# Home ## Frequently Asked Questions ### How can I register for Dataimporter? You can register using either your Salesforce credentials (oAuth), or with an email and password. Head over to , choose the server that you would like to work with and complete the registration. ### Where is Dataimporter and my data hosted? We have servers in the US, Germany, and Sydney. When you register you will choose the region and your data will never leave that region. Our servers are all hosted by AWS. ### Do I need to enter a Credit Card when registering? No you don’t. We have a Free Tier which is only limited by the number of records that you can process (20,000). ### Can I connect multiple Salesforce instances? Yes you can, simply head to the Instance page and click on Login to Production or Login to Sandbox. ### My Job Run has errors, what do they mean? There are lots of different errors you can receive from Salesforce. We have an article of 10 of the most common ones to help you out [Here](https://www.dataimporter.io/blog/10-common-errors-with-salesforce-data-loading-explained), otherwise feel free to email us and we will do our best to help. ### Can I use lookup relationships to link records? Yes you definitely can! When on the mapping screen, search for the lookup relationship, and choose the Salesforce field that you would like Dataimporter to lookup the records via.

### How can I undo records that I have inserted? If you have inserted records, head over to the Successful Records page, and up the top you will see a Rollback button. If you click on this, and then confirm, Dataimporter will automatically delete the records for you, without having to download the CSV file, and create a new job. ![](/files/Qe6gKrLMblvqFxgo0CYs) ### Do you offer discounts for Nonprofits? We definitely do! We offer discounts for registered nonprofit organizations, just send an email to and we will be in touch regarding this. # Register with oAuth {% hint style="info" %} Register using your Salesforce Login, so you don’t need to create a separate password. {% endhint %} On the register page (), you will have two options: * Register with Production * Register with Sandbox

