Portfolio
A selection of previous projects
Tableau for Operational Needs
Challenge
The leadership at a large student housing company needed to be able to determine how effective individual properties were leasing, and how many more leases were needed to achieve goals.
Process
Talking with executives and users across the company we were able to determine what was needed from both a data standpoint and visual standpoint. Utilizing an internal custom application and data mart we were able to retrieve the necessary data, load the data to an on-premises Tableau Server instance and perform rapid prototyping to produce the final product.
Result
Tableau visuals were developed that refreshed on a daily basis to allow the property managers, district managers, and corporate executives to see where issues were occurring. This allowed the organization for for the first time view the numbers the same way, leading to quicker escalation of issues and capitalization on opportunities.
Product Focused
Jeff Barrett
VP of Operational Systems and Business Intelligence
"Exceptional Product Owner with an ability to understand each aspect of business intelligence and the supporting technology."
Optimizing ETL to Enable Decision Making
Challenge
The leadership of a go-to-market organization in a large SaaS company was struggling getting timely and accurate insights for decision making. Finalized data was needed 48 hours earlier than the current processes were able to deliver.
Process
We evaluated three core components in order to evaluate what was occurring in the current ETL processes, and how to develop a full solution.
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Dependencies
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Audit Balance Control processes
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Code Performance and maintainability
After performing this evaluation, improvements were made to existing ETL pipeline code, processes were re-sequenced, and an automated QA processes was created from the ground up.
Result
The data required by executives was able to be delivered 72 hours earlier than previously. With this data, the executive team was able to analyze what was occurring with the sales numbers across different product lines earlier, and coordinate more effectively across the different go-to-market organizations when creating customer promotions and performing enterprise sales operations.
Power BI for Summarized Reporting
Challenge
The go-to-market organization at a large SaaS company needed the ability to easily steer the business. The current solutions did not offer insights quickly or easily into how the business was running to make these decisions, resulting in missed opportunities and a lag between when issues occurred and the implementation of remedial actions.
Process
Looking at the existing solutions being used by the business, two main opportunities were spotted.
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Data Architecture could be enhanced to meet current needs and be easily extensible for future needs. This could be done using a combination of existing data pipelines and new pipelines at low risk.
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The existing visuals were built focused on one user group. Utilizing Power BI we could build one set of reports that met our three user group's needs in one solution.
Result
New dashboards were created which met the needs of executives, program managers, and analysts. This was done by building a single data source which was ingested into Power BI for use in all reporting. This created a single source of truth and ensured that all team members were looking at the same numbers, regardless if they were looking at the executive, program manager, or analyst views.
Creative & Resourceful
"Highly creative and uses this skill to resolve challenges for the team in the most efficient manner."
Steven Gole
IT Delivery Manager
Building Web Data Pipelines
Challenge
Up-to-date pricing information was needed from an online marketplace. This data was going to be used to detect the sales price of items, and determine how the marketplace was affected by seasonality, internal marketplace competition, and other variables.
Process
This proof of concept was implemented with time to market and budget being the main two considerations. With this in mind, we assessed speed and cost were the most important factors.
We determined using AWS infrastructure and open source libraries would be the most efficient implementation.
The data ingestion process was built from the ground up using the following:
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Amazon Web Services EC2
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Amazon Web Services RDS
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Python 3 (Scrapy, Psycopg2)
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SQL
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Github
Creative & Resourceful
"Anyone fortunate enough to work with...[Strait Sight] will quickly see the value and customer-focused mindset"
Taylor Ehrlich
Public Sector Scrum Master
Result
Data infrastructure was configured on AWS which ingested the data from the web. This infrastructure was then used to run different reporting and analytics, meeting the goals of the project. This was able to be implemented with little infrastructure cost and showed that the architecture and product was viable.
