Is there a Tableau connector that will give me access to the Azure Log Analytics tables in my workspace? I see that there are connectors out of the box for SQL server, Data Lake and Synapse but not one for log analytics. There is a link on the MSFT site to move that log analytics data to SQL but that would increase costs on our side besides the work needed, perhaps data factory, to get the data moved.
The idea is to create reports off log analytics data, creating some dashboards and leveraging the local Tableau expertise. PowerBI has a free connector but we are not too familiar with that tool.
Tnanks for any help you may provide.
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I have a scenario where I would like to query Azure Data warehouse tables within the Log Analytics workspace and using those records I need to create a result set and prepare a chart.
I do see some objects in log analytics workspace like a database, table but not sure what is the purpose and are these objects specific to a resource or generic and how to use them I couldn't get documentation for these objects can somebody guide me on this.
Unfortunately, you cannot use Azure Log Analytics to query Azure SQL Data Warehouse.
Use Azure Data Studio to connect and query data in Azure SQL data warehouse.
Recommended tools for querying data in Azure SQL Data Warehouse.
Azure Log Analytics is used to write, execute, and manage Azure Monitor log queries in the Azure portal. You can use Log Analytics queries to search for terms, identify trends, analyze patterns, and provide many other insights from your data.
For more information about log queries, see Overview of log queries in Azure Monitor.
For a detailed tutorial on writing log queries, see Get started with log queries in Azure Monitor.
I want to integrate Azure data lake storage with Grafana for visualization of time series data. I need to know what all the tools I can use to make it possible.
I used ADF to extract data from csv files stored in data lake and move to a table in Azure data explorer. After that, I used Azure data explorer plugin in grafana to visualize the same. It worked fine. But I need to know is there any other approach which may be better or cost-effective.
Integrating Grafana with Azure Data Lake is the best option when compared to others because the other options include data movements using ADF and additional cost for Azure SQL Datawarehouse along with the cost of PowerBI.
Reason:
Grafana is a leading open source software designed for visualizing time series analytics. It is an analytics and metrics platform that enables you to query and visualize data and create and share dashboards based on those visualizations. Combining Grafana’s beautiful visualizations with Azure Data Explorer’s snappy ad hoc queries over massive amounts of data, creates impressive usage potential.
The Grafana and Azure Data Explorer teams have created a dedicated plugin which enables you to connect to and visualize data from Azure Data Explorer using its intuitive and powerful Kusto Query Language. In just a few minutes, you can unlock the potential of your data and create your first Grafana dashboard with Azure Data Explorer.
For more details on visualizing data from Azure Data Explorer in Grafana please visit our documentation, “Visualize data from Azure Data Explorer in Grafana”.
Other options:
For Azure Data Lake Gen1:
You can use a mix of services to create visual representations of data stored in Data Lake Storage Gen1.
You can start by using Azure Data Factory to move data from Data Lake Storage Gen1 to Azure SQL Data Warehouse.
After that, you can integrate Power BI with Azure SQL Data Warehouse to create visual representation of the data.
For Azure Data Lake Gen2:
You can use a mix of services to create visual representations of data stored in Data Lake Storage Gen2.
You can start by using Azure Data Factory to move data from Data Lake Storage Gen2 to Azure SQL Data Warehouse.
After that, you can integrate Power BI with Azure SQL Data Warehouse to create visual representation of the data.
Hope this helps.
They just released a new guide. This is for Grafana 5.3
https://learn.microsoft.com/en-us/azure/data-explorer/grafana
you are able to test this by running Grafana in a Docker container (or for real, if you want). I followed the guide, and it is working almost exactly as expected. The only issue I am having is Grafana is concatenating the column name and the data in the column, making reading and formatting tricky.
I'm doing some tests with Azure Data Lake Analytics and I can’t add a new SQL Server database as a Data Source. When I click on "Add data source", the only two available options are: "Azure Data Lake Storage Gen1" and "Azure Storage".
