Data explorer

Author: t | 2025-04-24

In this article, you query data using the Azure Data Explorer. Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Azure Data Explorer In this article. Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Explore your data from end-to-end in the Azure Data Explorer web application, starting with data ingestion

Toolsverse Data Explorer: Data Explorer is a

Title description ms.reviewer ms.topic ms.date adobe-target What is Azure Data Explorer? Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. mblythe overview 08/28/2023 true What is Azure Data Explorer?Azure Data Explorer is a fully managed, high-performance, big data analytics platform that makes it easy to analyze high volumes of data in near real time. The Azure Data Explorer toolbox gives you an end-to-end solution for data ingestion, query, visualization, and management.By analyzing structured, semi-structured, and unstructured data across time series, and by using Machine Learning, Azure Data Explorer makes it simple to extract key insights, spot patterns and trends, and create forecasting models. Azure Data Explorer uses a traditional relational model, organizing data into tables with strongly-typed schemas. Tables are stored within databases, and a cluster can manage multiple databases. Azure Data Explorer is scalable, secure, robust, and enterprise-ready, and is useful for log analytics, time series analytics, IoT, and general-purpose exploratory analytics.Azure Data Explorer capabilities are extended by other services built on its query language: Kusto Query Language (KQL). These services include Azure Monitor logs, Application Insights, Time Series Insights, and Microsoft Defender for Endpoint.When should you use Azure Data Explorer?Use the following questions to help decide if Azure Data Explorer is right for your use case:Interactive analytics: Is interactive analysis part of the solution? For example, aggregation, correlation, or anomaly detection.Variety, Velocity, Volume: Is your schema diverse? Do you need to ingest massive amounts of data in near real-time?Data organization: Do you want to analyze raw data? For example, not fully curated star schema.Query concurrency: Will multiple users or processes use Azure Data Explorer?Build vs Buy: Do you plan on customizing your data platform?Azure Data Explorer is ideal for enabling interactive analytics capabilities over high velocity, diverse raw data. Use the following decision tree to help you decide if Azure Data Explorer is right for you::::image type="content" source="media/data-explorer-overview/decision-tree.png" alt-text="This image is a schematic workflow image of an Azure Data Explorer decision tree.":::What makes Azure Data Explorer unique?Data velocity, variety, and volumeWith Azure Data Explorer, you can ingest terabytes of data

Data Explorer – Exploration and Analytics

Camel Lenses" data-image-caption="" data-medium-file=" data-large-file=" src=" alt="Gear Review: Julbo Explorer 2.0 With Camel Lenses" width="840" height="561" srcset=" 1024w, 150w, 300w, 768w, 1998w, 1680w" sizes="(max-width: 840px) 100vw, 840px">The Explorer 2.0 has adjustable ear stems that are less malleable than the previous version. I like the more rigid ear stem structure, as they don’t bend out of place so easily. I’ve worn these sunglasses for long days on and off the trail and have never felt any unwanted throbbing or pressure points. The Explorer 2.0 gets top marks for comfort.Gear Review: Julbo Explorer 2.0 With Camel Lenses" data-image-caption="" data-medium-file=" data-large-file=" src=" alt="Gear Review: Julbo Explorer 2.0 With Camel Lenses" width="840" height="561" srcset=" 1024w, 150w, 300w, 768w, 1998w, 1680w" sizes="(max-width: 840px) 100vw, 840px">Gear Review: Julbo Explorer 2.0 With Camel Lenses" data-image-caption="" data-medium-file=" data-large-file=" src=" alt="Gear Review: Julbo Explorer 2.0 With Camel Lenses" width="840" height="561" srcset=" 1024w, 150w, 300w, 768w, 1998w, 1680w" sizes="(max-width: 840px) 100vw, 840px">The Explorer 2.0 comes with detachable side shades like the original Explorer. I’m glad julbo got rid of the bright green accents on the side shades in favor of a matte grey. The green accents on my old Explorers always bothered me. The new side shades on the Explorer 2.0 disappear and go unnoticed, just as they should.Gear Review: Julbo Explorer 2.0 With Camel Lenses" data-image-caption="" data-medium-file=" data-large-file=" src=" alt="Gear Review: Julbo Explorer 2.0 With Camel Lenses" width="840" height="561" srcset=" 1024w, 150w, 300w, 768w, 1998w, 1680w" sizes="(max-width: 840px) 100vw, 840px">Gear Review: Julbo Explorer 2.0 With Camel Lenses" data-image-caption="" data-medium-file=" data-large-file=" src=" alt="Gear Review: Julbo Explorer 2.0 With Camel Lenses" width="840" height="561" srcset=" 1024w, 150w, 300w, 768w, 1998w, 1680w" sizes="(max-width: 840px) 100vw, 840px">The Julbo Explorer 2.0 comes with a detachable neck lanyard, and is the same one found on my original Explorer and Bivouak model. This lanyard is a no-fuss accessory that allows me to drape the Explorer 2.0 from my neck when I need to take them off while on trail.Gear Review: Julbo Explorer 2.0 With Camel Lenses" data-image-caption="" data-medium-file=" data-large-file=" src=" alt="Gear Review: Julbo Explorer 2.0 With Camel Lenses" width="840" height="561" srcset=" 1024w, 150w, 300w, 768w, 1998w, 1680w" sizes="(max-width: 840px) 100vw, 840px">Lenses:On my previous pair of Julbo Explorers I opted for the Spectron 4 lenses. For the explorer 2.0, I paid a little more and got Julbo’s photochromic Camel lenses. I fell in love with the Camel lenses on my Julbo Bivouak, and have a hard time using any other lens option now. The Spectron 4 is still a great choice and superb option for those looking to save a little money. For those not familiar with lens features, functions, and terminology, I’ve put together an entire post to help you get accustomed. For those that just want a quick overview, I’ll cover the main points here.The first thing to look for when picking a lens to wear for hiking, backpacking, and mountaineering is that they offer complete and full spectrum UV protection. Most expensive sunglasses will have this. From there, you need to look at the protection

