Merge pull request #176 from quixio/dev

Docs Release 2023-06-003

README.md

@@ -7,6 +7,10 @@ This repository is the source content for the Quix documentation that is publish
 
 To get a free Quix account, [sign up](https://portal.platform.quix.ai/self-sign-up).
 
+## Docs releases
+
+You can find detailed information on docs releases in the [docs repo Wiki page](https://github.com/quixio/quix-docs/wiki/Docs-Releases).
+
 ## Contributing
 
 If you would like to contribute to the docs, there are two main ways:
@@ -42,6 +46,6 @@ If you are part of the Quix technical writing team, or you contribute frequently
 
 ## Getting in touch
 
-If you need any help, please sign up to the [Quix community forum](https://forum.quix.io/){target=_blank}.
+If you need any help, please sign up to the [Quix community forum](https://forum.quix.io/).
 
 Thanks!

docs/apis/data-catalogue-api/streams-paged.md

@@ -1,8 +1,8 @@
 # Paged streams
 
 You can fetch all streams within a
-[workspace](../../platform/definitions.md#workspace), across
-[topics](../../platform/definitions.md#topics) and locations, with a
+[workspace](../../platform/glossary.md#workspace), across
+[topics](../../platform/glossary.md#topics) and locations, with a
 single call. If you’re working with a large number of streams, you can
 use pagination parameters to group the results into smaller pages.
 

docs/apis/index.md

@@ -4,28 +4,16 @@ The Quix Platform provides the following APIs:
 
 ## Data Catalogue
 
-The [Data Catalogue HTTP API](data-catalogue-api/intro.md) allows you
-to fetch data stored in the Quix platform. You can use it for exploring
-the platform, prototyping applications, or working with stored data in
-any language with HTTP capabilities.
+The [Data Catalogue HTTP API](data-catalogue-api/intro.md) allows you to fetch data stored in the Quix platform. You can use it for exploring the platform, prototyping applications, or working with stored data in any language with HTTP capabilities.
 
 ## Streaming Writer
 
-The [Streaming Writer API](streaming-writer-api/intro.md) allows you
-to stream data into the Quix platform via HTTP. It’s an alternative to
-using our C\# and Python client libraries. You can use the Streaming Writer API from
-any HTTP-capable language.
+The [Streaming Writer API](streaming-writer-api/intro.md) allows you to stream data into the Quix platform via HTTP. It’s an alternative to using our C\# and Python client libraries. You can use the Streaming Writer API from any HTTP-capable language.
 
 ## Streaming Reader
 
-As an alternative to the client library, the Quix platform supports real-time data
-streaming over WebSockets, via the [Streaming Reader
-API](streaming-reader-api/intro.md). Clients can receive updates on
-data and definitions for parameters and events, as they happen. The
-examples use the Microsoft SignalR JavaScript client library.
+As an alternative to the client library, the Quix platform supports real-time data streaming over WebSockets, via the [Streaming Reader API](streaming-reader-api/intro.md). Clients can receive updates on data and definitions for parameters and events, as they happen. The examples use the Microsoft SignalR JavaScript client library.
 
 ## Portal API
 
-The [Portal API](portal-api.md) gives access to the Portal interface
-allowing you to automate access to data including Users, Workspaces, and
-Projects.
+The [Portal API](portal-api.md) gives access to the Portal interface allowing you to automate access to data including Users, Workspaces, and Projects.

docs/apis/portal-api.md

@@ -1,6 +1,5 @@
-Portal API gives access to the Portal interface allowing you to automate
-access to data including Users, Workspaces, and Projects.
+# Portal API
 
-Refer to [Portal API
-Swagger](https://portal-api.platform.quix.ai/swagger){target=_blank} for more
-information.
+The Quix Portal API gives access to the Portal interface allowing you to automate access to data including Users, Workspaces, and Projects.
+
+Refer to [Portal API Swagger](https://portal-api.platform.quix.ai/swagger){target=_blank} for more information.

