Data Cleaning - The Format and Type of Data Imported - IT Assignment Help

Assignment Task:

Introduction

No matter how data are collected (in face-to-face interviews, telephone interviews, self-administered questionnaires, etc.), there will be some level of error. Messy data” refers to data that is riddled with inconsistencies. While some of the discrepancies are legitimate as they reflect variation in the context, others will likely reflect a measurement or entry error. These can range from mistakes due to human error, poorly designed recording systems, or simply because there is incomplete control over the format and type of data imported from external data sources. Such discrepancies wreak havoc when trying to perform analysis with the data. Before processing the data for analysis, care should be taken to ensure data is as accurate and consistent as possible.

The Data Cleaning Process

Data cleaning consists primarily in implementing error prevention strategies before they occur (see data quality control procedures later in the document). However, error-prevention strategies can reduce but not eliminate common errors and many data errors will be detected incidentally during activities such as:

• When collecting or entering data
• When transforming/extracting/transferring data
• When exploring or analysing data
• When submitting the draft report for peer review

Even with the best error prevention strategies in place, there will still be a need for actively and systematically searching for, detecting and remedying errors/problems in a planned way.

Data cleaning involves repeated cycles of screening, diagnosing, treatment and documentation of this process. As patterns of errors are identified, data collection and entry procedures should be adapted to correct those patterns and reduce future errors.

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