Unit 03: LO 5 - 5.1 - Data quality

Ensuring the quality of data is like cooking with clean, sorted, and well-organized ingredients. It makes the end product (your analysis or report) much better. Let's look at how you can ensure data quality:

Data Cleansing

Think of data cleansing as washing your fruits and veggies before cooking. You're removing any "dirt" or errors that shouldn't be there.

How to Do It:

• Remove Duplicates: Duplicate entries can inflate your data and distort your results.

• Fix Typos and Inconsistencies: Check for any misspelled or inconsistent entries, like 'USA' and 'U.S.A.', and standardize them.

• Correct Null or Missing Values: Replace or remove any null or missing values in your data set.

Data Validation

Data validation is like checking the quality of your ingredients before you cook. You want to make sure everything is fresh and good to use.

How to Do It:

• Set Data Type Requirements: Specify the type of data you expect (e.g., text, numbers, dates) and reject any data that doesn't match.

• Use Regular Expressions: For text data, you can use regular expressions to define a pattern that the data should match. For instance, email addresses should fit a certain pattern.

• Range Checks: For numerical data, specify a range of acceptable values.

Data Sorting

Just as you would sort your ingredients into different bowls, sorting your data helps you organize it and find what you need more efficiently.

How to Do It:

• Alphabetical Sorting: Sort textual data in alphabetical order for easier reading and locating.

• Numerical Sorting: Sort numerical data in ascending or descending order, depending on your needs.

• Date Sorting: When working with time-series data, sort it chronologically.

Indexing

Indexing is like putting labels on your ingredient bowls so you can instantly know what is inside each. It makes accessing data faster.

How to Do It:

• Primary Key Index: In databases, always define a primary key for quick and unique identification of each record.

• Search Index: Create search indices for frequent queries to speed up data retrieval.

• Multi-Column Index: In some cases, you might want to index multiple columns for more complex queries.

By cleansing, validating, sorting, and indexing your data, you make sure your ingredients are clean, high-quality, well-organized, and easy to use, leading to better results in whatever you're cooking up.