add predicate pushdown update

website/docs/docs/build/about-metricflow.md

@@ -21,7 +21,8 @@ Before you start, consider the following guidelines:
 
 ## MetricFlow
 
-MetricFlow is a SQL query generation tool designed to streamline metric creation across different data dimensions for diverse business needs. 
+MetricFlow is a SQL query generation tool designed to streamline metric creation across different data dimensions for diverse business needs. It renders SQL using <Term id="predicate-pushdown" />, which optimizes performance and brings faster query time.
+
 - It operates through YAML files, where a semantic graph links language to data. This graph comprises [semantic models](/docs/build/semantic-models) (data entry points) and [metrics](/docs/build/metrics-overview) (functions for creating quantitative indicators).
 - MetricFlow is a [BSL package](https://github.com/dbt-labs/metricflow) with code source available, and compatible with dbt version 1.6 and higher. Data practitioners and enthusiasts are highly encouraged to contribute.
 - As a part of the dbt Semantic Layer, MetricFlow empowers organizations to define metrics using YAML abstractions.

website/docs/docs/use-dbt-semantic-layer/sl-architecture.md

@@ -23,7 +23,6 @@ The dbt Semantic Layer includes the following components:
 | **Service layer** | Coordinates query requests and dispatching the relevant metric query to the target query engine. This is provided through dbt Cloud and is available to all users on dbt version 1.6 or later. The service layer includes a Gateway service for executing SQL against the data platform. | ❌ | ❌ | ✅ | ✅ | Proprietary, Cloud (Team & Enterprise) |
 | **[Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview)** | The interfaces allow users to submit metric queries using GraphQL and JDBC APIs. They also serve as the foundation for building first-class integrations with various tools. | ❌ | ❌ | ✅ | ✅ | Proprietary, Cloud (Team & Enterprise)|
 
-
 ## Feature comparison
 
 The following table compares the features available in dbt Cloud and source available in dbt Core:

website/docs/docs/use-dbt-semantic-layer/sl-faqs.md

@@ -174,7 +174,8 @@ No, the dbt Semantic Layer is flexible enough to work with many data modeling ap
 
 <Expandable alt_header="How are queries optimized to not scan more data than they should?">
 
-MetricFlow always tries to generate SQL in the most performant way, while ensuring the metric value is correct. It generates SQL in a way that allows us to add optimizations, like predicate pushdown, to ensure we don’t perform full table scans.
+
+MetricFlow always tries to generate SQL in the most performant way, while ensuring the metric value is correct. It generates SQL in a way that allows us to add optimizations, like <Term id="predicate-pushdown"  />, to ensure we don’t perform full table scans for faster query time.
 
 </Expandable>
 

website/docs/terms/predicate-pushdown.md

@@ -1,10 +1,13 @@
 ---
 id: predicate-pushdown
 title: predicate pushdown
-description: A predicate pushdown is an expression used to determine what rows in a database apply to a particular query
-displayText: Predicate pushdown
-hoverSnippet: A predicate pushdown is an expression used to determine what rows in a database apply to a particular query
+description: Predicate pushdown is an expression used to make database queries faster.
+displayText: predicate pushdown
+hoverSnippet: Predicate pushdown is an expression used make database queries faster by applying filters as early as possible in the query process. 
 ---
 
-A predicate pushdown is an expression used to determine what rows in a database apply to a particular query. For example, if you filter in a `WHERE` clause based on a specific dimension value, the database searches to determine what values in the database apply to the query. The optimization known as "predicate pushdown" involves applying this filtering process to the database, leading to enhanced and faster query performance.
+Predicate pushdown is a technique used to make database queries faster. Here's how it works:
 
+When you run a query with a filter (for example, using a `where` clause), the database has to find which rows match that filter.
+
+Predicate pushdown means that instead of checking each row one by one, the database applies the filter as early as possible in the query process. This way, it reduces the amount of data it needs to process, making the query run faster.