Skip to main content

Data Extraction methods in Azure Synapse Analytics


Data extraction is an essential step in the data analysis process, and Azure Synapse Analytics provides a variety of methods to extract data from different sources. In this blog post, we will explore the different data extraction methods available in Azure Synapse Analytics and provide example codes to demonstrate how to use them.

Copy Data Transformation: Copy Data transformation is the most basic and commonly used method for extracting data in Azure Synapse Analytics. It allows you to copy data from a source to a sink, such as an Azure Data Lake Storage or an Azure SQL Database. The "Copy Data" transformation also allows for filtering and sorting of the data, as well as mapping columns to different names.

Example code:

{
    "name": "CopyData1",
    "properties": {
        "type": "Copy",
        "source": {
            "type": "SqlSource",
            "sqlReaderQuery": "SELECT * FROM mytable"
        },
        "sink": {
            "type": "AzureDataLakeStorageSink",
            "folderPath": "myfolder/mydata"
        }
    }
}

In this example, the "sqlReaderQuery" parameter specifies the SQL query to be used to extract the data from the Azure SQL Database. The "folderPath" parameter specifies the location in the Azure Data Lake Storage where the data will be copied to.

Data Flow Source: The Data Flow Source is a method of extracting data directly from a data flow. This method is useful when you want to extract data from a data flow that has already been transformed and cleaned.

Example code:

{
    "name": "DataFlowSource1",
    "properties": {
        "type": "DataFlowSource",
        "dataFlow": {
            "referenceName": "MyDataFlow"
        }
    }
}

In this example, the "referenceName" parameter specifies the name of the data flows that the data that will be extracted from.

Stored Procedure: The Stored Procedure method allows you to extract data by executing a stored procedure in an Azure SQL Database or an Azure Synapse Analytics SQL pool. This method is useful when you want to extract data from a specific stored procedure or when you want to pass parameters to the stored procedure.

Example code:

{
    "name": "StoredProcedure1",
    "properties": {
        "type": "SqlSource",
        "storedProcedureName": "sp_getdata",
        "storedProcedureParameters": [
            {
                "name": "param1",
                "value": "value1"
            },
            {
                "name": "param2",
                "value": "value2"
            }
        ]
    }
}

In this example, the "storedProcedureName" parameter specifies the name of the stored procedure to be executed and the "storedProcedureParameters" parameter specifies the parameters to be passed to the stored procedure.

Lookup Transformation: Lookup Transformation allows you to extract data from a reference data source by looking up values in the reference data source. This method is useful when you want to extract data that is stored in a reference data source, such as a CSV file or an Azure SQL Database.

Example code:

{
    "name": "Lookup1",
    "properties": {
        "


Comments

Post a Comment

Popular posts from this blog

ACID? 🤔

In the world of data engineering and warehousing projects, the concept of ACID transactions is crucial to ensure data consistency and reliability. ACID transactions refer to a set of properties that guarantee database transactions are processed reliably and consistently. ACID stands for Atomicity , Consistency , Isolation , and Durability . Atomicity : This property ensures that a transaction is treated as a single, indivisible unit of work. Either the entire transaction completes successfully, or none of it does. If any part of the transaction fails, the entire transaction is rolled back, and the database is returned to its state before the transaction began. Consistency : This property ensures that the transaction leaves the database in a valid state. The database must enforce any constraints or rules set by the schema. For example, if a transaction tries to insert a record with a duplicate primary key, the database will reject the transaction and roll back any changes that have alre...
Post a Comment
Read more

The Medallion Architecture

Data warehousing is a crucial aspect of modern business intelligence. The Medallion Architecture is a popular approach for designing data warehouses that can effectively meet the needs of an organization. The Medallion Architecture consists of three layers: Bronze, Silver, and Gold. In this blog post, we'll explore each of these layers and their role in building an effective data warehouse. Bronze Layer: The Bronze layer is the first layer of the Medallion Architecture. This layer is responsible for storing raw data. The data is typically loaded into this layer without any transformation or modification. The goal of this layer is to store all the data that an organization collects in its original form, without losing any information. This data can come from various sources, including transactions, logs, and sensors. For example, consider an e-commerce website that collects data on customer transactions. The Bronze layer of the data warehouse for this website would contain all the r...
Post a Comment
Read more

Data Loading methods in Azure Synapse Analytics

  Azure Synapse Analytics is a powerful tool for working with big data, and one of the key features of this platform is its ability to quickly and easily load data from a variety of sources. In this blog post, we will explore the different data loading methods available in Azure Synapse Analytics, along with examples of how to use each one. Azure Data Factory : Azure Data Factory is a fully managed data integration service that allows you to create, schedule, and manage data pipelines. With Azure Data Factory, you can easily move data from a variety of sources, such as flat files, databases, and cloud storage, into Azure Synapse Analytics. Example: {     "name": "AzureDataFactoryPipeline",     "properties": {         "activities": [             {                 "name": "CopyFromBlobToSynapse",                 "type": "Copy",   ...
Post a Comment
Read more