Extract data from source, transform, and load in destination

This is the most commonly used flow type. Almost all available connectors can be used as a source, as well as a destination.

When to use this flow type

Eltworks Integrator extracts data from the source connection, transforms it by applying one or multiple transformations, and then automatically loads it in the destination.

The following variations of this flow are available:

This transformation modifies the source data before loading it in the destination. Use copy, move, rename, delete, zip, and unzip files if all you need is to copy, move, rename or delete the files or perform the bulk operations with the data without modifying it.

The source is a relational database

When the source is a relational database, the Integrator extracts data from the database table, view, or synonym or executes a user-defined SQL query.

The user has two options:

Use the From field to select or enter a database object name, such as table, view or synonym. In this case, Integrator will automatically execute the SQL query select * from object. Note that the fully qualified wildcard names are supported. Example: public.*. In this case, the system will extract the data from all database objects which match then wildcard name public.* and load into the destination.
Enter the actual SELECT SQL statement in the Source Query field.

Creating flow when the source is a relational database

To create a flow, go to Flows window, click the + button and type in database to. Select one of the available flows types and add one or multiple source-to-destination transformations.

Available transformations when the source is a relational database

Available parameters when the source is a relational database

The destination is a relational database

When loading data into a database, the Integrator either automatically generates and executes the SQL DML statement (INSERT, UPDATE, DELETE or MERGE) or executes user-created SQL statements.

When the destination is a relational database, the user has two options:

Use the To field to select or enter the database object name (table, view, synonym). If the source (FROM) is configured with a wildcard, you can use * as a part of the destination name (TO). The system will substitute the * with the source name at run time.
Or enter the actual INSERT, UPDATE, or DELETE SQL statement in the Destination query field.

The destination query can be more than just one SQL statement. Use ; to separate SQL statements.

In the example below, 2 queries will be executed. Fields within the { and } brackets will be replaced with the actual field values given by the source.

Source query:

SELECT locust_staging.id,
       locust_update_id.hotlineeventid,
       recorded_time AS calldatetime,
       CASE
         WHEN date_completed IS NULL
         THEN 2
         ELSE 1
       END AS eventstatusid,
FROM   locust_staging

Destination query:

update hotlineevent
set calldatetime = {calldatetime}, 
where hotlineeventid = {hotlineeventid};             

update locust_staging
set HotlineEventId =  {hotlineeventid}
where id = {id};

Creating flow when the destination is a relational database

To create a flow, go to Flows window, click the + button and type in to database. Select one of the available flows types and add one or multiple source-to-destination transformations.

Available transformations when the destination is a relational database

SQL
Source-to-destination
Per-field mapping
Filter (only if the source is not database)
Validation
Remove duplicates
Scripting transformations
Extract dimensions (only if the source is not database)
Transpose
Wrap columns
Denormalize (pivot)
Normalize as key-value pairs
Denormalize key-value pairs

Available parameters when the destination is a relational database

The source is a file, API endpoint, NoSQL database or inbound email connection

The source can be a flat, structured or semi-structured file, a response from the API endpoint, a document in the NoSQL database or an email body or attachment.

Etlworks Integrator parses the source document and transforms it into the internal data structure, then converts it to the appropriate format and sends it to the destination.

Here is an example of the flow which extracts data from the web service, transforms it and loads into the database.

When creating the transformation, define the source by selecting a source (FROM) connection and a source (FROM) format. Then select or enter a source (FROM) object name:

If the source connection is file storage (server or cloud), the source object name is an actual file name or a wildcard file name.
If the source connection is a web service, the source object name is an any appropriate name. For example, patient.json.
If the source connection is an outbound email connection, the source object name is either the name of the attached file or any appropriate name.
If the source connection is in a key-value storage, such as Redis, the name is a "key" (in a key-value pair).
If the source connection is in a NoSQL database, such as MongoDB, the name is a document id.

Using SQL to transform data

Similar to when the source is a relational database, the user has an option to enter an SQL query, which will be executed after the data has been read from the source. For example, if the source is a CSV file, the user can write a query that aggregates the data into a file and creates a summary view. This view will be used to drive the destination data.

Working with wildcard file names

If your source data object is a file, it is possible to configure a source (FROM) so that it will read the files by the wildcard name, for example, order_*.csv.

Read how to work with wildcard file names and how to process all files by the wildcard.

Creating flow when the source is a file

To create a flow go to Flows window, click the + button.

If the source is a file, inbound email connection, Redis or MongoDB type in file to.
If the source is a web service type in web service to.

Select one of the available flow types and add one or multiple source-to-destination transformations.

Available transformations when the source is a file

Available parameters when the source is a file

The destination is a file, API endpoint, NoSQL database or outbound email connection

The destination can be a flat, structured or semi-structured file, a payload for the API endpoint, a document in the NoSQL database or an email body or attachment.

Etlworks Integrator creates the destination document from the source using the appropriate data exchange format and by applying transformations and mapping.

When creating the transformation define the destination by selecting a destination (TO) connection and a destination (TO) format. Then select or enter a destination (TO) object name:

If the destination connection is in file storage (server or cloud), the destination object name is an actual file name. Read how Etlworks Integrator calculates the destination file name.
If the destination connection is a web service, the destination object name is any appropriate name. For example, patient.json.
If the destination connection is an outbound email connection, the destination object name is either the name of the attached file or any appropriate name.
If the destination connection is a key-value storage, such as Redis, the name is any appropriate name.
If the destination connection is a NoSQL database, such as MongoDB, the name is document id.

When the destination connection is in file storage - the new file will be created each time the transformation is executed. If the file already exists, it will be overwritten.

Creating flow when the destination is a file

To create a flow, go to Flows window, click the + button.

if the destination is a file, outbound email connection, Redis or MongoDB, type in to file.
if the destination is web service, type in to web service.

Select one of the available flow types and add one or multiple source-to-destination transformations.

Available transformations when the destination is a file

Available parameters when the destination is a file

The source is a well-known API

A well-known API is a business application or API for which Etlworks has a native connector, for example, Marketo, Salesforce, etc.

Here is an example of the flow which extracts data from the well-known API, transforms it and loads into the database.

Creating flow when the source is a well-known API

To create a flow, go to Flows window, click the + button, select Well-known API to and select the flow which extracts data from the well-known API.

Add one or multiple source-to-destination transformations.

Available transformations when the source is a well-known API

Available parameters when the source is a well-known API

The destination is a well-known API

A well-known API is a business application or API for which Etlworks has a native connector, for example, Marketo, Salesforce, etc.

Creating flow when the destination is a well-known API

To create a flow go to Flows window, click the + button, select to Well-known API and select the flow which loads data into the well-known API.