Domain "Industrial Data"; References to videos and presentations

docs/domain/document/index.md

@@ -6,6 +6,11 @@ Learn how to efficiently store JSON or other structured data, also nested, and
 how to query this data with ease, based on CrateDB's `OBJECT` data type.
 
 Storing documents in CrateDB provides the same development convenience like the
-document-oriented storage layer of Lotus Notes / Domino, CouchDB, and MongoDB.
+document-oriented storage layer of Lotus Notes / Domino, CouchDB, MongoDB, and
+PostgreSQL's `JSON(B)` types.
 
 - [](inv:cloud#object)
+- [Unleashing the Power of Nested Data: Ingesting and Querying JSON Documents with SQL]
+
+
+[Unleashing the Power of Nested Data: Ingesting and Querying JSON Documents with SQL]: https://youtu.be/S_RHmdz2IQM?feature=shared

docs/domain/index.md

@@ -8,10 +8,11 @@ how to use CrateDB optimally, related to different topic domains.
 
 
 ```{toctree}
-:maxdepth: 3
+:maxdepth: 1
 
 document/index
 search/index
+industrial/index
 timeseries/index
 ../integrate/ml/index
 ```

docs/domain/industrial/index.md

@@ -0,0 +1,52 @@
+(daq)=
+(iiot)=
+(industrial)=
+(industry-40)=
+# Industrial Data
+
+Learn how to use CrateDB in industrial / IIoT / Industry 4.0 scenarios within
+engineering, manufacturing, and other operational domains.
+
+In the realm of Industrial IoT, dealing with diverse data, ranging from
+slow-moving structured data, to high-frequency measurements, presents unique
+challenges.
+
+The complexities of industrial big data are characterized by its high variety,
+unstructured features, different data sampling rates, and how these attributes
+influence data storage, retention, and integration.
+
+Today's warehouses are complex systems with a very high degree of automation.
+The key to the successful operation of these warehouses lies in having a
+holistic view on the entire system based on data from various components like
+sensors, PLCs, embedded controllers and software systems.
+
+
+
+## TGW Insights
+
+After trying multiple database systems, TGW Logistics moved to CrateDB for
+its ability to aggregate different data formats and ability to query this
+information without much hassle.
+
+In the second presentation, you will learn how TGW leverages CrateDB to build
+digital twins of physical warehouses around the world.
+
+- [Fixing data silos in a high-speed logistics environment]
+- [Challenges of Storing and Analyzing Industrial Data]
+
+**What's inside**
+
+- The Complexity of IoT Data: An examination of the unique properties of
+  industrial IoT data, including slow-moving structured information and
+  high-frequency measurements.
+
+- Challenges and Solutions: Discussion of the difficulties in data storage,
+  retention, and integration posed by this complexity, and how CrateDB
+  provides a targeted solution.
+
+- Real-World Applications: Exploration of actual customer use cases to
+  illustrate how CrateDB can be applied in various industrial scenarios.
+
+
+[Challenges of Storing and Analyzing Industrial Data]: https://youtu.be/ugQvihToY0k?feature=shared
+[Fixing data silos in a high-speed logistics environment]:  https://youtu.be/6dgjVQJtSKI?feature=shared

docs/domain/timeseries/index.md

@@ -8,6 +8,7 @@ Learn how to optimally use CrateDB within time series use-cases.
 - [Financial data collection and processing using pandas]
 - [](inv:cloud#time-series)
 - [](inv:cloud#time-series-advanced)
+- [Time-series data: From raw data to fast analysis in only three steps]
 
 :::{toctree}
 :hidden:
@@ -17,3 +18,4 @@ normalize-intervals
 :::
 
 [Financial data collection and processing using pandas]: https://community.crate.io/t/automating-financial-data-collection-and-storage-in-cratedb-with-python-and-pandas-2-0-0/916
+[Time-series data: From raw data to fast analysis in only three steps]: https://youtu.be/7biXPnG7dY4?feature=shared

docs/index.md

@@ -127,6 +127,20 @@ application and topic domains.
 :::
 
 
+:::{grid-item-card} Industrial Data
+:link: industrial
+:link-type: ref
+:link-alt: CrateDB in industrial / IIoT / Industry 4.0 scenarios
+:padding: 3
+:text-align: center
+:class-card: sd-pt-3
+:class-body: sd-fs-1
+:class-title: sd-fs-5
+
+{material-outlined}`precision_manufacturing;1.3em`
+:::
+
+
 :::{grid-item-card} Time Series Data
 :link: timeseries
 :link-type: ref