETL

• Audience: Companies that can benefit from Microsoft’s Business Intelligence

• Project Goals: Move data from multiple sources to a staging area

Extracting from Excel to a relational DB staging area, inserting and updating records with error reporting

• I created this Data Flow showing the process by which the data is read from the Excel file, translated to the database format and verified. The process determines if the record is valid, if the record already exists and if an update is required. Records are inserted or updated into the Staging DB as needed.

ETL from multiple flat file sources into the staging DBIncluding error logging and email verification

• Example of a Control Flow I created for a different ETL process. The control flow removes any existing error logs and steps through each flat file found in the source location, counting number of files read and total number of records found in those files. Then an email is generated on successful completion of the task reporting the number of files read and records updated, inserted or sent to the error log.

Master Package runs all the ETL packages then backs up, rebuilds the index and shrinks the DB

• Note the power of the SSIS. After I finished creating many ETL packages, I created another package to execute them all . This package, or any package can then be scheduled in SSMS using SQL Server Agent to run at appropriate times unattended. This project represents the foundation for creating a business intelligence solution.

SSAS OLAP Project

• Introduction: Using Microsoft’s SQL Server Analysis Services , SSAS to create an OLAP Cube

• Audience: Companies that can benefit from the performance of an OLAP Cube

• Project Goals: Use data in the staging area to build an OLAP Cube for analysis

Microsoft’s Visio used for layout and design of the OLAP Cube

• A successful Business Intelligence solution requires careful planning. Determining reporting and analytical needs of the company is foremost in this design process. Also important is determining time frames for deliverables, small incremental projects delivered quickly or large all encompassing projects delivered periodically. Here I used Visio to design an OLAP Cube.

Design from Visio implemented in Microsoft’s SSAS

• Using SSAS to create OLAP Cube. The Cube structure was modified to add calculated fields and relationships. Hierarchies where created, sorting behavior and naming conventions applied to provide the data in a user friendly format. I found that proper naming conventions and hierarchical structures greatly improve the usability of the OLAP Cubes.

KPIs, Key Performance Indicators added to the Cube for analytical and reporting purposes

• SSAS can also add Calculations often used to support the creation of the KPIs. Using MDX in the calculations provided an extreme amount of flexibility and power to create complex business calculations. Learning the full capabilities of the SSAS product provides me with a powerful tool for answering business needs.

Partitions and Aggregations within SSAS allow performance tuning of the OLAP Cube

• I utilized the partitions and aggregations to improve the performance of the designed cube. Very large cubes can cause performance issues, by breaking large cubes into multiple partitions across multiple physical servers performance can be improved. Aggregation level can be set to balance cube size verses performance. Increasing the level of aggregations increases the size of the cube but increases the speed at which rollups occur when reports are generated from the cube.

Report Project

• Introduction: Using Microsoft’s SQL Server Reporting Services, SSRS, Performance Point Server, PPS, and Excel to create reporting solutions

• Audience: Anyone wishing to analyze and share data in a productive, beneficial manor

• Project Goals: Creating reports and deploying them to SharePoint for quick and easy access

Reports created in SSRS, delivered to the end user with subscriptions and to SharePoint

• I created reports in SSRS to provide solutions to business requirements. With SSRS these reports can be setup to be delivered to the end user through subscriptions to email accounts, a file location or historical reporting. This ability allows end users quick access to up to date information in which to make critical business decisions.

Microsoft’s Excel used to create reports then deployed to SharePoint is another powerful reporting tool

• Using Excel to create spreadsheet like reports or charts provides another reporting tool. Here I created a chart in Excel and deployed it to SharePoint. While Excel is a powerful reporting tool, adding an Excel chart to a PPS Dashboard and deploying that to SharePoint adds a cleaner more user friendly interface.

KPIs used on Scorecards in PPS Dashboard designer were then deployed on a Dashboard to SharePoint

• Using the KPIs previously created in SSAS for the OLAP Cube or creating new KPIs on the fly in PPS Dashboard designer provided another useful reporting tool. I used KPIs to create scorecards which I added to a Dashboard then deployed to SharePoint. As can be seen the Scorecard page is just one of many pages on the Dashboard.

Final Team Project• Introduction: Using all of Microsoft’s BI tools

to create a real word solution for a real company

• Audience: Companies wanting to improve their bottom line

• Project Goals: Deliver new reporting solutions in a team environment. From production DB to staging DB via ETL to OLAP Cube design and implementation to final report deliverables

The purpose of the final team project was to demonstrate our skills and provide real word deliverables

• The team had four members and I was chosen to be the team leader.• The only deliverables where the final reports.• Design and implementation was left entirely up to each team.• Our first step was to determine what information was required for the deliverables.• Secondly we designed and implemented a DB using Visio.• Using SSIS an ETL package was created to extract the information from the two production

DBs, transform the data into a more useable format and load the staging DB.• From there an OLAP cube was created using SSAS. Calculations and KPIs were added to the

OLAP cube to provide the rest of the needed data to create the reports.• At which point the actual deliverables could be created.• The desired results could only be achieved through the use of all of Microsoft’s reporting

tools.– Excel, PPS and SSRS where all used to create the required reports. All of the reports were then

deployed to the SharePoint site the team created. Each product provides slightly different features and to achieve the desired results all of the tools had to be leveraged.

Designing the Staging DB

• Here is the final design, this was the most difficult part of the project. Designing from scratch the staging DB and resulting OLAP Cube was an enjoyable exercise which went through many iterations before a workable solution was found.

Creating the ETL solution

• As it turned out a single Data Flow for just one table in the staging DB was rather complicated. It took a little creative arrangement to fit into a single screen shot. Above and beyond the projects requirements my team was able to create a production level ETL package designed to be scheduled and run through SQL Server Agent for incremental updates to the staging DB.

Creating the OLAP Cube

• Once the proper design was implemented and populated with data, building the OLAP cube went rather painlessly. Creating the calculations and KPIs along with the hierarchies within the cube enable the report creating process to move along smoothly.

Reports the deliverables

• Here is an example of a couple of the reports. While it may appear that once the OLAP cube had been created we had finished with the cube. This was not the case. As the team worked on the reports we realized that some information we required was unavailable, formatted poorly, sorted incorrectly or simply required difficult calculations within the reports. While most of the issues could be resolved within the reports, since the problems often spanned more than one report it made logical since to correct these issues with in the cube itself. In at least one case missing information required a significant redesign of the staging DB, ETL package and the OLAP Cube.

Conclusions from the Final Team ProjectSome key points

• Project demonstrated the need to clearly understand what exactly the deliverables are.– The format the deliverables are to be presented in must be defined clearly.– The information / data required has to be determined, how that data needs calculated

and sliced and at what level of granularity.– Where and how are the above two requirements going to met.

• The initial design determines the overall success and ease of which the rest of the project comes together.– Understanding of the layout and data within the production DB is a must.– Determination of the requirements of the staging DB from the deliverables analysis

creates the foundation to the project. • Does the production data need cleaned up or reformatted.• Do counts or aggregations need to be included.• What is best handled during the ETL process and what is best handled within the Cube.

– Creating the OLAP cube to support the report creation process.• What calculations and KPIs need created.• What hierarchies and named sets complement the report writing process.

• Good leadership and organization is the final key for any project.