You can register with either, and the Login that you choose will be used to log in with Dataimporter going forward. If you wish to change the username used to log in to dataimporter, then head to the Billing page, and click Edit next to your user. # Register with Email + Password {% hint style="info" %} Register using email and password, which is not tied to your Salesforce Login. {% endhint %} On the register page (), you will fill in the form with the necessary information ![](/files/ZyGqRgtlbr7RGv6ZYzNn) Once you will in this information and click on Register, then you will be able to access Dataimporter. {% hint style="info" %} If you register with Email + Password, then you will not be able to Log In to Dataimporter using oAuth (Salesforce Login). {% endhint %} # Formulas {% hint style="info" %} Use formulas to dynamically add columns to your source data. Use common Excel & Salesforce formulas such as LEFT, CONCATENATE, and IF {% endhint %} ## General Formula Rules To reference a source column in a formula then place the column name in square brackets `[Name]` To add a static value e.g. a record type id, place the value in double quotes `"0013t00001XJ2dXAAT"` ## Text Operators ### MAP Map source values to target values. The Formula must include 3 parameters:
1. The field being mapped 2. The dictionary of mapping values 3. The default value where the source value is not provided in the mapping All values must be enclosed in double-quotes " and not single-quotes ' `MAP([Color], {"One": "Blue", "Two": "Red"}, "No Color")` This will convert 'One' to 'Blue', 'Two' to 'Red', and every other value to 'No Color' ### CONCATENATE Combine two or more fields by referencing their columns names and adding a + in between them. `[Name] + "-" + [Type]` E.g. if the Name value is ‘Sam Hoult’, and the Type value is ‘Prospect’ then the evaluated formula for that record would be “Sam Hoult-Prospect” ### LEFT Take the left n characters of a field `LEFT([Name], 3)` E.g. if the Name value is Benjamin Button, then the evaluated formula for that record would be “Ben” ### RIGHT Take the left n characters of a field `RIGHT([Name], 3)` E.g. if the Name value is Benjamin Button, then the evaluated formula for that record would be “ton” These expressions can be combined together e.g. for a column \[Date] where the values are in yyyy-mm-dd format the following formula could be used `LEFT(RIGHT[Date], 5), 2)` This first takes the right 5 characters from the date string: ‘mm-dd’, and then takes the left 2 characters of that substring: ‘mm’ ### REPLACE Replace characters in a string using either direct replacement, or a regex expression. `[Email].str.replace(" ", "")` `[Phone].str.replace("\d+", "", regex=True)` ### SPLIT Split up a field by a specified character, and the specified number of the split. 0 gives the first value in the split, 1 gives the second and so on. The value “” would give the value “dataimporter.io” using the formula below. `SPLIT([Email], "@", 1)` The value "One;Two;Three" would give the value "One" using the formula below. `SPLIT([Picklist], ";", 0)` ### LOWER Convert the text of a column into lowercase characters. "Sam Hoult" would become "sam hoult" `LOWER([NAME])` ### UPPER Convert the text of a column into uppercase characters. "Sam Hoult" would become "SAM HOULT" `UPPER([NAME])` ### CAPITALIZE Convert the first character of a column into uppercase, and the remaining characters into lowercase. "salesforce" would become "Salesforce" `CAPITALIZE([NAME])` ### TITLE Convert the first character of each word into uppercase, and the remaining characters into lowercase. "john smith" would become "John Smith" "fiRsT naME" would become "First Name" `TITLE([NAME])` ## Comparison Operators ### EQUALS True if the operands are equal. String comparisons that use the equals operator are case-sensitive. `[State] == "NY"` ### NOT EQUALS True if the operands are not equal. String comparisons that use the not equals operator are case-sensitive. `[State] != "NY"` ### LESS THAN True if the left operand is less than the right operand. `[Revenue].astype('int') < 50000` ### GREATER THAN True if the left operand is greater than the right operand. `[Revenue].astype('int') > 50000` ## Logical Operators ### IF Determines if expressions are true or false. Returns a given value if true and another value if false. `IF([State] == "NY", "New York", "Other")` `IF([Revenue].astype('int') > 100000, "Big Customer", "Regular Customer")` You can also nest IF statements like so `IF([State] == "NY", IF([Type] == "Big Customer", "NY Big Customer", "NY Regular Customer"), "Other")` ### AND Combine multiple logic statements together using the ampersand symbol. Each condition must be surrounded by parenthesis, as shown in the example below. Only when every condition returns True will the entire statement return True. `IF(([State] == "NY") & ([City] == "New York City"), "Target Customer", "Other")` ### OR Combine multiple logic statements together using the ampersand symbol. Each condition must be surrounded by parenthesis, as shown in the example below. When one of the conditions returns True will the entire statement return True. `IF([State] == "NY") | ([State] == "TX"), "Target Customer", "Other")` You can combine multiple & and | operators to create more complex expressions `IF((([Support Plan] == "TRUE") & ([Name] == "Big Account")) | ([Big Account] == "True"), "Gold", "Silver")` ### ISNULL Returns True is a value is Null and False if it contains a value. Will return False if the value is an empty string e.g. “”. `IF(ISNULL([Name]), "Unknown", [Name])` ### NOTNULL Returns True is a value is Not Null and False if it is null. `NOTNULL([Name])` ### CONTAINS Returns True if a value contains the string provided, otherwise will return False. The string provided is case sensitive. `IF(CONTAINS([Name], "New"), "New Account", "Old Account")` If the value is “New York” this would return true, where as “new york” would return False. ## Date Operators Date operators can be used to generate static values, as well as to filter records e.g. where date is less than 90 days from today. When you want to use a field in your data as part of a date calculation then you need to first convert it to the right format using the to\_datetime formula ### to\_datetime Changes the field from string to date / datetime `to_datetime([DateField])` ### TODAY Evaluates to the current day. `today()` ### YESTERDAY Evaluates to the previous day `yesterday()` ### TOMORROW Evaluates to the next day `tomorrow()` ### timedelta Can be used to change a dates value by a number of minutes, days, weeks or months `timedelta(days=90)` `to_datetime([DateField]) - timedelta(days=90)` # Migration Templates Migration Templates are used to Migrate multiple objects from one Salesforce Org to another. They extend the functionality of the Salesforce to Salesforce connector to allow for hierarchies of objects to be migrated at once, keeping the relationships between the objects in tact. For the basics, please review the [Migrate Documentation](/jobs/migrate). # Setting up the Template ## 1. Create a new Template 1. Name. 2. Source Instance. This is the Salesforce Org that you will choose the Objects from which you will do the migration. 3. Target Instance. This is the Salesforce Org that you will migrate the data to. 4. Team (If available). 5. Lock Source Instance. This will mean that whenever the Migration is run, the source instance cannot be changed or chosen at run time. 6. Stop on Failure (Recommended). This will stop running the template as soon as an Object has all records fail the migration. 7. Batch Size. The batch size for each request made during the migration. 8. Locale. Used for Anonymization of data. 9. Save the Template

