diff --git a/1-Introduction/03-defining-data/README.md b/1-Introduction/03-defining-data/README.md
index 4f7499bd..313dcbb6 100644
--- a/1-Introduction/03-defining-data/README.md
+++ b/1-Introduction/03-defining-data/README.md
@@ -21,7 +21,9 @@ This lesson focuses on identifying and classifying data by its characteristics a
 ## How Data is Structured
 
 ## Structured Data
-Structured data is data that is organized into rows and columns, where each row will have the same set of columns. Columns represent a value of a particular type and will be identified with a name describing what the value represents, while rows contain the actual values. A benefit of structured data is that it can be organized in such a way that it can be related to other structured data. However, because the data is designed to be organized in a specific way, making changes to its overall structure can take a lot of effort to do. For example, imagine you've been tasked to add additional data that currently doesn't exist in an existing structured data set. One option would be to add a new column, but you'll need to also decide if and how you'll add values to the existing rows in the dataset. 
+Structured data is data that is organized into rows and columns, where each row will have the same set of columns. Columns represent a value of a particular type and will be identified with a name describing what the value represents, while rows contain the actual values. Columns will often have a specific set of rules or restrictions on the values, to ensure that the values accurately represent the column. For example imagine a spreadsheet of customers where each row must have a phone number and the phone numbers never contain alphabetical characters. There may be rules applied on the phone number column to make sure it's never empty and only contains numbers. 
+
+A benefit of structured data is that it can be organized in such a way that it can be related to other structured data. However, because the data is designed to be organized in a specific way, making changes to its overall structure can take a lot of effort to do. For example, adding an email column to the customer spreadsheet means you'll need to if and how you'll add these values to the existing rows of customers in the dataset. 
 
 Examples of structured data: spreadsheets, relational databases, phone numbers, bank statements
 
@@ -29,7 +31,7 @@ Examples of structured data: spreadsheets, relational databases, phone numbers,
 *type description*
 
 ## Unstructured Data
-Unstructured data typically cannot be categorized into into rows or columns, or would take more effort to achieve when compared to structured data. Unstructured data is not organized into a specific format which makes it easier to add new information
+Unstructured data typically cannot be categorized into into rows or columns. There are tools and methods to convert an unstructured dataset into a structured format, but would take more effort to achieve. Unstructured data does not follow a is easier to add new information
 
 Examples of unstructured data: email, text files, social media, text messages, video files