Evaluation of Relational Data-Intensive Information Management Architecture
Siltanen, Sampo Matias (2017)
2017
Tietojohtaminen
Talouden ja rakentamisen tiedekunta - Faculty of Business and Built Environment
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Hyväksymispäivämäärä
2017-06-07
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201705241459
https://urn.fi/URN:NBN:fi:tty-201705241459
Tiivistelmä
Big Data has been a phenomenon for some years now. The well accepted solution for Big Data management has been based on distributed filesystems, but the need for faster and more accurate analytics has created a need for alternative solutions. To implement alternative solutions, they need to be evaluable and the concept should be proofed.
This study set out to find a way to evaluate the use of relational databases with Data Vault architecture in a cloud environment for a Big Data solution. The purpose of this study was to proof the concept, and offer theoretical backing and support for the architecture design.
The research was carried out with a design science research methodology to form an artifact to evaluate the solution architecture. The theory for the model was formed with literature review about data warehousing, Data Vault, Big Data, and cloud computing. By using the research methodology, an artifact was developed based on the theory gathered. The artifact was then reviewed by a professional group and evaluated with an interview.
The results of this study are that Big Data management solution should be evaluated through the characteristics of Big Data in all phases of information management separately. This study recognized volume, velocity, variety, veracity, validity, and volatility to the characteristics that should be considered. Information security was also recognized as an important aspect, but it should be considered as its’ on accord. Information management phases used in this study were data acquisition, data storage, and analytics.
This study set out to find a way to evaluate the use of relational databases with Data Vault architecture in a cloud environment for a Big Data solution. The purpose of this study was to proof the concept, and offer theoretical backing and support for the architecture design.
The research was carried out with a design science research methodology to form an artifact to evaluate the solution architecture. The theory for the model was formed with literature review about data warehousing, Data Vault, Big Data, and cloud computing. By using the research methodology, an artifact was developed based on the theory gathered. The artifact was then reviewed by a professional group and evaluated with an interview.
The results of this study are that Big Data management solution should be evaluated through the characteristics of Big Data in all phases of information management separately. This study recognized volume, velocity, variety, veracity, validity, and volatility to the characteristics that should be considered. Information security was also recognized as an important aspect, but it should be considered as its’ on accord. Information management phases used in this study were data acquisition, data storage, and analytics.