Data Cleaning – The Key To Improving Data Quality
What Is Data Cleaning?This is the process of preparing raw data for analysis. After that, it is modified to remove any information that is irrelevant, incorrect, duplicated, and incomplete. This maintains the integrity and quality of the data so the organization can have accurate and valuable data.
Implementing Data CleaningHere are the steps your organization can take to implement an effective data cleaning process:
Create A StrategyCleaning comes later. First, you have to create a strategy to filter out data. This means to spot problems in the existing data and make it more relevant to what you need. There is a vast amount of data within an organization. This is why the first step is to choose the datasets you will utilize. Here are some questions to help you create a successful strategy:
- What is your core dataset?
- What are you trying to achieve through this dataset?
- Is the source reliable?
- Were accurate methods used to collect this dataset?
- Is it complete?
- How can the quality of this dataset be tested?