The document discusses a project where Pragmatic Works helped an oil and gas company improve the performance of their SQL Server Analysis Services (SSAS) and SQL Server Integration Services (SSIS) environments. Pragmatic Works conducted a two-week assessment where they identified bottlenecks and provided recommendations. Specifically, they optimized the SSAS cube processing by changing transaction dimensions to ROLAP storage and redesigning parent-child dimensions, reducing processing times from 30-45 minutes to seconds. They also improved the SSIS ETL process by transforming views into tables and parameterizing by date, reducing fact package processing from 1.5 hours to 5 minutes. As a result, the client saved significant time and resources and gained the flexibility to

1. 1. Review and assess environments for
industry accepted best practices:
• SQL Server instance and data
warehouse database
• SSIS environment
• SSAS environment
2. Review and assess server and SQL
Server instance and database, including:
• CPU/Memory/Storage/Network
configuration and allocation
• Server, instance and database
configuration
• Waits and queues platform review
• Query execution bottlenecks
3. Review and assess SSIS configuration
and design, including:
• Best practices
• Notification and alerting capabilities
4. Review and assess SSAS configuration
and design, including:
• Dimension Usage
• Attribute relationships
• Aggregation designs
• Partitioning
• Processing bottlenecks
• Demo write back capabilities
5. Formulate Best practice
recommendations and associated time/
cost estimates to implement
6. Mentor client team on SSIS and SSAS
best practices
Pragmatic Works recently worked with an independent oil and gas company focused on the acquisition, exploitation, development
and production of oil and gas properties in the United States. Over the past year, our customer has gone through an effort to replace
and re-architect their data platform. They expect to bring additional data into their platform; which should more than double the
existing volume of data. With the current data volume, there are a number of issues that are causing concern, including SQL Server
Analysis Services (SSAS) processing running longer than expected, SQL Server Integration Services (SSIS) executing longer than
expected, and exception handling and logging not consistently applied to SSIS packages. Additionally, with the acquisition of a
second company, a new need exists to be able to perform write back forecasting within SSAS.
Pragmatic Works came on board to review and assess our customer’s environment for best practices, including SQL Server instance
and database and SSIS and SSAS configuration and design. Furthermore, we performed a two-week BI assessment while working with
their internal team to identify potential scaling and performance bottlenecks while providing recommendations for improvement.
From the start of this project, the customer was dealing with a slow ETL that hindered
their ability to fully utilize their data. They use their data to optimize oil production
costs which translates into great margins and increased profitability. Great effort was
taken to improve this process to meet the goals of the project. Pragmatic Works was
able to make significant improvements in their cube processing environment by setting
transaction dimension to ROLAP and transforming several parent-child dimensions
into normal dimensions.
In a two week period, Pragmatic Works delivered an improved SSAS processing
pattern. Before the assessment and implementation, transaction dimensions were
processing 30-45 minutes. As ROLAP storage, they now process in seconds.
The customer also had many parent child and many-to-many dimensions that caused
issues with their query performance. By improving the SSAS dimension design pattern,
the client now sees a significant improvement in that performance.
Pragmatic works also improved the SSIS fact processing pattern. The fact packages
were originally built off of multiple views that were several orders of magnitude
deep. The consultant working onsite took the views and transformed them into
tables allowing for very fast querying of the source data. The source data was also
parameterized by date. A control table was added to allow date based processing. The
SSIS fact table packages went from 1.5 hours to 5 minutes to process dates for the
last 90 days.
By working with Pragmatic Works, our customer was able to gain significant and
impactful return on investment in processing time and performance.
These increases saved the company in both man hours and resources allocated. They
were also able to ease the strain of adding to their existing volume of data as their
platform increases in scope. Now our client has the flexibility to scale their data while
improving the quality thanks to the efforts of the Pragmatic Works expert team.
Client Overview
Engagement Goals Solutions and Benefits Delivered
sales@pragmaticworks.com | pragmaticworks.com
CASE STUDY
Oil and Gas Company saves significant man hours
and resources by increasing data processing and
performance with Pragmatic Works.