## 2. Choose the Objects and Hierarchy to be Migrated.

In the Dropdown Box choose the Parent Objects that you want to be Migrated. When you have chosen an Object, click the + next to the dropdown to add it to the Template. Once you have added a parent object, you will be able to click the > to load all of the Related Objects. You will be able to see the lookup field which relates the two objects. In the Example above, you can see that Account has been selected, as well as the Contacts, related via AccountId, and the Cases, related via ContactId. The way that this template is set up, means that **only the Contacts that are related to Accounts via the AccountId will be included as part of the Migration.** If you wish to Migrate all records of an Object, or use an SOQL filter to get a subset of Records, then you should add the Object via the dropdown at the top of the page, rather than via the Related list. ## 3. Map the Objects and Fields

After choosing the Objects and the structure of the Template, you will be taken to the Template View. Here you can see the Source and Target Objects, the Operation, as well as the Order in which the Objects will be run. In the example above, you can see that the first object to be run is a custom object called Security\_\_c. The Target Objects is currently set to None, as the Target Org which was selected in the Template doesn't have an Object called Security\_\_c. **Where there is a match in Object Names, Dataimporter will automatically complete the Object and Field mapping for that Object.** For each source object that doesn't have a target object, click Actions next to it, and select Mapping:

This will then let you choose the Target object to be mapped to:

Once you have chosen the Object, you will then be able to Map the fields. You can read about the Mapping options in the [Migrate Documentation](/jobs/migrate). One additional feature of the Mapping as part of Migration Templates is the [Magic ID](/migration-templates/magic-id). # Magic ID Using the Magic ID lookup relationships, Dataimporter can automatically perform a VLOOKUP on your behalf, to link related records from the source org, to the newly created records in the Target Org. Let's run through the same example from the [Previous document](/migration-templates/setting-up-the-template) using the Contact object. Under the Account lookup you will see that the mapping has been completed automatically for you, with the AccountId from the source org being mapped to the Account Lookup via MagicId in the Target Org.

What Dataimporter will do in the background, is take the source and target Ids of the parent records that were created, and perform a match, so that when the Lookup values are populated in the target org, they are the same records which existed in the source org. **MagicId can only be used to link objects which are included in the Migration Template, and the referenced object must be run before the current object.** If you try to include an object as a MagicId which is either not included in the Template, or is set to run after the current Job you will receive an error. # Running the Template To run the Template, click on Run:

Next you will choose the Source and Target Instance for the Migration:

