Scenario:I have formatted Excel files in ADLS, I want to access them in SSIS package and perform simple transformations and load them in to SQL DB.
What connection manager to use for fetching Excel files since these are not CSV files.
Using the Flexible File Source component on the data flow, you can connect SSIS to Azure data lake storage.
Install Azure feature pack for Integration Services (SSIS) extension to get the components required for Azure resources.
Provide all the details in Flexible File Source Editor properties to connect to Azure data lake as mentioned here.
Currently the source file formats supported are Text, Avro, ORC, Parquet.
Also, refer to this MS document for Configure the Azure Data Lake Store Connection Manager and this link for example.
Related
Usecase: I have data files of varying size copied to a specific SFTP folder periodically (Daily/Weekly). All these files needs to be validated and processed. Then write them to related tables in Azure SQL. Files are of CSV format and are actually a flat text file which directly corresponds to a specific Table in Azure SQL.
Implementation:
Planning to use Azure Data Factory. So far, from my reading I could see that I can have a Copy pipeline in-order to copy the data from On-Prem SFTP to Azure Blob storage. As well, we can have SSIS pipeline to copy data from On-Premise SQL Server to Azure SQL.
But I don't see a existing solution to achieve what I am looking for. can someone provide some insight on how can I achieve the same?
I would try to use Data Factory with a Data Flow to validate/process the files (if possible for your case). If the validation is too complex/depends on other components, then I would use functions and put the resulting files to blob. The copy activity is also able to import the resulting CSV files to SQL server.
You can create a pipeline that does the following:
Copy data - Copy Files from SFTP to Blob Storage
Do Data processing/validation via Data Flow
and sink them directly to SQL table (via Data Flow sink)
Of course, you need an integration runtime, that can access the on-prem server - either by using VNet integration or by using the self hosted IR. (If it is not publicly accessible)
have you ever made an azure data convert Azure Data Lake excel conversion to CSV file.
first, I have tried using SSIS with Azure Data Lake Source, but when Mapping is not possible, the choice is to add text.
second, says try using azure apps logic with create CSV table but the csv that comes out is only the structure in that folder
Thank you in advance
There is not a built-in way to extract from excel file in Azure data lake. I would suggest you to try one of the below approaches:
Write Custom .NET library for converting Excel to CSV and deploy that to Azure Data Lake Analytics. Azure Data Lake Analytics Programming Guide
Write a custom .NET activity in Azure Data Factory to do this. Custom Activities in Azure Data Factory
Use Azure Functions and Open XML do this activity as detailed in the stack overflow post
Use SSIS Package to do the conversion. You can have SSIS Runtimes in Azure Data Factory. SSIS packages running in Azure Data Factory
As I know about Azure, These isn't any way can help convert the excel file to csv directly.
You could follow these steps:
Download the excel file to you computer.
Import the excel file to the you SQL database.
Then export the table data as CSV file to you Blob Storage.
You could reference this document:
Import data from Excel to SQL Server or Azure SQL Database
Connect to Azure Blob Storage (SQL Server Import and Export
Wizard)
Hope this helps.
I have 20 files of type Excel/pdf located in different https server. i need to validate these file and load into azure storage Using Data Factory.I need to do apply some business logic on this data and load into azure SQL Database.I need to if we have to create a pipe line and store this data in azure blob storage and then load into Azure sql Database
I have tried creating copy data in data factory
My idea as below:
No.1
Step 1: Use Copy Activity to transfer data from http connector source into blob storage connector sink.
Step 2: Meanwhile, configure a blob storage trigger to execute your logic code so that the blob data will be processed as soon as it's collected into blob storage.
Step 3: Use Copy Activity to transfer data from blob storage connector source into SQL database connector sink.
No.2:
Step 1:Use Copy Activity to transfer data from http connector source into SQL database connector sink.
Step 2: Meanwhile, you could configure stored procedure to add your logic steps. The data will be executed before inserted into table.