docs/apis/streaming-reader-api/intro.md

@@ -1,11 +1,9 @@
 # Introduction
 
-As an alternative to [Quix Streams](../../client-library/subscribe.html), the Quix platform
-supports real-time data streaming over WebSockets. Clients can receive
-updates on data and definitions for parameters and events, as they
-happen. The examples shown use the Microsoft
-[SignalR](https://docs.microsoft.com/en-us/aspnet/core/signalr/javascript-client?view=aspnetcore-5.0){target=_blank}
-JavaScript client library.
+As an alternative to [Quix Streams](../../client-library-intro.md), the Quix platform supports real-time data streaming over WebSockets. Clients can receive updates on data and definitions for parameters and events, as they happen. 
+
+The examples shown use the Microsoft
+[SignalR](https://docs.microsoft.com/en-us/aspnet/core/signalr/javascript-client?view=aspnetcore-5.0){target=_blank} JavaScript client library.
 
 ## Documentation
 
@@ -15,5 +13,4 @@ JavaScript client library.
 
   - [Reading data](reading-data.md)
 
-  - [Subscription & Event
-    reference](subscriptions.md)
+  - [Subscription and Event reference](subscriptions.md)

docs/apis/streaming-writer-api/create-stream.md

@@ -12,7 +12,7 @@ supplying any other additional properties required.
 
 ## Before you begin
 
-  - You should have a [Workspace set up](../../platform/definitions.md#workspace) with at least one [Topic](../../platform/definitions.md#topics).
+  - You should have a [Workspace set up](../../platform/glossary.md#workspace) with at least one [Topic](../../platform/glossary.md#topics).
 
   - [Get a Personal Access Token](authenticate.md) to authenticate each
     request.
@@ -24,7 +24,7 @@ To create a new stream, send a `POST` request to:
     /topics/${topicName}/streams
 
 You should replace `$\{topicName}` in the endpoint URL with the name of
-the [Topic](../../platform/definitions.md#topics) you wish to create the
+the [Topic](../../platform/glossary.md#topics) you wish to create the
 stream in. For example, if your topic is named “cars”, your endpoint url
 will be `/topics/cars/streams`.
 

docs/apis/streaming-writer-api/send-data.md

@@ -7,7 +7,7 @@ timestamps.
 
 ## Before you begin
 
-  - You should have a [Workspace set up](../../platform/definitions.md#workspace) with at least one [Topic](../../platform/definitions.md#topics).
+  - You should have a [Workspace set up](../../platform/glossary.md#workspace) with at least one [Topic](../../platform/glossary.md#topics).
 
   - [Get a Personal Access
     Token](authenticate.md) to authenticate each

docs/apis/streaming-writer-api/stream-metadata.md

@@ -6,7 +6,7 @@ exist.
 
 ## Before you begin
 
-  - You should have a [Workspace set up](../../platform/definitions.md#workspace) with at least one [Topic](../../platform/definitions.md#topics).
+  - You should have a [Workspace set up](../../platform/glossary.md#workspace) with at least one [Topic](../../platform/glossary.md#topics).
 
   - [Get a Personal Access
     Token](authenticate.md) to authenticate each

docs/index.md

@@ -1,36 +1,50 @@
 # Quix Documentation
 
-Welcome to the Quix documentation!
+Welcome to the Quix developer documentation!
+
+!!! tip
+
+    Our docs support hotkeys. Press ++slash++, ++s++, or ++f++ to activate search, ++p++ or ++comma++ to go to the previous page, ++n++ or ++period++ to go to the next page.
 
 ## Get started
 
 If you're new to Quix, here are some resources to help get you started quickly.
 
+First, sign up for a [free account](https://portal.platform.quix.ai/self-sign-up){target=_blank}.
+
 <div class="grid cards" markdown>
 
 - __What is Quix?__
 
     ---
 
-    New to Quix? Find out more.
+    New to Quix? Find out more!
 
     [:octicons-arrow-right-24: What is Quix?](./platform/what-is-quix.md)
 
-- __Definitions__
+- __Quickstart__
 
     ---
 
-    Learn about common terms and definitions.
+    Get data into Quix, and display it, in under 10 minutes.
 
-    [:octicons-arrow-right-24: Definitions](./platform/definitions.md)
+    [:octicons-arrow-right-24: Quickstart](./platform/quickstart.md)
 
-- __Quickstart__
+- __Quix Tour__
+
+    ---
+
+    Build a complete stream processing pipeline in under 30 minutes.
+
+    [:octicons-arrow-right-24: Quix Tour](./platform/quixtour/overview.md)
+
+- __Glossary__
 
     ---
 
-    Start working with Quix Platform, the simple-to-use GUI for building real-time streaming applications.
+    List of Quix terms.
 