*Note:* If you have selected 'Lock Source Instance' on the Template then only the Target Instance will be selectable at this stage. # Summary Dataimporter provides you a way to generate mock records for you to seed your sandboxes and demo orgs. Speed up your Sandbox seeding, testing, and deployments by creating seeding templates, to fill your Sandbox Orgs with realistic mock data. # Data Types Dataimporter provides the following Data Types to be used for Sandbox Seeding 1. Person 2. Address 3. Numeric 4. Datetime 5. Finance 6. Payment 7. Science 8. Transport 9. Food 10. Text 11. Development 12. Internet 13. Binary Files 14. Picklist Picklist values are automatically detected by Dataimporter when generating the Seeding template. # Configuration On the configuration screen of each Object, you can select the number of records to be created (defaults to 10), and the Locale:

Most data types allow you to configure the possible values that can be created. For each Object & Template, you can choose a Locale which will localize certain fields when creating the mock data. The following Data Types are generated using the Locale: 1. Person 2. Address 3. Food 4. Finance 5. Text ### Masks Masks are used to generate custom formats for mock values. Masks can be a combination of hard-coded values, random ### Person #### Telephone You can configure the format of the telephone fields to be created, or leave it blank to be generated in the locale format:

#### Identifier The Identifier data type should be used to generate External Ids, or other unique string values:

### Datetime Date and time fields can be limited to certain year values:

### Numeric Numeric values can be limited to certain ranges, as well as specifying the number of digits after the decimal:

### Picklist Picklist values are read, and applied automatically for you when generating the seeding template. These can also be restricted on the configure screen:

# Job Management 💡 Jobs are the processes you create to Insert, Update, Upsert, Delete, and Export data to and from Salesforce ## Viewing Jobs To view all of your jobs, click on the Jobs page:

## Saving Jobs Jobs are automatically saved, at each step of the process that you go through, so you don’t need to explicitly request a job is saved. **All of the options that you select e.g. API Type, Mapping, Deduplicating or Sampling are saved on the job, and will be followed each time the job is run.** ## Types of Jobs 💡 Using Dataimporter you can interact with your Salesforce data in multiple ways.

### Insert Choose Insert to create new records in Salesforce. This will not update existing data in Salesforce. ### Upsert Choose Upsert to update existing records when certain criteria are met, otherwise create new records in Salesforce. Use this option when you have existing records in Salesforce, as well as new data that you wish to create. On the Mapping screen you will choose which field should be used to match existing records in your source data, as well as in Salesforce. ### Update Choose Update to update existing data in Salesforce. This will not create new records in Salesforce. ### Delete Choose Delete to delete existing records in Salesforce. ### Export Choose Export, to export (and send) existing data in Salesforce, to either a CSV file, or to an external data source which you have connected. ## Advanced Details 💡 There are two API types available from within Dataimporter. ### REST API The REST API sends records to and from Salesforce in predefined Batch sizes. You can control, in the advanced details section, what the batch size for each job should be (maximum 200). This API is generally appropriate for most jobs where the size of data is either under 20,000 rows, or where a smaller batch size is required due to heavy processing within Salesforce. ### Bulk API 2.0 The Bulk API 2.0 is the newest bulk data loading API provided by Salesforce. Using this API, Salesforce will create their own chunk sizes, based on the optimal size for processing. There is no option for you to choose your own batch size with this API. This API is appropriate for large data volumes where the speed of the upload is important, and the processing of data on the Salesforce side is minimal. ### Pass Duplicate Rules Check this box to bypass duplicate rules set up in Salesforce. This will allow records to be created, and the duplicate rule error message to be ignored. ### Use Assignment Rules Uncheck this box to ignore assignment rules when creating or updating Accounts, Cases, or Leads. ### Other Other options available for you to choose in the Advanced Details section include: **Date Field Format** Here you can choose the date format for your source data. Options available to you are: * YYYY-MM-DD * DD/MM/YYYY * MM/DD/YYYY **Time Field Format** Here you can choose the time format for your source data. Options available to you are: * hh:mm:ss.mmm * hh:mm:ss.mmmZ+/-hh:mm * hh:mm:ss.mmmXXX **Separator** You can choose the separator (delimiter) in your CSV file. The default is comma. The options available to you are: * , * | * ; # Migrate {% hint style="info" %} You can migrate Data directly from one Salesforce Org to another, without needing to download CSV Files. {% endhint %} ## Create a Migrate Job Head over to the Jobs page and click on New Job. Fill in the Name, choose your Target Instance, Source Instance, and the Operation. The Target Instance is the Salesforce Org that you want to Import Data into, and the Source Org is where the Data should be coming from. Once you have filled in these fields you can click next.

