Kaelyn_Murphy_2-3 Journal_ Data_Assessment_Preparation

.docx

School

Southern New Hampshire University *

*We aren’t endorsed by this school

Course

300

Subject

Business

Date

Apr 3, 2024

Type

docx

Pages

4

Uploaded by BaronKuduPerson693

Report
1 2-3 Journal: Data Assessment Preparation Kaelyn Murphy Kaelyn.murphy@snhu.edu Southern New Hampshire University DAT-300-T3038 Data Valid: Getting Right Data
2 Determine if the data set reveals a problem. How will you know if the data set represents an organizational challenge? To determine if the data set reveals a problem, we must first understand the object or purpose of the analysis we will be performing. Understanding the objective will help us develop questions to determine the correct data and the right amount of data is being collected. Utilizing the Data Quality Management (DQM) process assists with identifying organizational challenges and managing organizational change. The DQM is a continuous process that defines the parameters of what is acceptable data quality wise to meet business needs and levels by analyzing the quality of the data, identifying anomalies, and defining the business requirements (Mosley, M. Bracket, M., Earley, S. and Henderson, D., 2010). The DQM allows for inspection and control process to monitor the data and how it conforms to business needs. Determine if the data set is usable. How will you know if the data set is suitable for an assessment? To determine if the data set is suitable for assessment, we should ensure that the data is complete and consistent. Complete and consistent data should result in no missing values or errors within the data. The data should be up to date and relevant to the objective we are attempting to accomplish. Ensuring data is complete, consistent, accurate, relevant, and up to date will assist in determining the useability of the data present. Assess the data set for consistency and completeness. What will you do to verify that you have all the accurate data needed to complete a data quality assessment? Consistency ensures the data in one set is consistent with the data in another set. Completeness ensures that certain attributes always have assigned values and that all appropriate rows are present. To ensure data is consistent and complete, the DAMA suggests performing a bottom-up and top- down assessment. The bottom-up assessment allows for direct data analysis to reveal any data
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help