Merge branch 'main' into patch-8

Author: dfreniche

docs/1-mongodb-atlas/setup-lab.mdx

@@ -2,10 +2,10 @@
 description: Setting up your MongoDB Atlas account, importing Library data 
 ---
 
-# 👐 Set up Lab
+# 👐 Set Up Lab
 
-To follow along you'll need:
-- a MongoDB Atlas account
-- test data. In this case, this is books, authors and reviews data for a library management system.
+To follow along, you'll need:
+- A MongoDB Atlas account.
+- Test data. In this case, this is book, author, and review data for a library management system.
 
-👐 To get both, open the [Intro Lab](https://mongodb-developer.github.io/intro-lab/docs/intro) and follow it (only takes 10-15 mins) to get your database ready. Return here when finished!
+👐 To get both, open the [intro lab](https://mongodb-developer.github.io/intro-lab/docs/intro) and follow it (only takes 10-15 mins) to get your database ready. Return here when finished!

docs/20-what-is-aggregation/1-what-is-aggregation.mdx

@@ -1,18 +1,17 @@
 ---
-description: Learn what is an Aggregation Pipeline 
+description: Learn what an aggregation pipeline is. 
 ---
 
-# 📘 What is an Aggregation Pipeline
+# 📘 What is an Aggregation Pipeline?
 
 ![](/img/20-what-is-aggregation/aggregation-pipeline.png)
 
-An Aggregation Pipeline is similar to unix commands connected using pipes. 
-We can Construct modular, composable processing pipelines.
+An aggregation pipeline is similar to unix commands connected using pipes. We can construct modular, composable processing pipelines.
 
-An aggregation pipeline consists of one or more _stages_ that processes documents:
+An aggregation pipeline consists of one or more _stages_ that process documents:
 
 Each stage performs an operation on the input documents. For example, a stage can filter documents, group documents, and calculate values.
 
 The documents that are the output of a stage are passed as the input to the next stage.
 
-An aggregation pipeline can return results for groups of documents. For example, return the total, average, maximum, and minimum values, etc.
+An aggregation pipeline can return results for groups of documents. For example, return the total, average, maximum, and minimum values, etc.

docs/20-what-is-aggregation/2-sql-vs-aggregation.mdx

@@ -1,14 +1,14 @@
 ---
-description: Let's compare SQL with an Aggregation Pipeline 
+description: Let's compare SQL with an aggregation pipeline. 
 ---
 
 # 📘 SQL vs Aggregations
 
 ## SQL
 
-A SQL query statement usually starts with a `SELECT` where we put a list of the fields we need, then a `FROM` clause to state the table/s (or as in this case the subquery) that will return the rows. We can filter out using `WHERE` and group data using `GROUP`.
+A SQL query statement usually starts with a `SELECT` where we put a list of the fields we need, then a `FROM` clause to state the table/s (or in this case, the subquery) that will return the rows. We can filter out using `WHERE` and group data using `GROUP`.
 
-We read this from the inside. If there's too much nesting is not easy to follow.
+We read this from the inside. If there's too much nesting, it's not easy to follow.
 
 ```SQL
 SELECT
@@ -33,9 +33,9 @@ FROM (
 GROUP BY city;
 ```
 
-## Equivalent MongoDB Aggregation Pipeline
+## Equivalent MongoDB aggregation pipeline
 
-Here we pass three stages, one to return one document per element in the `address` array, then we filter out to get only the documents that have a `home` address location and finally we do the grouping. As we'll see, this can be split and tested separately, and resembles our code. 
+Here we pass three stages: one to return one document per element in the `address` array, and then we filter out to get only the documents that have a `home` address location. Finally, we do the grouping. As we'll see, this can be split and tested separately and resembles our code. 
 
 ```js
 db.customers.aggregate([
@@ -59,4 +59,4 @@ db.customers.aggregate([
 
 :::info
 See also [SQL to Aggregation Mapping Chart](https://www.mongodb.com/docs/manual/reference/sql-aggregation-comparison/)
-:::
+:::

docs/20-what-is-aggregation/3-structure-aggregation.mdx

@@ -1,10 +1,10 @@
 ---
-description: See the parts that compose an Aggregation Pipeline 
+description: See the parts that compose an aggregation pipeline. 
 ---
 
-# 📘 Structure of an aggregation pipeline
+# 📘 Structure of an Aggregation Pipeline
 
-To interact with a relational database we typically use SQL, a 4th Generation language to access our data. With MongoDB we instead get data and transform it in incremental steps.
+To interact with a relational database, we typically use SQL, a 4th-generation language, to access our data. With MongoDB, we instead get data and transform it in incremental steps.
 
 An aggregation pipeline is composed of [__stages__](https://www.mongodb.com/docs/manual/reference/operator/aggregation-pipeline/).
 
@@ -20,7 +20,7 @@ db.mycollection.aggregate([
 
 ## Example
 
-An Aggregation Pipeline that does the same than above SQL statement could be:
+An aggregation pipeline that does the same as the above SQL statement could be:
 
