Insight-Driven Visualization of Open Purchase Order Lines for Asahi Kasei Bioprocesses, Inc.
School Name
South Carolina Governor's School for Science and Mathematics
Grade Level
12th Grade
Presentation Topic
Consumer Science
Presentation Type
Mentored
Abstract
Asahi Kasei Bioprocesses America (“AKBA'') has issued purchase orders to Polypore, a recent supplier. The raw data consisting of open purchase order lines were derived from multiple distinct sources and consisted of approximately 2,000 points. Consequently, it was not possible to gain insight. Microsoft Power BI was thus employed to connect the disparate data sets. Open purchase orders, which are prioritized by the customer and supplier, were used for this process. Visual Studio Code was employed for cleansing the data points. The data was transformed to a uniform format and Python code was utilized to manipulate the data to avoid discrepancies. Pandas allowed the use of data structures and operations for manipulating the raw data numerical tables via Python. Data Analysis Expressions (“DAX”) developed various calculated columns such as “Quantity Not Received,” reducing the need for manual computation. The data was then organized in a custom table via both external Python scripts and DAX. Slicers allowed the report to represent portions of data depending on document number, job number, and dates of arrival. This final visual provided insight on the total expected remaining cost, which amounted to an approximate value. However, the lack of cleansing features in Power BI led to discrepancies in calculations and external debugging processes must be used. Overall, this report provides logistical management and financial insight for both the buyer and seller. Individual employees can track orders and the report itself can be shared across multiple business domains, furthering the corporate relationship between AKBA and Polypore.
Recommended Citation
Senthil, Mritika, "Insight-Driven Visualization of Open Purchase Order Lines for Asahi Kasei Bioprocesses, Inc." (2023). South Carolina Junior Academy of Science. 41.
https://scholarexchange.furman.edu/scjas/2023/all/41
Location
ECL 340
Start Date
3-25-2023 11:00 AM
Presentation Format
Oral Only
Group Project
No
Insight-Driven Visualization of Open Purchase Order Lines for Asahi Kasei Bioprocesses, Inc.
ECL 340
Asahi Kasei Bioprocesses America (“AKBA'') has issued purchase orders to Polypore, a recent supplier. The raw data consisting of open purchase order lines were derived from multiple distinct sources and consisted of approximately 2,000 points. Consequently, it was not possible to gain insight. Microsoft Power BI was thus employed to connect the disparate data sets. Open purchase orders, which are prioritized by the customer and supplier, were used for this process. Visual Studio Code was employed for cleansing the data points. The data was transformed to a uniform format and Python code was utilized to manipulate the data to avoid discrepancies. Pandas allowed the use of data structures and operations for manipulating the raw data numerical tables via Python. Data Analysis Expressions (“DAX”) developed various calculated columns such as “Quantity Not Received,” reducing the need for manual computation. The data was then organized in a custom table via both external Python scripts and DAX. Slicers allowed the report to represent portions of data depending on document number, job number, and dates of arrival. This final visual provided insight on the total expected remaining cost, which amounted to an approximate value. However, the lack of cleansing features in Power BI led to discrepancies in calculations and external debugging processes must be used. Overall, this report provides logistical management and financial insight for both the buyer and seller. Individual employees can track orders and the report itself can be shared across multiple business domains, furthering the corporate relationship between AKBA and Polypore.
