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How to Complete a Data Change Request Form

Blair Matheson
  • Updated

By using the Change Request Form, you are providing us with the necessary information to complete your request - which allows our data teams to better understand the discrepancy and solve it is a more efficient way.

We have created this form to streamline the data change request process, and it is important to submit the form properly and fill in each field correctly. submitting the form properly will prevent mistakes and limit the back-and-forth communication between you and our data team.

If you want to make a data-related change, you should submit your desired change to this Change Request form.

 

Please fill in your details at the beginning of the form, and choose the relevant request type (you can choose multiple request types):

  • Add New Tables
  • Add columns to Existing Tables
  • Add/Update Customer Attributes/Activity History
  • Add/Update Purchase History Attribute

data

Each type of request will open a new section where you will need to add the information of the request- there are full examples below.

 

Add New Tables

This section allows you to add new tables to the ETL process.

Fill in the necessary information, and focus on the required fields / columns, marked with a *.

Please note:

  1. You don’t have to fill all the table rows.
  2. If you need to add more rows to the table, tick the box at the bottom of the table, and another table will appear (see below).
  3. If you would like to create new customer attributes based on the new tables, make sure to also add and fill the ‘Add/Update Customer Attributes‘ section.

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Table Columns Explained

  • Data Source (Files Delivery, DB, API)*: Specify how the table’s data will be delivered to Optimove. Options include Files Delivery (e.g., SFTP), Database (DB), or API. Example: Choose "Files Delivery" for CSV uploads via SFTP.
  • Table Name*: Provide a unique name for the new table to be added to the ETL process. Example: "CustomerBalances" for a table tracking account balances.
  • Unique Identifier*: Indicate the column that uniquely identifies each record (e.g., CustomerID, TransactionID). This ensures no duplicate records are processed. Example: "CustomerID" for a customer data table.
  • Incremental / Full Incremental*: Choose how data is processed:
    • Incremental (Delta-Based Processing): Processes only changes (new, updated, or deleted records) since the last successful batch. This reduces data volume and improves efficiency by avoiding redundant processing.
    • Full Incremental: Includes all historical records alongside the latest changes. This ensures consistency and is often used when reconciliation with past data is required.
    Example: Select "Incremental" for daily updates to customer balances, or "Full Incremental" if historical data must be reprocessed.
  • Incremental Date Column: For Incremental processing, specify the column tracking the date of changes (e.g., LastUpdatedDate). This helps Optimove identify new or updated records. Example: "TransactionDate" for a payments table.
  • Add to Missing Files Procedure?: Indicate whether to monitor for missing files in the batch process. If checked, a message will be triggered if expected files are missing. Example: Check this for critical tables like daily transactions to ensure data completeness.
  • Add to Check Data Exists Procedure?: Enable monitoring of data volume. This evaluates the average daily data volume over the past 180 days. If a day’s data is less than 20% of the average, a message is sent. Example: If the daily average for "UpdateClientBalances" is 1,000 rows, but today’s batch has only 190 rows, a message will be triggered.
  • Is Check Data Exists Fail Process?*: Specify whether a low data volume (less than 20% of the 180-day average) should fail the entire batch process. Example: Check this to halt processing if "UpdateClientBalances" drops below 200 rows, ensuring data reliability.
  • Default Parameters for Check Data Exists Procedure: Confirm if default settings (20% threshold, 180-day average) are acceptable. If not, provide custom parameters in the Comments column. Example: Specify a 10% threshold for stricter monitoring.
  • Comments: Add any additional details, such as custom settings for Check Data Exists, special instructions, or clarifications. Example: “Use a 10% threshold for Check Data Exists due to variable transaction volumes.”

 

Add Columns to Existing Tables

This section allows you to add new columns to existing tables.

Fill in the necessary information and pay attention to the required fields / columns, marked with a *.

Please note:

  1. You don’t have to fill all the table rows.
  2. If you need to add more rows to the table, tick the box at the bottom of the table, and another table will appear (see below).
  3. If you would like to create new customer attributes based on the new tables, make sure to also add and fill the ’Add/Update Customer Attributes’ section if needed.

