Optimizing Data Warehouse Implementation on Azure : A Comparative Analysis of Efficient Data Warehousing Strategies on Azure
Shah, Syed Tahoor Ullah (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202405069607
https://urn.fi/URN:NBN:fi:amk-202405069607
Tiivistelmä
This thesis addresses the optimal strategies for elevating Azure data warehouses, emphasizing adopting practical solutions to enhance data storage and management comprehensiveness through Microsoft Azure. This research investigates the advantages and disadvantages of different deployment methods and optimization approaches to make data analytics more efficient.
Data to be analyzed are deployment options and performance metrics based on data warehouse implementations on Windows Azure. The methods comprise tweaking the algorithm, which is then tested to ascertain its influence on speed and efficiency. Results generated from these operations and performance optimization techniques can become the harbingers of comprehensive applications and significantly advance data analytics results.
The study states that organizations can develop boosted operational efficiency and analytics capabilities by adequately exploiting the potential of the Azure data warehouse. By implementing practices, organizations can facilitate data management processes and, in the end, bolster decision-making. Overall, the results provide substantial implications in the area of cloud data management solutions and are very practical for organizations pursuing optimization of their data warehousing through Azure
Data to be analyzed are deployment options and performance metrics based on data warehouse implementations on Windows Azure. The methods comprise tweaking the algorithm, which is then tested to ascertain its influence on speed and efficiency. Results generated from these operations and performance optimization techniques can become the harbingers of comprehensive applications and significantly advance data analytics results.
The study states that organizations can develop boosted operational efficiency and analytics capabilities by adequately exploiting the potential of the Azure data warehouse. By implementing practices, organizations can facilitate data management processes and, in the end, bolster decision-making. Overall, the results provide substantial implications in the area of cloud data management solutions and are very practical for organizations pursuing optimization of their data warehousing through Azure