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Data Transformation methods in Azure Synapse Analytics


Data transformation is a crucial step in the data processing pipeline and Azure Synapse provides several methods to perform data transformation tasks. In this blog post, we will discuss some of the most commonly used data transformation methods in Azure Synapse with code examples.

Mapping Data Flow: Mapping Data Flow allows you to define data transformation tasks by creating a flow of data between source and destination datasets. You can use built-in transformation tasks such as filtering, aggregation, and joining data.

Example:

{

    "name": "ExampleDataFlow",

    "properties": {

        "activities": [

            {

                "name": "Source",

                "type": "Source",

                "policy": {

                    "timeout": "7.00:00:00"

                },

                "typeProperties": {

                    "source": {

                        "type": "BlobSource"

                    },

                    "format": {

                        "type": "TextFormat",

                        "columnDelimiter": ","

                    }

                }

            },

            {

                "name": "Sink",

                "type": "Sink",

                "policy": {

                    "timeout": "7.00:00:00"

                },

                "typeProperties": {

                    "sink": {

                        "type": "BlobSink"

                    },

                    "format": {

                        "type": "TextFormat",

                        "columnDelimiter": ","

                    }

                }

            }

        ],

        "annotations": []

    }

}

T-SQL: You can also use T-SQL statements to perform data transformation tasks. You can use the SELECT statement to filter, aggregate, and join data.

Example:

-- Select specific columns

SELECT column1, column2, column3 FROM table1

-- Filter data

SELECT * FROM table1 WHERE column1 = 'value'

-- Aggregate data

SELECT column1, SUM(column2) as total FROM table1 GROUP BY column1

-- Join tables

SELECT t1.column1, t2.column2 FROM table1 t1 JOIN table2 t2 ON t1.id = t2.id


Data Flow: Data Flow is a visual tool that allows you to create data transformation tasks by connecting various transformation tasks together. You can use built-in transformation tasks such as filtering, aggregation, and joining data.

Example:

{

    "name": "ExampleDataFlow",

    "properties": {

        "activities": [

            {

                "name": "Source",

                "type": "Copy",

                "inputs": [

                    {

                        "name": "input1"

                    }

                ],

                "outputs": [

                    {

                        "name": "output1"

                    }

                ],

                "typeProperties": {

                    "source": {

                        "type": "BlobSource"

                    },

                    "sink": {

                        "type": "BlobSink"

                    }

                }

            }

        ],

        "annotations": []

    }

}

These are just some examples of the data transformation methods available in Azure Synapse, and you can also use other tools like Azure Data Factory and Power Query to perform your data transformation tasks.

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