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# crm_campaign_data_integration_flow.ps1
# PowerShell script to simulate logic for Power Automate's HTTP-based data integration workflows

# Configuration
$crmApiUrl = "https://api.crmcompany.com/v1/customers"
$campaignApiUrl = "https://api.marketingplatform.com/v2/campaigns"
$authToken = "Bearer YOUR_ACCESS_TOKEN_HERE"
$headers = @{
    "Authorization" = $authToken
    "Content-Type"  = "application/json"

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# Load required libraries
library(plspm)
library(lavaan)
library(semTools)
library(dplyr)

# Load and preview data
survey_data <- read.csv("survey_data_190.csv")
head(survey_data)

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/**
 * Shopify-NetSuite Integration Flow - Order Sync Script
 * Filename: shopify_netsuite_integration_flow.js
 */

// Sample mapping and transformation script for Celigo integrator.io
function transformOrder(record) {
  try {
    let transformed = {};

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public class NetSuiteIntegrationHandler {

    private static final String NETSUITE_ENDPOINT = 'https://api.netsuite.com/customers';
    private static final String AUTH_TOKEN = 'Bearer YOUR_NETSUITE_API_TOKEN';

    public class NetSuiteCustomer {
        public String externalId;
        public String name;
        public String email;
        public String phone;

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let
    // Connect to NetSuite via ODBC
    NetSuiteODBC = Odbc.DataSource("dsn=NetSuiteODBC", [HierarchicalNavigation=true]),
    TransactionsTable = NetSuiteODBC{[Name="Transactions"]}[Data],
    CleanedTransactions = Table.TransformColumnTypes(TransactionsTable, {
        {"TransactionID", Int64.Type}, {"VendorID", Int64.Type}, {"Amount", type number}, {"Date", type date}
    }),

    // Connect to dynamic CSV folder (Everstage files)
    SourceFolder = Folder.Files("https://company.sharepoint.com/sites/data/EverstageCSVs"),

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# etl_pipeline_adf_sql_powerbi.py

import pyodbc
from azure.identity import DefaultAzureCredential
from azure.mgmt.datafactory import DataFactoryManagementClient
from azure.mgmt.datafactory.models import *

# Azure configuration
subscription_id = 'YOUR_SUBSCRIPTION_ID'
rg_name = 'YOUR_RESOURCE_GROUP'

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from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.operators.python import PythonOperator
from airflow.providers.slack.operators.slack_webhook import SlackWebhookOperator
from airflow.utils.dates import days_ago
from airflow.models import Variable
import snowflake.connector
import requests

default_args = {

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import csv

# Define Sage 50 to QuickBooks field mapping
field_mapping = {
    'Date': 'TRNS_DATE',
    'Vendor': 'NAME',
    'Amount': 'AMOUNT',
    'Account': 'ACCOUNT',
    'Memo': 'MEMO',
    'Type': 'TRNSTYPE'

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import snowflake.connector
import pandas as pd
import requests

# Configuration
SNOWFLAKE_CONFIG = {
    'user': 'your_user',
    'password': 'your_password',
    'account': 'your_account',
    'warehouse': 'your_warehouse',

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import numpy as np
import pandas as pd
import time
import queue
import threading
from collections import deque

# Simulated tick data generator
def generate_tick_data(n=10000):
    timestamps = np.arange(n)