 ```
 db.mycollection.aggregate([
@@ -63,4 +63,4 @@ db.mycollection.aggregate([
       },
   },
 ])
-```
+```

docs/30-simple-queries/0-using-library-database.mdx

@@ -1,12 +1,11 @@
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
-# 👐 Using the library database
+# 👐 Using the Library Database
 
 ## Select the library database
 
-💻 We'll use the `library` database for all of the hands-on exercises in this lab.
-If you haven't already, import the [library data](https://mdb.link/import-library-data) into your database cluster.
+💻 We'll use the `library` database for all of the hands-on exercises in this lab. If you haven't already, import the [library data](https://mdb.link/import-library-data) into your database cluster.
 
 <Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
@@ -19,13 +18,13 @@ Select the correct database in the aggregation pipeline builder.
   </TabItem>
   <TabItem value="mongodb-shell" label="MongoDB Shell">
 
-To do that, in a MongoDB shell type in:
+To do that, in a MongoDB shell, type:
 
 ```js
 use library
 ```
 
-You can show all collections with
+You can show all collections with:
 
 ```js
 show collections
@@ -36,7 +35,7 @@ show collections
 🦸‍♂️ 💻 How would you switch to a database called `orders`?
 
 :::info
-Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on lab.
+Extra activity! Do it if you have extra time or are following along at home. It won't be covered during the hands-on lab.
 :::
 
 <details>
@@ -47,7 +46,7 @@ Extra activity, do it if you have extra time or are following at home, won't be
 use orders
 ```
 
-Even if this database does not yet exists, MongoDB can change to it. If we create a collection, users, etc. then this DB will get created.
+Even if this database does not yet exist, MongoDB can change to it. If we create a collection, users, etc., then this DB will be created.
 
 Remember to get back to the library database by using:
 
@@ -57,13 +56,13 @@ use library
 </div>
 </details>
 
-## 🦸‍♂️ Showing all Databases
+## 🦸‍♂️ Showing all databases
 
 :::info
-Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab
+Extra activity! Do it if you have extra time or are following along at home. It won't be covered during the hands-on lab.
 :::
 
-You can also list other databases in your MongoDB instance with
+You can also list other databases in your MongoDB instance with:
 
 ```js
 show databases

docs/30-simple-queries/1-empty-aggregation.mdx

@@ -1,11 +1,11 @@
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
-# 👐 Empty aggregation pipeline
+# 👐 Empty Aggregation Pipeline
 
 ## An empty aggregation
 
-This code is the equivalent to a `SELECT * FROM AUTHORS`. Returns a [cursor](https://www.mongodb.com/docs/manual/reference/method/js-cursor/) with all documents in the `authors` collection:
+This code is the equivalent of a `SELECT * FROM AUTHORS`. It returns a [cursor](https://www.mongodb.com/docs/manual/reference/method/js-cursor/) with all documents in the `authors` collection:
 
 <Tabs groupId="aggregations">
 
@@ -29,7 +29,7 @@ This code is the equivalent to a `SELECT * FROM AUTHORS`. Returns a [cursor](htt
 db.authors.aggregate([])
 ```
 
-We can iterate over the returned cursor and get more documents typing `it`. 
+We can iterate over the returned cursor and get more documents by typing `it`. 
 
 👐 Return all the documents in the `books` collection and iterate to get the next page of books.
 
@@ -47,10 +47,10 @@ it
 ## 🦸‍♂️ Cursor methods
 
 :::info
-Extra activity, do it if you have extra time or are following at home, won't be covered during the hands-on Lab
+Extra activity! Do it if you have extra time or are following along at home. It won't be covered during the hands-on lab.
 :::
 
