Fix minor typo in source-data-best-practices.md

dataschool/_chapters/data-governance/source-data-best-practices.md

@@ -55,7 +55,7 @@ If you're using Tableau, they have a feature called Data Interpreter that will d
 
 ## Visual, Drag & Drop Exploration
 
-In addition to SQL access, some BI products with drag and drop data explorers such as Tableau Desktop or Chartio's Visual SQL will handle writing the SQL for you.  Generally exploring data visually is much faster and more intuitive than writing raw SQL. Visual interfaces will handle changing data format strings, join paths, new groupings, unique dialects, etc. which will automatically you a lot of googling and debugging.
+In addition to SQL access, some BI products with drag and drop data explorers such as Tableau Desktop or Chartio's Visual SQL will handle writing the SQL for you.  Generally exploring data visually is much faster and more intuitive than writing raw SQL. Visual interfaces will handle changing data format strings, join paths, new groupings, unique dialects, etc. which will automatically save you a lot of googling and debugging.
 
 ![Chartio Visual SQL](/assets/images/Screen Shot 2019-09-30 at 9.44.02 PM.png)
 
@@ -102,4 +102,4 @@ Analyzing source data can be tricky since it has not been cleaned or modeled. Th
 * Design dashboards with pen and paper first
 * Keep an eye on query performance if you are hitting the production database
 
-Lastly, you should start exploring tools to pipe-in multiple sources of data that are not handled by your SQL-based BI tool to build your Data Lake.
+Lastly, you should start exploring tools to pipe-in multiple sources of data that are not handled by your SQL-based BI tool to build your Data Lake.