Collecting data from Azure Blob Storage

This guide explains how to collect data from Azure Blob Storage. To learn how to collect data from a different data source, go back to the Available data sources in Adverity overview.

Creating a datastream to collect data from Azure Blob Storage

The basics of creating a datastream to collect data from any data source are explained in our guide to Creating a datastream. This guide contains information about the specific steps to create a datastream to fetch data from Azure Blob Storage.

Configuration: Choose the data you want to collect from Azure Blob Storage

To choose what data to collect and customize the Azure Blob Storage datastream configuration, follow these steps:

(Optional) Rename your datastream.

In the Source section, select the container with your data using one of the following options:
- Select container name from the list
  
  Select one of the containers available with the selected authorization. You may not see the containers in this field if you do not have Azure Blob account owner rights. However, you can still collect your data from the container specified manually.
- Enter the name of your container
  
  Enter the name of the container you want to collect data from. The container name should match its URL.
In Add path to folder, enter the relative path to a folder with your data within the selected container.

For information on configuring other Azure Blob Storage fields, see Advanced Azure Blob Storage tips.

What's next?

Apply Data Mapping to your collected data to harmonize data collected from different sources in Adverity.
Transform your data to meet your needs by creating and applying enrichments to your datastream.
Load your data into Adverity Data Storage to send it to BI tools using data shares
Load your data into an external destination of your choice

Advanced Azure Blob Storage tips

Configuring data collection from Azure Blob Storage

In the Settings tab of your Azure Blob Storage datastream overview, you can configure a number of additional settings:

The File Matching Options section contains the following fields:

File pattern

Specify a regular expression that matches the file attachment from which to collect data. By default, File pattern is pre-populated with .* which collects data for any attached file.

Other examples of regular expressions for file patterns include:

.*\.xlsx collects every file that ends with .xlsx.
.*\.csv collects every file that ends with .csv.
.*Display.*\.csv collects every file that contains the (case-sensitive) phrase Display anywhere in the file name and also ends with .csv.

Zip match

If you collect data from ZIP or GZIP files, specify a regular expression that matches the file names within the ZIP or GZIP containers. Leave this field empty to collect all files within the ZIP or GZIP container.

Archive password

If the ZIP or GZIP files require password access, provide the password. By default, Adverity uses the previously entered password, if available.

Filename date match, Filename date pattern

Use these fields to fetch source files with a date in their filename that is within the fetch date range.

To use these fields the following conditions need to be satisfied:

The File pattern field includes the date placeholders for the date you want to match. For example, .*\_%Y-%m-%d\_.*\.csv.
In the Sortorder field, the Date match option is selected.

To match dates in the filenames, follow these steps:

In Filename date match, enter a regular expression that matches the date. For example, \d{4}-\d{2}-\d{2} or \d{8}.
In Filename date pattern, enter the date format used in the filenames using placeholders. For example, %Y-%m-%d or %m%d%Y.

For more information, see Fetching Azure Blob files based on dates in the filenames.

Keep filename

Select this checkbox to name data extracts using the same name as the corresponding source files. If you select this checkbox and the source filename stays the same between fetches, data in the corresponding data extract is overwritten.

The File Parsing section contains the following fields:

Parse

Select the data format used in the source files. The type of data format selected may cause additional fields to appear.

Source encoding

Select the character encoding used in the source files. By default, the option Auto-detect is selected and will automatically detect the encoding of the source files.

Delimiter

If CSV is selected in Parse, specify the character used to separate values in the CSV source files.

Quote Char

If CSV is selected in Parse, specify the character used to quote values with special characters in the CSV source files.

Quoting

If CSV is selected in Parse, specify when a quoting character should be added to the field values in the data extract. Choose from one of the following options:

Select all to add quote characters to everything in the data extract, regardless of the field type.
(Default) Select minimal to add quote characters only when required. For example, a quote character will be added to a field that contains either the Quote Char or Delimiter.
Select none to ensure no quote characters are added to the data extract.
Select nonnumeric to add quote characters to everything, except integer and float values.

Sheet

If Excel is selected in Parse, specify the name of the sheet within the Excel source files to import to Adverity.

Column offset

If Excel is selected in Parse, specify the number of columns that you do not want to import to Adverity from each Excel source file. For example, if the first column contains information that you do not want to import, specify 1 in this field.

Row offset

Specify the number of rows that you do not want to import to Adverity from each source file. For example, if the first row contains header information that you do not want to import, specify 1 in this field. This field is available for all parse types.

