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Activity5 This week, you will explore the Data Management Body of Knowledge (DAMA-DMBOK) to learn more about the importance of managing data, challenges in managing data, and principles of effective...

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Activity5
This week, you will explore the Data Management Body of Knowledge (DAMA-DMBOK) to learn more about the importance of managing data, challenges in managing data, and principles of effective data management.
Select one of the data repository scenarios provided under weekly resources. Use the hypothetical use case description provided and assume you need to support a recently formed team of researchers who need to work with this data and future data curated for and by the team. Review the scenario to understand the general goals and objectives of the research group and become familiar with the types of data the team works with.
Create an initial data management plan as a technical report that includes the following:
1. Describe the role of architecture in the storage process (with an annotated diagram), the purpose of data modeling, and the importance of planning in your proposed design to manage the overall lifecycle of the data.
2. Explain how the data will be cataloged (including metadata), accessed, and stored and the policies and procedures that will guide the creation and preservation of new data that supports the team of researchers.
3. Provide details for a specific potential use case (in addition to the cu
ent use case) for the data and how these policies and procedures would apply to enable best practices in management and use of the data.
Length: 7 to 8-page technical report, not including title and references pages, and architecture diagram in the appendix
References: Include a minimum of 3 scholarly references (be sure that at least one of the three is a peer-reviewed research study involving data management planning from the school li
ary to support your ideas).
NB:
“Select one of the data repository scenarios provided under weekly resources.”
Here’s the link to the data repository scenario provided under weekly resources, and the required scholarly reference from li
ary. The files are also attached in case you are unable to access the below web link.
Data repository: https:
doi.org/10.7302/v559-6e13
Scholarly reference from school li
ary: DOI: https:
doi.org/10.2218/ijdc.v17i1.799

Activity5
This week, you will explore the Data Management Body of Knowledge (DAMA-DMBOK) to learn more about the importance of managing data, challenges in managing data, and principles of effective data management.
Select one of the data repository scenarios provided under weekly resources. Use the hypothetical use case description provided and assume you need to support a recently formed team of researchers who need to work with this data and future data curated for and by the team. Review the scenario to understand the general goals and objectives of the research group and become familiar with the types of data the team works with.
Create an initial data management plan as a technical report that includes the following:
1. Describe the role of architecture in the storage process (with an annotated diagram), the purpose of data modeling, and the importance of planning in your proposed design to manage the overall lifecycle of the data.
2. Explain how the data will be cataloged (including metadata), accessed, and stored and the policies and procedures that will guide the creation and preservation of new data that supports the team of researchers.
3. Provide details for a specific potential use case (in addition to the cu
ent use case) for the data and how these policies and procedures would apply to enable best practices in management and use of the data.
Length: 7 to 8-page technical report, not including title and references pages, and architecture diagram in the appendix
References: Include a minimum of 3 scholarly references (be sure that at least one of the three is a peer-reviewed research study involving data management planning from the school li
ary to support your ideas).
NB:
“Select one of the data repository scenarios provided under weekly resources.”
Here’s the link to the data repository scenario provided under weekly resources, and the required scholarly reference from li
ary. The files are also attached in case you are unable to access the below web link.
Data repository: https:
doi.org/10.7302/v559-6e13
Scholarly reference from school li
ary: DOI: https:
doi.org/10.2218/ijdc.v17i1.799
Answered 13 days After Mar 10, 2023

Solution

Banasree answered on Mar 20 2023
33 Votes
2
1. Ans.
As a data management professional tasked with supporting a research team that requires access to a data repository, it is important to develop a comprehensive data management plan that takes into consideration the overall lifecycle of the data, including storage, retrieval, and archiving. A well-designed architecture can play a crucial role in ensuring the successful management of data, and data (Greg Wilson et al., n.d.) modeling is equally important in developing a structure that supports the data repository's intended use. Additionally, effective planning is essential to ensure that the data repository is designed to meet the team's cu
ent and future data management needs.
Architecture plays a critical role in data storage by providing a framework for organizing data and enabling efficient data retrieval. The overall architecture of the data repository should be designed with the team's research goals in mind. A typical data storage architecture consists of three main components:
1. A storage area network (SAN),
2. A network-attached storage (NAS) device,
3. A database management system (DBMS).
The SAN is responsible for providing the underlying infrastructure that enables data storage, while the NAS serves as a gateway for accessing the data stored in the SAN. The DBMS is responsible for providing the database software that manages the data and makes it available to the research team. As mentioned, architecture refers to the overall framework that enables the storage, retrieval, and management of data. When designing an architecture for a data repository, it's important to consider the specific needs of the research team. Some questions to ask might include:
1. What types of data will be stored in the repository? For example, will it include images, videos, or text documents?
2. How much data will be stored in the repository, and how frequently will it be accessed?
3. What types of security and backup measures are required to ensure the data is secure and can be recovered in case of a disaster?
Based on the answers to these questions, a storage architecture can be designed that includes different types of storage devices, such as SANs, NASs, and databases. The architecture can also include additional components, such as backup systems, disaster recovery plans, and data security measures. To further illustrate the role of architecture in the storage process, consider the following annotated diagram:
In addition to the role of architecture in the storage process, data modeling plays a crucial role in designing an effective data repository. The purpose of data modeling is to develop a structure that accurately reflects the data repository's intended use. A well-designed data model enables the research team to retrieve data efficiently, while also ensuring data integrity and consistency. The data modeling process typically involves analyzing the data requirements and developing a conceptual, logical, and physical data model. The conceptual model identifies the high-level entities and relationships in the data repository, while the logical model defines the detailed structure of the data repository, and the physical model specifies how the data will be stored in the repository.
Finally, planning is essential for ensuring that the data repository is designed to meet the research team's cu
ent and future data management needs. The planning process should involve identifying the types of data that the team works with, analyzing data usage patterns, and developing a strategy for managing the data throughout its lifecycle. This strategy should include data archiving, data backup, and data retention policies that reflect the team's data management requirements. Effective planning also involves identifying potential risks to data security and developing a strategy for managing those risks.
In summary, effective data management involves designing an architecture that supports the intended use of the data repository, developing a data model that accurately reflects the data repository's structure, and planning for the overall lifecycle of the data. By taking a holistic approach to data management, it ensure that the research team has access to high-quality data that meets their data management needs.
2. Ans.
Cataloging data involves organizing it in a systematic and logical manner to facilitate its storage, retrieval, and use. Metadata is a critical component of data cataloging and refers to the information that describes data, such as its origin, format, content, and context....
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