Renewing Analysis Process for Catalog Data
Timperi, Samu (2021)
Timperi, Samu
2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021060113141
https://urn.fi/URN:NBN:fi:amk-2021060113141
Tiivistelmä
The objective of this thesis was to construct and model an analytics dashboard with Microsoft Power BI, that includes relevant Key Performance Indicators for comparing varying data errors in product catalog data. The tool is built to a client that operates globally in the field of electrification and automation manufacturing, which in practice means the client is using a vast amount of modern computer systems which has significantly increased the amount of data and has thus resulted in the critical need for data correctness and quality.
The current method of going through product data is to check it from a table view without any additional indicators helping to identify conspicuous data. This method consumes excessive work time and is to be replaced with an analytics program using Microsoft Power BI as a platform. Power BI is able to read data from an ERP export file through Microsoft Excel and showcase and highlight only the products and data cells that the system recognizes as the ones needing inspection.
The research section of the thesis includes a Current State Analysis and targeted literature research that tackles the weaknesses in the case company’s data quality process identified through the CSA. This is where theoretical information and common practices are researched and put together to be used in a building solution.
The outcome of this thesis is an analytics dashboard with Microsoft Power BI that includes relevant Key Performance Indicators for comparing varying data errors in product catalog data.
The current method of going through product data is to check it from a table view without any additional indicators helping to identify conspicuous data. This method consumes excessive work time and is to be replaced with an analytics program using Microsoft Power BI as a platform. Power BI is able to read data from an ERP export file through Microsoft Excel and showcase and highlight only the products and data cells that the system recognizes as the ones needing inspection.
The research section of the thesis includes a Current State Analysis and targeted literature research that tackles the weaknesses in the case company’s data quality process identified through the CSA. This is where theoretical information and common practices are researched and put together to be used in a building solution.
The outcome of this thesis is an analytics dashboard with Microsoft Power BI that includes relevant Key Performance Indicators for comparing varying data errors in product catalog data.