I think both methods are feasible. The No.1, the business logic is freer and more flexible. The No.2, it is more convenient, but it is limited by the syntax of stored procedures. You could pick the solution as you want.
The excel and pdf are supported yet. Based on the link,only below formats are supported by ADF diectly:
i tested for csv file and get the below random characters:
You could refer to this case to read excel files in ADF:How to read files with .xlsx and .xls extension in Azure data factory?
I am new to Azure and hence trying to understand what services to use when and how.
At the moment, I have one excel file that has couple of tabs that require some transformation to create one excel file tab (inside the source file itself - say Tab "x"). The final tab "x" created is then being useful for creating one final excel file that is shared to various team.
At present, everything is done manually.
This needs to change and the excel file shared to team has to be automated. The source of the file is the excel file that has various tabs (excluding tab "x") and the reporting tool will be SSRS with excel data being stored in cloud.
Keeping this scenario in mind, what is the best way to store excel data into cloud? The excel data will be stored in cloud on a monthly basis. I am confused as to whether to store data in Azure-SQL, Azure Data Lake Gen 2 or Azure Data Lake Analytics or Azure SQL VM?
Every month data can be fetched from Excel file and populate into Azure using azure data factory. But I am not sure what is the best way to store data in the cloud considering the fact that some ETL process is needed to generate data in format similar to tab "X".
I think you can think about to using Azure SQL database.
Azure SQL database or SQL server support you import data from the excel( or csv) files. For more details and limits, please see: Import data from Excel to SQL Server or Azure SQL Database.
If your data have stored in Azure SQL database, you also can using EXCEL to get the data from Azure SQL database:
Connect Excel to a single database in Azure SQL Database and import data and create tables and charts based on values in the database. In this tutorial you will set up the connection between Excel and a database table, save the file that stores data and the connection information for Excel, and then create a pivot chart from the database values.
Reference: Import data from Excel to SQL Server or Azure SQL Database.
I think you don't need to store these excel files in Azure Data Lake.Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure Blob storage. It's still a storage.
The more Azure resource you use, the more cost you need to pay.
If your excel file stored in you local computer, you can using Azure Data Factory to access these local files or with self host integration runtime.
Please referenceļ¼ Copy data to or from a file system by using Azure Data Factory.
Hope this helps.
Your storage requirements are very minimal, so I would select Data Lake to store your documents. The alternative is Blob Storage, but I always prefer Data Lake because it works with Azure Active Directory.
In your scenario, drop it in the ADL, and use the ADL as the source in Azure Data Factory.
Edit:
Honestly, your original post is a little confusing. You have a RAW Excel document, you do some transformations on the RAW document, to generate an Excel Source document. This source document holds the final dataset that the dev team will use to build out SSRS reports. You need to make this dataset available to the teams so that they can connect to it to build the reports? My suggestion is to keep it simple and drop the final source dataset in Excel format, into blob or data lake storage and then ask the dev guys to pick it up from the location. If you are going the route of designing and maintaining a data pipeline (Blob > Data Factory > SQL, or CSV, TSV - then you are introducing unnecessary complications.
I have a directory on a local machine that holds various source files containing data that I need to load into an Azure SQL Server instance. The source files are in a variety of formats including xlsx, xls, csv, txt, dat. I built a solution a while back that transforms and loads these files into a local sql server and ssis instance (developers edition).
Now that development has concluded I would like to deploy the db and packages to Azure. With an Azure account I created SQL Server and SSIS instances, then I created a file storage account in Azure and copied the source file directory into the file store. My intention was that I would be able to simply take the old solution, change the sources from local files to an Azure data lake store source and the destinations from local db to the Azure Sql instance.
However, I am having a lot of complications with active directory authentication and it also appears that the datalake and blob source tools in SSIS only work for text and azro files. Is there not a ways for SSIS to easily access files in an Azure file store?