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Evaluating Data Quality in Database

Beth

Evaluating Data Quality in Database

Evaluating and improving the quality of data that is stored in any given information system are both vital and challenging tasks. For many organizations that rely on information as their most vital asset, ensuring a high level of data quality shows a strategic investment that is aimed at preserving the value of such assets. Good data quality means good service and exceptional relations with clients. However, ensuring high-quality standards is a huge task since there are many ways through which errors can be introduced in a system, and correcting them in a systematic way can be difficult. Issues with data quality fall into different categories. For example, poor data quality can be linked to inconsistencies among systems like semantic, format, and syntax inconsistencies. Other issues can be related to inconsistencies with reality, as shown by missing, incorrect, and obsolete data outliers and values. This paper focuses on evaluating and improving the quality of data in a system.

Recommend At Least Three Specific Tasks That Could Be Performed To Improve the Quality of Data Sets Using the Software Development Life Cycle (SDLC) Methodology

SDLC (software development life cycle) methodology can be described as a methodology with well-defined processes for developing high-quality software. It emphasizes adhering to stages of software development to avoid any error that may occur, hence interfering with the quality of data stored. There exist different phases in SDLC and different tasks that could be performed to improve the quality of data sets in these phases, as seen below.

Planning phase; after identifying the current problems, the team can determine the resources needed to implement the analyzed requirements (Georgiou et al., 2019). Hence, the task performed here is determining the feasibility of the project and ways for implementing the project successfully.

Design phase; proper design decisions are critical. The tasks that can be performed in this phase to ensure the quality of data is gathering the input of stakeholders and other suggestions on the best way to ensure that quality standards are maintained (Georgiou et al., 2019). Any failure at this phase can lead to cost overrun and the collapse of a project.

Maintenance phase; in this phase, the task that can be done to improve the quality of data is updating and advancing software to help match any change (Georgiou, Rizou & Spinellis, 2019). False null values should also be eliminated.

Recommend The Actions That Should Be Performed To Optimize Record Selections and Improve Database Performance From A Quantitative Data Quality Assessment.

The collection of quality data remains a priority for many organizations. To optimize record selections and to improve database performance from a quantitative data quality assessment, one of the actions that should be performed is avoidance. Before any transaction is executed, it should obtain all the locks it requires. This approach helps avoid rolling back any given conflicting transaction. Another action that can be performed is detection. DBMS should be allowed to periodically check the database for any deadlocks (Coronel & Morris, 2016; Shichkina, 2019). Should a deadlock be detected, appropriate measures can be taken promptly.

Suggest Three Maintenance Plans And Three Activities That Could Be Performed To Improve Data Quality.

To improve data quality, it is important that maintenance plans and activities are carried out. Maintenance plans in the database ensure a workflow of tasks, making sure that there are no inconsistencies, hence quality data. It is also a way of keeping different databases such as XML and multidimensional data databases optimized (Chen & Lee, 2019). One of the maintenance plans that can be undertaken to improve data quality is regular database checkups in which the quality of data available would be measured and old data refreshed. Secondly, companies must comprehend the data contained in their database because it helps in improving operations and communications (Curry, 2010). This should be followed by identifying data entry trends and determining possible bottlenecks that may exist and that hinder the collection of data. Finally, there is a need to share data management practices with all people who update records and capture and access the data in question.

A couple of activities are also required to be performed to improve data quality. One such activity is adaptive maintenance. This helps in keeping the database program usable in any circumstance. Secondly, there is a need for preventive maintenance activities such as regular inspections to ensure that the database works with no difficulties. Finally, corrective maintenance such as resolving equipment failure and restoring them to their operational state is important in maintaining data quality.

Suggest Methods That Would Be Efficient For Planning Proactive Concurrency Control Methods And Lock Granularities. Assess How Your Selected Method Can Be Used To Minimize The Database Security Risks That May Occur Within A Multiuser Environment.

