feat(discover-split): Update Discover, Alerts, Dashboards docs

docs/concepts/search/searchable-properties/events.mdx

@@ -8,7 +8,7 @@ Events are the underlying event data captured using Sentry SDKs — that is, err
 
 You can search by event properties in the following [sentry.io](https://sentry.io) pages:
 
-- Discover - in the query builder
+- Discover - in the query builder, depending on the dataset selection
 - Dashboards - within the widget builder, depending on dataset selection
 - Performance - only in transaction summaries
 - Issues - as indicated in the list below

docs/product/alerts/create-alerts/metric-alert-config.mdx

@@ -85,7 +85,6 @@ For some metric alerts, you can set the event type that you want to be alerted a
 - `event.type:error` OR `event.type:default`
 - `event.type:default`
 - `event.type:error`
-- `event.type:transaction`
 
 ### Tags & Properties
 

docs/product/dashboards/widget-builder/index.mdx

@@ -48,15 +48,19 @@ A big number visualization displays the current value of a single function. This
 
 ## Choose Your Dataset
 
-In the dataset selection step, choose which type of data you would like to use in your widget. This data is classified into two different datasets: [errors and transactions](#errors--transactions) and [issues](#issues).
+In the dataset selection step, choose which type of data you would like to use in your widget. This data is classified into four different datasets: [errors](#error), [transactions](#transactions), [issues](#issues), and [releases](#releases).
 
-### Errors & Transactions
+### Errors
+Choosing "Errors" allows you to query and aggregate error events in the same way you would for a [Discover Query](/product/explore/discover-queries/). This data is comprised of errors that occur in your application, which Sentry will use to group into issues. Some widget examples include:
 
-Choosing "Errors and Transactions" allows you to query and aggregate error and transaction events in the same way you would for a [Discover Query](/product/explore/discover-queries/). Some widget examples include:
+- Users most affected by errors
+
+### Transactions
+
+Choosing "Transactions" allows you to query and aggregate transaction events in the same way you would for a [Discover Query](/product/explore/discover-queries/). This data is comprised of events that track the performance of operations in your application. Some widget examples include:
 
 - Tracking performance of an endpoint
 - Throughput by country
-- Users most affected by errors
 
 ### Issues
 

docs/product/dashboards/widget-library/index.mdx

@@ -29,16 +29,16 @@ You can change the title, queries, fields, visualization types, sort order, and
 
 To monitor how your app is performing on a certain release, you can modify the "Duration Distribution" widget by adding the release version to the search condition:
 
-- Search condition 1: `event.type:transaction release.version:{version}`
+- Search condition 1: `release.version:{version}`
 
 To compare performance with another release version, you can add another query by clicking the "Add Query" button and querying for a different release version:
 
-- Search condition 2: `event.type:transaction release.version:{another_version}`
+- Search condition 2: `release.version:{another_version}`
 
 You can also compare performance before and after a certain version with the following conditions:
 
-- Search condition 1: `event.type:transaction release.version:<{version}`
-- Search condition 2: `event.type:transaction release.version:>={version}`
+- Search condition 1: `release.version:<{version}`
+- Search condition 2: `release.version:>={version}`
 
 ### Response thresholds
 
@@ -52,15 +52,15 @@ Set one of the y-axis values to `count()` and remove the other two axes:
 
 To the first query, add the search condition for satisfactory transaction duration (this example uses 300ms as the satisfactory response threshold):
 
-- Search condition 1: `event.type:transaction transaction.duration:<300`
+- Search condition 1: `transaction.duration:<300`
 
 Add another query for the tolerable condition by clicking the "Add Query" button. In this example, we're using the [Apdex](/product/performance/metrics/#apdex) definition where tolerable response times are between the satisfactory threshold and four times the satisfactory threshold:
 
-- Search condition 2: `event.type:transaction (transaction.duration:<1200 AND transaction.duration:>=300)`
+- Search condition 2: `transaction.duration:<1200 AND transaction.duration:>=300`
 