Skip initial space

If CSV is selected in Parse, select this checkbox to ignore any whitespace that follows the selected delimiter character.

The File Processing section contains the following fields:

Process all

By default, Adverity only processes the most recently uploaded files. Select this checkbox to process all files that match the criteria you specify.

Recursive

By default, Adverity only searches for source files in the folder that you specify. Select this checkbox to search in all the subfolders of the specified folder.

Concatenate files

Select this checkbox to combine data from all source files into a single data extract.

Delete source

Select this checkbox to delete the source files after Adverity has imported their data.

Move to

Specify the full path to the folder in into which the source files will be moved after Adverity has imported the data.

Move to hierarchy

Select this checkbox to move the source files to the folder specified in the Move to field after Adverity has imported their data, and to use a folder structure that mirrors the original folder structure. This option is only effective if you also select the Recursive checkbox and specify a folder in the Move to field.

Sortorder

Specify the order in which Adverity processes the source files. Select one of the following:

Select Filename to process source files in alphabetical order based on their filenames.
Select Modification Time to process source files in chronological order based on the file's last modification time.
Select Date Match to process source files in chronological order based on the date contained in their filenames. To specify how the date is contained in the filenames, see the fields Filename date match and Filename date pattern.

Reverse sortorder

Select this checkbox to reverse the order in which Adverity processes the source files that you specify in the Sortorder field.

Ignore file time

By default, Adverity uses the file timestamp to import data. Select this checkbox to use the date contained in the filenames that you specify with the fields Filename date match and Filename date pattern.

Fetching Azure Blob files based on dates in the filenames

To fetch data from Azure Blob Storage for a specific date range based on the filenames, configure the datastream in the following way:

Before you complete the procedure, make sure the names of the source files contain dates. For example, filename-2021-04-16.
Select the workspace you work with in Adverity and then, in the platform navigation menu, click Datastreams.
Open the Azure Blob Storage datastream by clicking on its name.
In the top navigation panel, click Settings.

In File pattern, enter a regular expression that matches the filenames, including the date pattern that you want to use for matching the fetch date.

Use the following placeholders to specify the date contained in the filenames:

Placeholder	Description
%Y	year
%m	month
%d	day
%H	hour
%M	minute
%S	second

For example, use the expression adverity-hourly-%Y-%m-%d-%H-%M to match files with the format adverity-hourly-2021-04-16-15-40.

In Filename Date Match, enter a regular expression that matches the date you want to use. For example, \d{4}-\d{2}-\d{2}-\d{2}-\d{2}.
In Filename Date Pattern, enter the date format used in the filename. For example, %Y-%m-%d-%H-%M.
Select the Process all checkbox in the File Processing section.
In Sortorder, select Date match.
Select the Ignore file time checkbox.
Fetch your Azure Blob Storage files specifying the date range. For more information, see Manual and scheduled fetches.

Uploading files into Adverity

To upload a file into Adverity using the Azure Blob Storage datastream, follow these steps:

Select the workspace you work with in Adverity and then, in the platform navigation menu, click Datastreams.
Open the Azure Blob Storage datastream by clicking on its name.
In the top right corner of the page, click Upload.
Click Choose File, and select the file to upload.
(Optional) Select the Keep data in raw state checkbox to achieve the following goals:
- Keep the data in its original form and do not apply any enrichments assigned to this datastream. For more information on enriching your data, see Enriching data in Adverity.
- Fetch the data without loading it into the destination specified for this datastream. For more information on loading data into a destination, see Introduction to loading data into Adverity Data Storage and external destinations.
Click Upload.

As a result, the file is uploaded into Adverity and Adverity creates a data extract that includes the uploaded data.

Fetching files from Azure Blob Storage manually

To browse files in the Azure Blob Storage server and fetch them manually, follow these steps:

Select the workspace you work with in Adverity and then, in the platform navigation menu, click Datastreams.
Open the Azure Blob Storage datastream by clicking on its name.
In the top right corner of the page, click More .
Click Browser.
Select the files to fetch. If the file is in a folder, click on the folder name to open the folder and view the files.
Click Fetch selected files.

The fetch collects data from Azure Blob Storage which takes some time. The Overview page of the newly created datastream is now displayed. To preview the collected data, follow these steps:

In the All tasks tab, find the task at the top of the list, and click Show extracts.
Click the top hyperlink.
The data extract is displayed in a table containing the data that you have fetched.