In any database, concurrency control is provided to preserve the consistency of the database by preserving the execution of transactions and enforcing isolation among transactions. The method that would be appropriate for planning proactive concurrency control methods and lock granularities is the optimistic concurrency control method. This method is based on the assumption that most of the operations in a database do not conflict. The approach does not require locking and time stamping techniques to operate, making it cost-effective (Lemilxavuier, 2019). Rather, by using this method, transactions would be executed without any restriction till it is committed. In an optimistic method, transactions move through different phases, namely, read, validation, and write. In the read phase, transactions read the database and then execute the needed operations before making updates to private copies of database values. In the validation phase, transactions get validated. This helps to ensure that any change made would not impact the consistency and integrity of the database. At the writing phase, changes become applied permanently to the database.

Analyze How the Method Can Be Used To Plan Out the System Effectively and Ensure That the Number of Transactions Does Not Produce Record-Level Locking While the Database Is In Operation

The method can be used to plan out the system effectively by isolating any sensitive database. This will help in maintaining an accurate inventory of databases, making sure that transactions do not produce record-level locking while the database is in operation. Also, the method can be used for monitoring any deviation and implementing effective policies. Besides, it can be used for responding to any suspicious behavior by alerting and responding to any abnormalities present in the system.

References

Chen, J. K., & Lee, W. Z. (2019). An Introduction of NoSQL Databases based on their categories and application industries. Algorithms, 12(5), 106.

Coronel, C., & Morris, S. (2016). Database systems: design, implementation, & management. Cengage Learning.

Curry, J. (2010). Five Tips to Improve Data Quality. Retrieved from http://www.information-management.com/newsletters/five-tips-to-improve-data-quality10016939-1.html

Georgiou, S., Rizou, S., & Spinellis, D. (2019). Software development lifecycle for energy efficiency: techniques and tools. ACM Computing Surveys (CSUR), 52(4), 1-33.

Lemilxavuier. (2019). Concurrency Control Techniques. Retrieved from https://www.geeksforgeeks.org/concurrency-control-techniques/

Shichkina, Y. (2019). Approaches to Speed up Data Processing in Relational Databases. Procedia Computer Science, 150, 131-139.

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Question 

Tasks of Improving the Quality of Data Case Study

Read the following articles and incorporate them into your paper. You are encouraged to review additional articles as well.

Evaluating Data Quality in Database

Instructions

Write a 2–3 page paper in which you:

Go to the Strayer Library to find at least three quality resources in this assignment.

This course requires the use of Strayer Writing Standards. For assistance and information, please refer to the Strayer Writing Standards link in the left-hand menu of your course. Check with your professor for any additional instructions.

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Content

Name: w10a2

Description: w10a2 – Case Study

  Unacceptable Needs Improvement Competent Exemplary
Recommend at least three specific tasks that could be performed to improve the quality of data sets using the software development life cycle (SDLC) methodology. Include a thorough description of each activity per each phase. Points:

0 (0.00%)

Did not submit or incompletely recommended at least three specific tasks that could be performed to improve the quality of data sets using the SDLC methodology. Did not include a thorough description of each activity per each phase.

Feedback:

 Points:

11.25 (11.25%)

Partially recommended at least three specific tasks that could be performed to improve the quality of data sets using the SDLC methodology. Included a partial description of each activity per each phase.

Feedback:

 Points:

12.75 (12.75%)

Satisfactorily recommended at least three specific tasks that could be performed to improve the quality of data sets using the SDLC methodology. Included a thorough description of each activity per each phase.

Feedback:

 Points:

15 (15.00%)

Thoroughly recommended at least three specific tasks that could be performed to improve the quality of data sets using the SDLC methodology. Included a thorough description of each activity per each phase.

Feedback:
Recommend the actions that should be performed to optimize record selections and to improve database performance from a quantitative data quality assessment. Points:

0 (0.00%)

Did not submit or incompletely recommended the actions that should be performed to optimize record selections and to improve database performance from a quantitative data quality assessment.

