Updates

Author: shsagir

articles/synapse-analytics/data-explorer/api/toc.yml

@@ -15,7 +15,7 @@ ms.subservice: data-explorer
 
 [Azure Data Explorer](/azure/data-explorer/data-explorer-overview) is a stand-alone, fast, and highly scalable data exploration service for log and telemetry data. The same underlying technology that runs the service is available in Azure Synapse as an integrated analytics service to complement its existing SQL and Spark services geared for data warehouse and data engineering machine learning scenarios.
 
-The native integration of Data Explore capabilities brings analytics log and time series workloads to Synapse in the form of Synapse Data Explorer pools. These pools offer close integration with and easier management of connectivity to other Synapse capabilities. Having all your machine and user data available and accessible in one place, and by leveraging the near real-time exploratory capabilities of Data Explorer, enables you to build solutions that drive business value.
+The native integration of Data Explore capabilities brings analytics log and time series workloads to Synapse in the form of Synapse Data Explorer pools. These pools offer close integration with, and easier management of connectivity to, other Synapse capabilities. Having all your machine and user data available and accessible in one place, and by leveraging the near real-time exploratory capabilities of Data Explorer, enables you to build solutions that drive business value.
 
 We recommend starting with Synapse Data Explorer if you are looking for a unified solution that combines big data and analytics capabilities.
 

articles/synapse-analytics/data-explorer/data-explorer-compare.md

@@ -1,5 +1,5 @@
 ---
-title: 'Create a Data Explorer pool using Synapse Studio (Preview)'
+title: 'Quickstart: Create a Data Explorer pool using Synapse Studio (Preview)'
 description: Create a Data Explorer pool using Synapse Studio by following the steps in this guide.
 ms.topic: quickstart
 ms.date: 08/20/2021

articles/synapse-analytics/data-explorer/data-explorer-create-pool-studio.md

@@ -19,10 +19,10 @@ Azure Synapse Analytics Data Explorer provides customers with an interactive que
 
 ## What makes Azure Synapse Analytics Data Explorer unique?
 
-* **Easy ingestion** - Data Explorer offers built-in integrations for no-code/low-code, high throughput data ingestion, and caching data from real-time sources. Data can be ingested from sources such as Event Hub, Kafka, Azure Data Lake, open source agents such as Fluentd/Fluent Bit, and a wide variety of cloud and on-premises data sources.
+* **Easy ingestion** - Data Explorer offers built-in integrations for no-code/low-code, high-throughput data ingestion, and caching data from real-time sources. Data can be ingested from sources such as Event Hub, Kafka, Azure Data Lake, open source agents such as Fluentd/Fluent Bit, and a wide variety of cloud and on-premises data sources.
 
-* **No complex data modeling** - With Data Explorer, there is no need to build complex data models and no need for complex scripting to transform data before it can be consumed.
-* **No index maintenance** - There is no need for maintenance jobs to optimize data for query performance and no need for index maintenance. With Data Explorer, all raw data is available immediately, allowing you to run high-performance and high-concurrency queries on your streaming and persistent data. You can use these queries to build near real-time dashboards and alerts, and connect operational analytics data with the rest of data analytics platform.
+* **No complex data modeling** - With Data Explorer, there is no need to build complex data models and no need for complex scripting to transform data before it's consumed.
+* **No index maintenance** - There is no need for maintenance tasks to optimize data for query performance and no need for index maintenance. With Data Explorer, all raw data is available immediately, allowing you to run high-performance and high-concurrency queries on your streaming and persistent data. You can use these queries to build near real-time dashboards and alerts, and connect operational analytics data with the rest of data analytics platform.
 * **Democratizing data analytics** - Data Explorer democratizes self-service, big data analytics with the intuitive Kusto Query Language (KQL) that provides the expressiveness and power of SQL with the simplicity of Excel. KQL is highly optimized for exploring raw telemetry and time series data by leveraging Data Explorer's best-in-class text indexing technology for efficient free-text and regex search, and comprehensive parsing capabilities for querying traces\text data and JSON semi-structured data including arrays and nested structures. KQL offers advanced time series support for creating, manipulating, and analyzing multiple time series with in-engine Python execution support for model scoring.
 * **Proven technology at petabyte scale** - Data Explorer is a distributed system with compute and storage that can scale independently, enabling analytics on gigabytes or petabytes of data.
 * **Integrated** - Azure Synapse Analytics provides interoperability across data between Data Explorer, Apache Spark, and SQL engines empowering data engineers, data scientists, and data analysts to easily, and securely, access and collaborate on the same data in the data lake.