-A [cursor](https://www.mongodb.com/docs/manual/reference/method/js-cursor/) has several useful methods, for instance we can check the size of the returned cursor with `itcount`
+A [cursor](https://www.mongodb.com/docs/manual/reference/method/js-cursor/) has several useful methods. For instance, we can check the size of the returned cursor with `itcount`.
 
 ```js
 cursor.itcount()

docs/30-simple-queries/2-match.mdx

@@ -20,13 +20,13 @@ The `<expression>` portion of the $match operator can be any valid MongoDB expre
 
 ## Matching book documents
 
-<Tabs groupId="aggregations-year">
+<Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
 
     First, make sure you select the `books` collection in the Atlas UI. 
     <Screenshot src="/img/30-simple-queries/select-books-collection.png" url="http://cloud.mongodb.com/" alt="Atlas UI database deployment with the books collection highlighted." />
 
-    Then, navigate to the `Aggregation` tab and click `Add Stage`.
+    Then, navigate to the `Aggregation` tab and click `</> TEXT`.
     <Screenshot src="/img/30-simple-queries/new-aggregation.png" url="http://cloud.mongodb.com/" alt="Atlas UI database deployment with aggregation tab highlighted." />
 
     Say we want all the books from the year 2010. We can add a `$match` stage to filter the documents from the books collection:
@@ -58,7 +58,7 @@ The `<expression>` portion of the $match operator can be any valid MongoDB expre
 <summary>Answer</summary>
 <div>
 
-<Tabs groupId="aggregations-pages">
+<Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
 ```js
 [
@@ -86,7 +86,7 @@ If we need to add more conditions using AND, we can do it with the `$and` operat
 
 If we want all the books with 100 pages with exactly `totalInventory` 2, we can use a `$and` operator. This takes an array of documents with all the conditions that should be true for the AND to succeed:
 
-<Tabs groupId="aggregations-and">
+<Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
 ```js
 [
@@ -187,7 +187,7 @@ db.books.aggregate([{$match: {$and: [{pages: 100}, {year: 2015}]}}]).itcount()
 
 We can do an implicit AND just passing a document with all the conditions (instead of an array of documents):
 
-<Tabs groupId="aggregations-shorthand-and">
+<Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
 ```js
 [
@@ -211,7 +211,7 @@ db.books.aggregate([{$match: {pages: 100, totalInventory: 2}}])
 <summary>Answer</summary>
 <div>
 
-<Tabs groupId="aggregations-shorthand-and-exercise">
+<Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
 ```js
 [

docs/30-simple-queries/3-project.mdx

@@ -62,7 +62,7 @@ A document from the `books` collection looks like:
 If we're interested just in the titles, we can use `$project` to select just the fields we're interested in. As an example, to get just the book's title and year we'll write:
 
 
-<Tabs groupId="project">
+<Tabs groupId="aggregations">
   <TabItem value="atlas" label="Atlas UI">
 ```js
 [

docs/40-using-arrays/2-search-inside-objects-in-arrays.mdx

@@ -1,6 +1,6 @@
 # 👐 Searching inside Objects in arrays
 
-In our books we're using the [Attribute Pattern](https://www.mongodb.com/developer/products/mongodb/attribute-pattern/) to have different attributes in our documents. As we can see in the [sample doc](/docs/simple-queries/project) we have an `attributes` array, containing several objects, each with the same structure:
+In the books collection, we're using the [Attribute Pattern](https://www.mongodb.com/developer/products/mongodb/attribute-pattern/) to store different attributes in our documents. As we can see in the [sample doc](/docs/simple-queries/project), we have an `attributes` array, containing several objects, each with the same structure:
 
 ```js
 attributes: [

docs/intro.mdx

@@ -7,10 +7,10 @@ sidebar_position: 0
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
-|Lab goals|Learn about Aggregation Pipelines writing Aggregation Pipelines|
+|Lab goals|Learn about aggregation pipelines writing aggregation pipelines|
 |-|-|
-|What you'll learn|What are Aggregation Pipelines |
-||How are they different from simple MongoDB queries or SQL|
+|What you'll learn|What are aggregation pipelines? |
+||How are they different from simple MongoDB queries or SQL?|
 ||How to use simple pipelines to get data, filter it, show the fields needed|
 ||How to write more advanced pipelines, querying arrays, counting and sorting results|
 ||How to do JOINs using $lookup|
@@ -19,11 +19,11 @@ import TabItem from '@theme/TabItem';
 ||How to write aggregations using popular programming languages (TBD)|
 |Time to complete|90 mins|
 
-In the navigation bar and in some pages, you will notice some icons. Here is their meaning:
+In the navigation bar and on some pages, you will notice some icons. Here are their meanings:
 
 |Icon|Meaning|
 |-|:-|
-|📘|Lecture material - If you're following along in an instructor lead session, they probably have covered this already.|
+|📘|Lecture material - If you're following along in an instructor-led session, they probably have covered this already.|
 |👐|Hands-on content - Get ready to get some work done. You should follow these steps.|
-|💬|Discussion - Item to discuss during the Lab|
-|🦸|Advanced content - This content isn't covered during the lab, but if you're interested in learning more, you can check it out.|
+|💬|Discussion - Item to discuss during the lab|
+|🦸|Advanced content - This content isn't covered during the lab, but if you're interested in learning more, you can check it out.|