Feedback:

 Points:

15 (15.00%)

Partially recommended the actions that should be performed to optimize record selections and to improve database performance from a quantitative data quality assessment.

Feedback:

 Points:

17 (17.00%)

Satisfactorily recommended the actions that should be performed to optimize record selections and to improve database performance from a quantitative data quality assessment.

Feedback:

 Points:

20 (20.00%)

Thoroughly recommended the actions that should be performed to optimize record selections and to improve database performance from a quantitative data quality assessment.

Feedback:
Suggest three maintenance plans and three activities that could be performed to improve data quality. Points:

0 (0.00%)

Did not submit or incompletely suggested three maintenance plans and three activities that could be performed to improve data quality.

Feedback:

 Points:

15 (15.00%)

Partially suggested three maintenance plans and three activities that could be performed to improve data quality.

Feedback:

 Points:

17 (17.00%)

Satisfactorily suggested three maintenance plans and three activities that could be performed to improve data quality.

Feedback:

 Points:

20 (20.00%)

Thoroughly suggested three maintenance plans and three activities that could be performed to improve data quality.

Feedback:
Suggest methods that would be efficient for planning proactive concurrency control methods and lock granularities. Assess how your selected method can be used to minimize the database security risks that may occur within a multiuser environment. Points:

0 (0.00%)

Did not submit or incompletely suggested methods that would be efficient for planning proactive concurrency control methods and lock granularities. Did not assess how your selected method can be used to minimize the database security risks that may occur within a multiuser environment.

Feedback:

 Points:

11.25 (11.25%)

Partially suggested methods that would be efficient for planning proactive concurrency control methods and lock granularities. Assessed how your selected method can be used to minimize the database security risks that may occur within a multiuser environment.

Feedback:

 Points:

12.75 (12.75%)

Satisfactorily suggested methods that would be efficient for planning proactive concurrency control methods and lock granularities. Assessed how your selected method can be used to minimize the database security risks that may occur within a multiuser environment.

Feedback:

 Points:

15 (15.00%)

Thoroughly suggested methods that would be efficient for planning proactive concurrency control methods and lock granularities. Assessed how your selected method can be used to minimize the database security risks that may occur within a multiuser environment.

Feedback:
Analyze how the method can be used to plan out the system effectively and ensure that the number of transactions does not produce record-level locking while the database is in operation. Points:

0 (0.00%)

Did not submit or incompletely analyzed how the method can be used to plan out the system effectively and ensure that the number of transactions does not produce record-level locking while the database is in operation.

Feedback:

 Points:

11.25 (11.25%)

Partially analyzed how the method can be used to plan out the system effectively and ensure that the number of transactions does not produce record-level locking while the database is in operation.

Feedback:

 Points:

12.75 (12.75%)

Satisfactorily analyzed how the method can be used to plan out the system effectively and ensure that the number of transactions does not produce record-level locking while the database is in operation.

Feedback:

 Points:

15 (15.00%)

Thoroughly analyzed how the method can be used to plan out the system effectively and ensure that the number of transactions does not produce record-level locking while the database is in operation.

Feedback:
Use at least 3 quality resources in this assignment. Points:

0 (0.00%)

No references provided.

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3.75 (3.75%)

Did not meet the required number of references; some references were poor-quality choices.

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 Points:

4.25 (4.25%)

Met number of required references; all references were high-quality choices.

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 Points:

5 (5.00%)

Exceeded number of required references; all references were high-quality choices.

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Clarity, writing mechanics, and formatting requirements. Points:

0 (0.00%)

More than 6 errors present.

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 Points:

7.5 (7.50%)

5–6 errors present.

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 Points:

8.5 (8.50%)

3–4 errors present.

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 Points:

10 (10.00%)

0–2 errors present.

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Name:w10a2

Description:w10a2 – Case Study

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