articles/synapse-analytics/data-explorer/data-explorer-overview.md

@@ -0,0 +1,85 @@
+items:
+- name: List of functions
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/functions-library?context=/azure/synapse-analytics/context/context
+- name: bartlett_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/bartlett-test-fl?context=/azure/synapse-analytics/context/context
+- name: binomial_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/binomial-test-fl?context=/azure/synapse-analytics/context/context
+- name: comb_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/comb-fl?context=/azure/synapse-analytics/context/context
+- name: factorial_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/factorial-fl?context=/azure/synapse-analytics/context/context
+- name: kmeans_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/kmeans-fl?context=/azure/synapse-analytics/context/context
+- name: ks_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/ks-test-fl?context=/azure/synapse-analytics/context/context
+- name: normality_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/normality-test-fl?context=/azure/synapse-analytics/context/context
+- name: levene_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/levene-test-fl?context=/azure/synapse-analytics/context/context
+- name: mann-whitney-u-test-fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/mann-whitney-u-test-fl?context=/azure/synapse-analytics/context/context
+- name: perm_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/perm-fl?context=/azure/synapse-analytics/context/context
+- name: predict_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/predict-fl?context=/azure/synapse-analytics/context/context
+- name: predict_onnx_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/predict-onnx-fl?context=/azure/synapse-analytics/context/context
+- name: quantize_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/quantize-fl?context=/azure/synapse-analytics/context/context
+- name: series_dbl_exp_smoothing_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-dbl-exp-smoothing-fl?context=/azure/synapse-analytics/context/context
+- name: series_dot_product_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-dot-product-fl?context=/azure/synapse-analytics/context/context
+- name: series_downsample_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-downsample-fl?context=/azure/synapse-analytics/context/context
+- name: series_exp_smoothing_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-exp-smoothing-fl?context=/azure/synapse-analytics/context/context
+- name: series_fit_lowess_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-fit-lowess-fl?context=/azure/synapse-analytics/context/context
+- name: series_fit_poly_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-fit-poly-fl?context=/azure/synapse-analytics/context/context
+- name: series_fbprophet_forecast_fl()
+  displayName: functions library, prophet algorithm, predict
+  href: /azure/data-explorer/kusto/functions-library/series-fbprophet-forecast-fl?context=/azure/synapse-analytics/context/context
+- name: series_metric_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-metric-fl?context=/azure/synapse-analytics/context/context
+- name: series_moving_avg_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-moving-avg-fl?context=/azure/synapse-analytics/context/context
+- name: series_rate_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-rate-fl?context=/azure/synapse-analytics/context/context
+- name: series_rolling_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/series-rolling-fl?context=/azure/synapse-analytics/context/context
+- name: time_weighted_avg_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/time-weighted-avg-fl?context=/azure/synapse-analytics/context/context
+- name: two_sample_t_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/two-sample-t-test-fl?context=/azure/synapse-analytics/context/context
+- name: wilcoxon_test_fl()
+  displayName: functions library
+  href: /azure/data-explorer/kusto/functions-library/wilcoxon-test-fl?context=/azure/synapse-analytics/context/context

articles/synapse-analytics/data-explorer/data-explorer-query-with-pool.md

@@ -1,10 +1,4 @@
 items:
-- name: Context test (ignore)
-  items:
-  - name: Query using .NET Core
-    href: ../../../azure-sql/database/connect-query-dotnet-core.md?context=/azure/synapse-analytics/context/context
-  - name: Add an Azure Stream Analytics job
-    href: ../../sql-data-warehouse/sql-data-warehouse-integrate-azure-stream-analytics.md?context=/azure/synapse-analytics/context/context
 - name: Getting started with Kusto
   href: /azure/data-explorer/kusto/concepts/index?context=/azure/synapse-analytics/context/context
 - name: Tutorial

articles/synapse-analytics/data-explorer/functions-library/toc.yml

@@ -50,7 +50,7 @@ Pipelines are how Azure Synapse provides Data Integration - allowing you to move
 * **Trigger** - Executes a pipeline. It can be run manually or automatically (schedule, tumbling window or event-based)
 * **Integration dataset** - Named view of data that simply points or references the data to be used in an activity as input and output. It belongs to a Linked Service.
 
-## Data Explorer
+## Data Explorer (Preview)
 
 Azure Synapse Analytics Data Explorer provides customers with an interactive query experience to unlock insights from log and telemetry data.
 

articles/synapse-analytics/data-explorer/kusto-query-language/toc.yml

@@ -56,8 +56,8 @@ Azure Synapse Analytics Data Explorer provides customers with an interactive que
 
 Use Data Explorer as a data platform for building near real-time log analytics and IoT analytics solutions to:
 
-* Consolidate and correlate your logs and events data across on-prem, cloud, 3rd party data sources.
-* Accelerate your AI Ops journey (pattern recognition, anomaly detection, forecasting, etc.)
+* Consolidate and correlate your logs and events data across on-premises, cloud, third-party data sources.
+* Accelerate your AI Ops journey (pattern recognition, anomaly detection, forecasting, and more)
 * Replace infrastructure-based log search solutions to save cost and increase productivity.
 * Build IoT Analytics solution for your IoT data.
 * Build Analytical SaaS solutions to offer services to your internal and external customers.

articles/synapse-analytics/overview-terminology.md

@@ -581,8 +581,6 @@ items:
       href: data-explorer/data-explorer-create-pool-portal.md
     - name: Create a Data Explorer pool using the Synapse Studio
       href: data-explorer/data-explorer-create-pool-studio.md
-    - name: Query data with data explorer pools
-      href: data-explorer/data-explorer-query-with-pool.md
     - name: Monitor and diagnose pools
       href: data-explorer/data-explorer-monitor-pools.md
   - name: Kusto Query Language
@@ -593,6 +591,8 @@ items:
       href: data-explorer/management/toc.yml
     - name: API
       href: data-explorer/api/toc.yml
+    - name: Functions library
+      href: data-explorer/functions-library/toc.yml
 - name: Apache Spark
   items:
   - name: Overview