Project Management Toolset for Big Data
Pietikäinen, Laura (2022)
Pietikäinen, Laura
2022
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022060615533
https://urn.fi/URN:NBN:fi:amk-2022060615533
Tiivistelmä
This thesis presents a case study that has targeted to improve the usage of big data and information flow in one of the famous international companies. The company is a large worldwide company in the IT sector, and our focus is on smaller pilot projects in the nanofabrication optics hardware engineering field. The thesis topics are about the process of developing and visualising solutions based on case studies of the problems that were found. As a brief background to our work field, we handle production type of manufacturing processes and R&D type of projects. Both areas have a target in quality and quantity, and schedules are tight. Work is done in differ-ent work modules using various tools, and each of these tasks produces high quantities of data. It has been a challenge to utilise that data from an operational point of view, so the solution was to make real-time reports out of that data with Power BI to help prioritise and plan tasks in a lean way. From these Power BI reports, end-users can anticipate, plan, and optimise what is relevant to do next based on output balance and other targets.
Another reason to create Power BI report-based solution is data mining, for example, to see the trends where results are developing, follow up on tool capacity usage, and evaluate processes. Also, in Power BI, user can integrate several data sources into one place and see results in one view from several sources. The secondary solution that was made is Report App for manual in-puts. Report App was created with Microsoft Power Apps. The root reason for creating that option was that all data does not come from tools, so there is an option to collect those missing tasks from each module through that App. The Report App database is Excel, visualised via Power BI and in Report App itself.
Based on the case studies, this thesis is divided into parts that explain the background of Project Management, Lean, and Agile Kanban methods that gave the guidelines to this project. Then the Data processing part is telling more details about big data, Databases, SQL, DAX in Power BI, and Power Apps. Presentation of the work is limited due to the company’s high confidentiality policy.
Another reason to create Power BI report-based solution is data mining, for example, to see the trends where results are developing, follow up on tool capacity usage, and evaluate processes. Also, in Power BI, user can integrate several data sources into one place and see results in one view from several sources. The secondary solution that was made is Report App for manual in-puts. Report App was created with Microsoft Power Apps. The root reason for creating that option was that all data does not come from tools, so there is an option to collect those missing tasks from each module through that App. The Report App database is Excel, visualised via Power BI and in Report App itself.
Based on the case studies, this thesis is divided into parts that explain the background of Project Management, Lean, and Agile Kanban methods that gave the guidelines to this project. Then the Data processing part is telling more details about big data, Databases, SQL, DAX in Power BI, and Power Apps. Presentation of the work is limited due to the company’s high confidentiality policy.