Discovering Data Tools in Azure
Hellsten, Lin (2022)
2022
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022060114356
https://urn.fi/URN:NBN:fi:amk-2022060114356
Tiivistelmä
As more and more organisations are adopting cloud services, it is important to understand how the services are applied in the real world. This product-based thesis aims to introduce and explore the data services in Azure. To better demonstrate the application, the thesis built a data platform utilizing the covid-19 data from open-source portals. Attention was given to the services used in the final product, namely Blob Storage, Azure Data Lake Stor age Gen2, Azure Data Factory, Azure SQL Database.
The thesis is formed into four parts. First it introduces the background, objectives, and scope of this thesis. Followed by the theoretical part, where it explains open-source data, reviews Agile methodology, and data solution architecture. The utilization of Azure Ser vices is also discussed in this part. The 2nd part is the foundation of the next phase. It also offers the reader the structure of how the data platform was designed and implemented. The product and details of implementation are discussed in the Empirical Part where the reader can have a deeper understanding on how this data platform was built. The result of the project and challenges is discussed in the last part.
The outcome of this thesis is a data platform implemented through Azure services which consists of a staging area, a ETL tool, and a data warehouse.
The thesis is formed into four parts. First it introduces the background, objectives, and scope of this thesis. Followed by the theoretical part, where it explains open-source data, reviews Agile methodology, and data solution architecture. The utilization of Azure Ser vices is also discussed in this part. The 2nd part is the foundation of the next phase. It also offers the reader the structure of how the data platform was designed and implemented. The product and details of implementation are discussed in the Empirical Part where the reader can have a deeper understanding on how this data platform was built. The result of the project and challenges is discussed in the last part.
The outcome of this thesis is a data platform implemented through Azure services which consists of a staging area, a ETL tool, and a data warehouse.