What I want is to add one SQL Server database so that I can run U-SQL queries against it.
Our SQL Server firewall is correctly configured to allow access to Azure Services, but I am not allowed to add it as a data source.
How can this be done? Is it a matter of other configuration issues?
Any help would be greatly appreciated.
Per my research ,there is no other configuration issues for sql server data source in DLA. Based on this official doc, DLA only supports two data sources:Data Lake Store and Azure Storage.
As workaround , I suggest you using Azure Data Factory to transfer data from sql server database to azure storage so that you could run U-SQL script against data source.
Any concern,please let me know.
I am using ADF to connect to sources and get data into Azure Data Lake store. After getting data into Data Lake Store, I want to do some transformation, aggregation and use that data in SSRS reports and also for creating Cubes.
Can anyone suggest me which will be the best option (Azure Data Lake Analytics or Azure SQL DW) ?
I am looking here to make a decision on to take which one after Data lake.
There are no more Azure SQL DW. What we have now are Azure Synapse (same as Azure DW) and Azure Synapse Analytics (instead of Azure Datalake analytics). Microsoft is stopping support (develop) USQL and Azure Datalake analytic. If volume of your data is huge and you want use Polybase technology the best choice is Azure Synapse and Azure Synapse Analytics. You can rich your ADF by using Databricks to do analytics stuff. By using Polybase you can do ELT instead of ETL.
Microsoft Azure is not anymore investing on Azure Data Lake Analytics (ADLA) , you can evidently see that number of enhancements /updates in last couple of years are almost none in ADLA. While on the other side Azure SQL Data Warehouse is their flagship service ( recently names as azure synapse analytics) and hence getting enhanced and updated very fast. Synapse is based on MPP architecture and provides all required capabilities of big data computing.
What is the size of your data? Azure Data Lake is more meant for petabyte size big data processing and Azure SQL Data Warehouse for large relational DWH solutions (starting from 250/500 GB and up).
With Azure Data Lake you can even have the data from a data lake feed a NoSQL database, a SSAS cube, a data mart, or go right into Power BI. With Azure SQL Datawarehouse you can have cubes, Power BI reports and SSRS
If you need SQL Server Reporting Services, Integration Services (and you have complex SSIS logic), and Analysis Services (SSAS), you may better consider an Azure SQL VM.
Currently as part of our requirements we are working with the below Azure components
Azure Event Hub
Azure Stream Analytics
Azure Table Storage
Azure Sql DB
Basically with first 3 components, we will be building an Analytics and Reports platform.
Currently as we just started we analyze the data from Azure Table Storage and display it in the analytics dashboard.
Recently we came across a new Azure product Azure Data Lake . Doing some research on microsoft website , we could see we can easily migrate data from Azure Table Storage (with help of Azure Data Factory) to Azure Lake Store. Creating big data pipelines using Azure Data Lake and Azure Data Factory
As we go through the above link, it's mentioned that we need to create an Azure Data Lake Analytics pipeline to process the data.
So what am unclear is the where will be analytics output data will be saved. Do we need to save the analytics output to some DB ? or can we real-time analytics through a Http request ?
We have huge number rows of records in Azure Table Storage that will be moved to Azure Data Lake. For this scenario is it a good option or Can we go an analytics-based solution from Azure Table Storage itself.
Please share your thoughts
You can store your analytics output data on Azure Data Lake Store (a data repository that enables you to store all kinds of data in their raw format without defining schemas.) after processing it through Azure Data lake Analytics (An analytics service that enables you to run jobs on data sets without having to think about clusters.)
As you said "We have huge number rows of records in Azure Table Storage that will be moved to Azure Data Lake.", I think performing analytics on data placed on Azure data lake store is much more efficient because it offers unlimited storage with immediate read/write access to it and scaling the throughput you need for your workloads. It's also offers small writes at low latency for big data sets. So I believe it is better choice then Azure Table storage.