dataexplorer-docs/data-explorer/data-explorer-overview.md at

Server Using Database Explorer AppOn the Database Explorer tab, in the Connections section, click Connect and select the data source for the connection.If you stored your user credentials using the Set Credentials button, the Database Explorer app makes the connection and the Catalog and Schema dialog box opens.If you have not stored your user credentials, the connection dialog box opens. Enter your username and password, or leave these boxes blank if your database does not require them. Click Connect and the Catalog and Schema dialog box opens.Select the catalog and schema from the Catalog and Schema lists. Click OK.The app connects to the database and displays its tables in the Data Browser pane. A data source tab appears to the right of the pane. The title of the data source tab is the data source name that you defined during the setup. The data source tab contains empty SQL Query and Data Preview panes.Select tables in the Data Browser pane to query the database.Close the data source tab to close the SQL query. In the Connections section, close the database connection by clicking Close Connection.NoteIf multiple connections are open, close the database connection of your choice by selecting the corresponding data source from the Close Connection list.Connect to SQL Server Using JDBC Driver and Command LineConnect to an SQL Server database using the configured JDBC data source, username, and password. For example, this code assumes that you are connecting to a JDBC data source named MSSQLServer.datasource = "MSSQLServer";setSecret("usernamemssql");setSecret("passwordmssql");conn = database(datasource,getSecret("usernamemssql"),getSecret("passwordmssql"));Close the database connection. See AlsoApps Database Explorer Functionsdatabase | close | databaseConnectionOptions | saveAsDataSource | setoptions | testConnection Related TopicsCreate JDBC Data Source and Set Options ProgrammaticallyCreate SQL Queries Using Database Explorer AppJoin Tables Using Database Explorer AppData Preview Using Database Explorer AppModify and Delete Data SourcesDatabase Explorer App Error. In this article, you query data using the Azure Data Explorer. Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Azure Data Explorer In this article. Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Explore your data from end-to-end in the Azure Data Explorer web application, starting with data ingestion

Toolsverse Data Explorer: Data Explorer is a complete end-to

Customers can quickly query unstructured, semi-structured, and structured data including arrays and nested structures, as well as native and advanced time series support for creation, manipulation, and analysis of multiple time series with in-engine Python execution support for model scoring. When using Azure Synapse data explorer, compute and storage are decoupled allowing you to scale independently and optimize for price-performance. Type Price Azure Synapse data explorer compute $- per vCore-hour Standard ZRS data stored $- per TB/month Standard LRS data stored $- per TB/month Note: Compute for a Data Explorer pool in Azure Synapse will only require one of the above-mentioned standard data stores. Whether the ZRS or LRS data storage is used depends on Availability Zones where the Data Explorer pool is provisioned. Compute for running the Azure Synapse data explorer engine service responsible for indexing, caching data on local SSDs and premium storage as managed disks, and serving queries requires a minimum of two compute instances. Azure Synapse data explorer offers Compute Optimized (38 GB disk cache per vCore) and Storage Optimized (Medium - 128 GB disk cache per vCore, Large – 192 GB disk cache per vCore) workload types. You can change the workload type (keeping the same pool size) after the initial deployment with no impact on cost. Both workload types are billed on the Azure Synapse data explorer meter. Compute for running the data management (DM) service responsible for data ingestion from managed data pipelines such as Azure Data Lake Storage, Event Hub, and IoT Hub requires a minimum of two compute instances. The size and scale for the DM service instance is automatically managed based on the engine instance size and usage and is billed as 0.5 units of the Azure Synapse data explorer meter. Azure Synapse data explorer uses storage under the hood as the persistent layer where all the data is stored compressed and is billed as Standard LRS Data Stored or as Standard ZRS Data Stored where Availability Zones are available. Compute for a Data Explorer pool in Azure Synapse will only require one of the above-mentioned standard data stores. Whether the ZRS or LRS data storage is used depends on Availability Zones where the Data Explorer pool is provisioned. Other resources such as Network I/O and Bandwidth cost may be charged separately based on your cross-region usage. Azure Synapse data explorer is billed by rounding up usage to the nearest

