Automate SSIS to Microsoft Fabric Migration in Minutes

// SSIS Derived Column Expression
(ISNULL(Discount) || Discount == 0) ? TotalAmount : (TotalAmount * (1.0 - Discount))

# Microsoft Fabric PySpark Transformation
from pyspark.sql.functions import col, when, coalesce

df_sales = df_source.withColumn(
    "NetSales",
    when(col("Discount").isNull() | (col("Discount") == 0), col("TotalAmount"))
    .otherwise(col("TotalAmount") * (1.0 - col("Discount")))
)
df_sales.write.format("delta").mode("append").saveAsTable("fact_sales")

/* SSIS Data Flow: Lookup Task */
SELECT CustomerID, CustomerTier, RegionID 
FROM dbo.DimCustomer 
WHERE IsCurrent = 1

# Microsoft Fabric Lakehouse Join
df_customer = spark.read.table("dim_customer").filter(col("is_current") == 1)

df_enriched = df_sales.join(
    df_customer,
    df_sales["customer_id"] == df_customer["customer_id"],
    how="left"
).select(df_sales["*"], df_customer["customer_tier"], df_customer["region_id"])

// SSIS C# Script Task: Extract JSON Payload
public void Main() {
    string rawJson = Dts.Variables["User::RawPayload"].Value.ToString();
    var obj = JObject.Parse(rawJson);
    Dts.Variables["User::BatchID"].Value = obj["batchId"].ToString();
    Dts.TaskResult = (int)ScriptResults.Success;
}

# Microsoft Fabric PySpark Notebook
import json

def process_batch_payload(raw_json: str) -> str:
    """Parses payload and extracts Batch ID for pipeline tracking."""
    payload_data = json.loads(raw_json)
    return str(payload_data.get("batchId", "UNKNOWN"))

batch_id = process_batch_payload(raw_payload)