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Table Columns Explained

  • Data Source (Files Delivery/DB/API)*: Specify the source of the existing table where the new column will be added (e.g., Files Delivery for SFTP, DB for database, API). Example: "Files Delivery" for an SFTP-based table.
  • Table Name*: Name the existing table to which the column will be added. Example: "Customers" for adding a new column to customer data.
  • Column Name*: Provide the name of the new column. Example: "LoyaltyPoints" for a column tracking customer rewards.
  • Data Format/Type*: Define the column’s data type (e.g., Integer, String, Date). This ensures correct processing. Example: "Integer" for LoyaltyPoints.
  • Sample File Is Available (relevant for SFTP): Indicate if a sample file with the new column is available in SFTP. Example: Check this if you’ve uploaded a sample CSV for testing.
  • Name of the File (if added directly to the SFTP): Specify the file name if a sample is provided via SFTP. Example: "Customers_Sample.csv" for a test file.
  • Comments: Include additional details, such as column purpose or special instructions. Example: “LoyaltyPoints tracks rewards earned monthly.”

 

Add/Update Customer Attributes/Activity History Section

This section allows you to add or update customer attributes/Activity History;

Activity history allows you to target and analyze audiences based on customer behavior.

Campaign KPIs allow you to measure your campaign performance based on key performance indicators important to your business.

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 Fill in the necessary information and pay attention to the required fields/columns, marked with a *.

Please note:

  1. You have the option to choose if the attribute should also be added to Activity history/ Campaign KPI.
  2. You don’t have to fill all the table rows.
  3. If you need to add more rows to the table, tick the box at the bottom of the table, and another table will appear.
  4. If the attributes are based on a new table addition, you will have to provide more information in the ‘Add New Tables’ Section.
  5. If you would like to add or update a site filter- you will need to fill in this section (Add/Update Customer Attributes) and mention in the comments that this is a site filter.

Table Columns Explained

  • Existing/New Attribute: Indicate whether the attribute is new or an update to an existing one. Example: Select "New" for a first-time attribute like Total Payment Amount.
  • Attribute Name*: Provide a clear name for the attribute. Example: "Total Payment Amount" for tracking payment sums.
  • Based on Table/s*: Specify the table(s) used for the attribute, including any joins. Example: "Payments" or "Payments combined with Customers based on CustomerID."
  • Calculation/Column Name*: Define the calculation or column used. Example: "Sum(Payment Amount Where Status=True)" for aggregated payments, or "Payment Amount" for a direct column.
  • Time Frames*: Set the time period for the calculation (if applicable). Example: "2 weeks" or "3 months" for time-based aggregations.
  • Data Format/Type*: Specify the attribute’s data type (e.g., Integer, Decimal, String). Example: "Decimal" for Total Payment Amount.
  • Required in Activity History?: Check if the attribute should be tracked in Activity History for behavioral analysis. Example: Check for attributes like "Last Purchase Date."
  • Required as KPI (Campaign/Dashboard)?: Indicate if the attribute is needed as a Key Performance Indicator for campaigns or dashboards. Example: Check for "Total Payment Amount" to monitor campaign impact.
  • Flagged as Exclusion Attributes (opt_out): Mark if the attribute identifies opt-out customers (e.g., unsubscribed users). Example: Check for an "EmailOptOut" attribute.
  • Comments: Add details like calculation logic, special requirements, or site filter notes. Example: “This is a site filter for email campaigns.”

 

Add/Update Purchase History (Game History) Attribute

This section allows you to filter data to target customers based on their previous transactions and to add additional attributes to Purchase History. You will need to include the attribute name, table name, and any conditions required for the new attribute. Please pay attention to the required fields/columns, marked with a *.

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Please note

  1. You don’t have to fill all the table rows.
  2. If you need to add more rows to the table, tick the box at the bottom of the table, and another table will appear.
  3. If the attributes are based on a new table addition, you will have to provide more information in the ‘Add New Tables’ Section.  

Table Columns Explained

  • Existing/New Attribute*: Specify if the attribute is new or an update to an existing Purchase History attribute. Example: Select "New" for "Bet Type."
  • Attribute Name*: Name the attribute clearly. Example: "Bet Type" for categorizing betting transactions.
  • Based on Table/s*: List the table(s) used, including any joins. Example: "Bets" or "Bets combined with Bet_Details based on BetID."
  • Calculation/Column Name*: Provide the column or calculation for the attribute. Example: "BetType" for a direct column, or "Count(BetID Where BetType=Sports)" for a calculation.
  • Comments: Include additional context, such as filtering conditions or attribute purpose. Example: “Bet Type filters sports vs. casino bets.”

 

Please note: If you encounter difficulties while completing the Change Request form, please reach out to your CSM for assistance.

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