Azure Data Explorer documentation - Azure Data Explorer

Data Explorer (TM) 4.0RequestDownloadlink when availableChoose the most popular programs from Developer ToolsYour vote:Latest version:4.0See allDeveloper:Applied Biosystems, Inc.ReviewDownloadComments Questions & Answers Edit program infoInfo updated on:Oct 03, 2020RequestDownloadlink when availableSoftware InformerDownload popular programs, drivers and latest updates easilyNo specific info about version 4.0. Please visit the main page of Data Explorer (TM) on Software Informer.Share your experience:Write a review about this program Comments Your vote:Notify me about replies Comment viaFacebookRelated software Air Explorer Two-pane explorer to access multiple cloud accounts from a single place.Tinytag Explorer Intuitive Windows program for all Tinytag data loggers.Internet Explorer Password It is a password recovery application for Internet Explorer.ArcGIS Explorer Desktop Data FreeIt expands the geodatabase functionality of the ArcGIS Explorer Desktop app.qTest eXplorer Integrated FreeqTest eXplorer - Integrated Edition is an add-on for qTest.Related storiesSee allMicrosoft is testing ads in Windows 11 File ExplorerBest Data Analysis Tools in 2022Google makes it easier to explore heritage sites worldwideSpotlight: File Explorer in Windows 11Best general-purpose softwareAI-OTBWebEx Meeting Manager for Internet ExplorerWOT para Internet ExplorerSolid State ION Internet Explorer PluginActuate LRX for Microsoft Internet ExplorerZipMail Windows Explorer and MS Office Extensions

Monitor Azure Data Explorer - Azure Data Explorer

In minutes via queued ingestion or streaming ingestion. You can query petabytes of data, with results returned within milliseconds to seconds. Azure Data Explorer provides high velocity (millions of events per second), low latency (seconds), and linear scale ingestion of raw data. Ingest your data in different formats and structures, flowing from various pipelines and sources.User-friendly query languageQuery Azure Data Explorer with the Kusto Query Language (KQL), an open-source language initially invented by the team. The language is simple to understand and learn, and highly productive. You can use simple operators and advanced analytics. Azure Data Explorer also supports T-SQL.Advanced analyticsUse Azure Data Explorer for time series analysis with a large set of functions including: adding and subtracting time series, filtering, regression, seasonality detection, geospatial analysis, anomaly detection, scanning, and forecasting. Time series functions are optimized for processing thousands of time series in seconds. Pattern detection is made easy with cluster plugins that can diagnose anomalies and do root cause analysis. You can also extend Azure Data Explorer capabilities by embedding python code in KQL queries.Easy-to-use wizardThe get data experience makes the data ingestion process easy, fast, and intuitive. The Azure Data Explorer web UI provides an intuitive and guided experience that helps you ramp-up quickly to start ingesting data, creating database tables, and mapping structures. It enables one time or a continuous ingestion from various sources and in various data formats. Table mappings and schema are auto suggested and easy to modify.Versatile data visualizationData visualization helps you gain important insights. Azure Data Explorer offers built-in visualization and dashboarding out of the box, with support for various charts and visualizations. It has native integration with Power BI, native connectors for Grafana, Kibana and Databricks, ODBC support for Tableau, Sisense, Qlik, and more.Automatic ingest, process, and exportAzure Data Explorer supports server-side stored functions, continuous ingest, and continuous export to Azure Data Lake store. It also supports ingestion time-mapping transformations on the server side, update policies, and precomputed scheduled aggregates with materialized views.Azure Data Explorer flowThe following diagram shows the different aspects of working with Azure Data Explorer.Generally speaking, when you interact. In this article, you query data using the Azure Data Explorer. Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Azure Data Explorer In this article. Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Explore your data from end-to-end in the Azure Data Explorer web application, starting with data ingestion