-    [:octicons-arrow-right-24: Quickstart](./platform/tutorials/quick-start/quick-start.md)
+    [:octicons-arrow-right-24: Glossary](./platform/glossary.md)
 
 -   __Help__
 

docs/platform/MLOps.md

@@ -62,6 +62,6 @@ In the Quix Portal, data teams can:
 
 Here are some suggested next steps to find out more about MLOps in Quix:
 
-* [Platform Quickstart](../platform/tutorials/quick-start/quick-start.md) - get started by building a complete sentiment analysis application without writing code, or optionally, dive deeper and write some code to ingest and transform data.
+* [Platform Quickstart](../platform/quickstart.md) - get data into Quix and displayed in real time in under 10 minutes.
 * [Building real-time ML pipelines tutorial](../platform/tutorials/train-and-deploy-ml/index.md) - train and run an ML model in Quix.
 * [Building real-time ML predictions](../platform/tutorials/data-science/index.md) - use data science and ML to predict bicycle availability in New York.

docs/platform/concepts/types-of-processing.md

@@ -0,0 +1,9 @@
+# Types of processing
+
+Types of processing:
+
+* Transformation - transform data from raw data to clean structured data tables (we expect this to happen in Quix, clean data before persisting it).
+* Exploratory data analysis (EDA) - using Quix data explorer and external tools like Jupyter Notebooks to understand data and find insights (generally a batch operation using persisted data in Quix and getting it to Jupyter)
+* Feature engineering - using external tools like Jupyter Notebooks to derive new data columns by making calculations from actual data columns eg calculate distance from time and speed. In ML distance would be a new feature (in McLaren Racing we called these 'virtual parameters') (this would happen outside of Quix, in Jupyter)
+* ML model training - using clean data to train a model (this would happen outside of Quix in Jupyter)
+* Back testing - using unseen data to test the model (traditionally this would happen outside of Quix in Jupyter, but now DS's can test their code in Quix against historic or live data)

docs/platform/concepts/types-of-transform.md

@@ -0,0 +1,24 @@
+# Types of transform
+
+Types of transform:
+
+1. Filtering: This pattern involves processing a stream of data and selecting specific records that meet certain criteria. It allows you to filter out irrelevant data and focus on the relevant information.
+
+2. Aggregation: Aggregation involves combining multiple data records from a stream into a single result. It is useful for calculating summary statistics, such as averages, counts, or maximum/minimum values, over a specific time window or key.
+
+3. Transformation: This pattern involves modifying the structure or content of the data as it flows through the stream. Transformations can include data enrichment, normalization, or any other necessary modifications to prepare the data for downstream processing.
+
+4. Joining: Joining patterns involve combining data from multiple streams based on a common key or attribute. It allows you to correlate information from different sources and create a unified view of the data.
+
+5. Windowing: Windowing involves dividing the data stream into discrete time intervals or windows and performing calculations or aggregations within each window. Windowing enables analysis over a specific period, such as sliding windows, tumbling windows, or session windows.
+
+6. Deduplication: This pattern removes duplicate records from a stream, ensuring that each event or data point is processed only once. Deduplication is essential for maintaining data integrity and preventing duplicate processing.
+
+7. Pattern matching: Pattern matching involves detecting predefined patterns or sequences of events within a stream. It is useful for identifying complex conditions or anomalies based on specific patterns of data.
+
+8. Splitting and routing: This pattern involves splitting a single stream into multiple substreams based on defined criteria or conditions. It enables parallel processing and allows different components to handle different subsets of the data.
+
+9. Time series analysis: Time series analysis patterns focus on analyzing and extracting insights from time-dependent data streams. Techniques like forecasting, anomaly detection, and trend analysis are commonly used in time series processing.
+
+10. Fan-out/Fan-in: This pattern involves duplicating a stream and sending it to multiple processing components in parallel (fan-out) and then aggregating the results back into a single stream (fan-in). It allows for scalable and parallel processing of data.
+