 Finally, add a third query for for the frustrating transaction duration:
 
-- Search condition 3: `event.type:transaction transaction.duration:>=1200`
+- Search condition 3: `transaction.duration:>=1200`
 
 The chart now shows cumulative counts at different response time thresholds.
 

docs/product/explore/discover-queries/query-builder.mdx

@@ -15,12 +15,17 @@ From the **Discover** page, you can build a query in three ways.
   2. Enter a new display name
   3. Click "Save"
 
-There are four main building blocks that impact the results of your saved query. You can use a combination of these to narrow down your search.
+There are five main building blocks that impact the results of your saved query, a combination of which can be used to narrow down your search.
 
-1. Project, environment, and date range filters
-2. Search Conditions
-3. Interactive Graph
-4. Table Columns
+1. Dataset selection
+2. Project, environment, and date range filters
+3. Search Conditions
+4. Interactive Graph
+5. Table Columns
+
+## Dataset Selection
+
+The dataset selector allows you to choose between querying for errors or transactions. This will determine the type of data you are querying for. You can only query one dataset at a time. The errors dataset will return events related to errors, while the transactions dataset will return transactions events for viewing performance data. 
 
 ## Filter by Project, Environment, and Date Range
 
@@ -101,8 +106,16 @@ Above the table, click "Columns" to open the modal that shows you a list of all
 
 ### Stacking Functions
 
-You can also add any of the following functions as columns to stack events:
+You can also add the following functions as columns to stack events, depending on the selected dataset:
+
+#### Errors
+- `count()`
+- `count_if(...)`
+- `count_unique(...)`
+- `eps()`
+- `epm()`
 
+#### Transactions
 - `any(...)`
 - `apdex(...)`
 - `avg(...)`

docs/product/explore/discover-queries/uncover-trends.mdx

@@ -24,7 +24,7 @@ Sentry notifies you in real-time when your application breaks, and then provides
 
 2. Select the projects, environments, and date range of errors you'd like to query.
 
-3. Sentry monitors different types of events for errors and performance. To query issues, filter by `event.type:error` in the search bar.
+3. Sentry monitors different types of events for errors and performance. To query issues, select the "Errors" dataset using the Dataset dropdown.
 
    ![Filter by Error type](./img/004.png)
 
@@ -57,7 +57,8 @@ The true power of **Discover** lies in its ability to query through all your err
 
 Create a report looking into all the errors occurring in the URL endpoints across your applications.
 
-- Search condition: `event.type:error has:url`
+- Dataset: Errors
+- Search condition: `has:url`
 - Table columns: `url`, `platform.name`, `count()`
 
 ![Errors by URL](./img/005.png)
@@ -71,7 +72,8 @@ Create a report looking into all the errors occurring in the URL endpoints acros
 
 Whether your code is running on mobile, in browser, or on a server, an unhandled fatal error might crash your application. To find out where those crashes are happening, run the following query in **Discover**:
 
-- Search condition: `event.type:error handled:no level:fatal`
+- Dataset: Errors
+- Search condition: `handled:no level:fatal`
 - Table columns: `mechanism`, `platform.name`, `count()`
 
   ![Crashes](./img/006.png)
@@ -87,7 +89,8 @@ To look deeper into one of the crash types:
 
 To find out which files in your codebase are generating the most errors, run the following query in **Discover**:
 
-- Search condition: `event.type:error has:stack.filename`
+- Dataset: Errors
+- Search condition: `has:stack.filename`
 - Table columns: `stack.filename`, `count()`, `count_unique(issue)`
 
 ![By File Names](./img/010.png)
@@ -102,7 +105,7 @@ You can continue exploring a specific filename by adding it to the filter and ch
 
 To find out how the health of a specific project is improving (or not) over time as you release new versions, create the following query:
 
-- Search condition: `event.type:error`
+- Dataset: Errors
 - Table columns: `release`, `count()`, `count_unique(issue)`
 
 ![Issues per release](./img/012.png)