Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Oil & Gas Case Study

85 views

Published on

  • Be the first to comment

  • Be the first to like this

Oil & Gas Case Study

  1. 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.

×