## Choose the Objects you would like to Migrate Choose the source and the target Objects that you wish to Migrate. These do not have to be the same in each Org.

## Map the fields you would like to Migrate Here is where you tell Dataimporter which source data should be migrated. On the left you will see every standard and custom field listed, and beneath you will see all of the Lookup Relationships as well. On the right side, are all of the Target fields which you can select to make sure that they will be included in the Mapping. To ensure that all of the Relationships are moved across make sure you make the Lookup Relationships using a key that is available in both orgs.

To make sure you Migrate the Lookup Relationships with the records, select them as shown below:

Here, Dataimporter will select the Account.Name, and Owner.Name from the source records, and create lookup relationships in the new org, using the Account.Name and User.Name. ## Filter the records to Migrate On the clean screen, you can create an SOQL filter, to select which records you want to migrate. If you want to migrate all records for this object, you can simply leave the filter field blank.

## Preview and Run the Job Preview the a sample of the records to be migrated. The SOQL Filters, and Deduplication Rules have been applied to the preview so you can check they are working correctly. Any formulas you have Mapped will also be evaluated, and appear on the Preview screen.

# Multi-Object {% hint style="info" %} Multi-Object Imports allow you to Insert, Update, or Upsert Parent and Child records in one job e.g. Accounts & Contacts, Leads & CampaignMembers. {% endhint %} ## Select Child Object On the Upload Page you will see the option ‘Add Related Records’. If you click this, you will be presented with the available Child Objects that you are able to use for the Job.

## Map Parent & Child Fields You will then Map the Parent and Child fields for the Job, using the same logic as a single object import, look at the Mapping article to read more about this. {% hint style="info" %} You will not need to define a lookup relationship between the Parent and Child records at this step {% endhint %} ## Choose the Unique Parent Field On the Clean screen, you will then choose the Unique Parent Field. This field is used to make sure duplicate Parent records are not created, as well as the field which will be used to match the Child Objects to their Parent. Take the CSV file below, which includes Account & Contact Data.

Each row represents a Contact, and the Column ‘Account Name’ represents the Account that the contact belongs to. We wouldn’t want the Account, Midwest Communications, to be created 4 times so on the Unique Parent Field:

## Preview the Parent & Child Data On the Preview Screen, you will see the Source Columns, 3 example records from the data, as well as the Parent and Child Object fields that have been Mapped:

## Job Run Results On the Job Run Results Page, you will see all of the Original CSV Data, however you will see more rows than the Original CSV File e.g.

In the results you will see a row for each Parent and Child record that was created. You will see that there is a Column ‘Object Type’ which determines which Object the row corresponds to, as well as the sf\_\_Id column which shows the Id of the corresponding record. {% hint style="info" %} If the Parent record fails, then the Child Record will not be created / updated, and will be shown in the results as ‘Parent record failed’. {% endhint %} Using Rollback will delete both the Parent and Child Records. # Upload {% hint style="info" %} The Upload screen is used to either upload a CSV or Excel file manually, or to choose where the External Data should be pulled from. {% endhint %} ### Importing Data On this page you can upload a CSV or Excel file, depending on the source selected on the previous screen. You will also select the Target Salesforce Object that you want the data to be imported into.

If you have recently uploaded a file already for this job, then you will have the option to proceed with the recently uploaded file, or to upload a new file: ![](/files/Qbn8uYjsSHr1OamIaHuK) # Mapping 💡 Here you will choose which columns in your Source data should be mapped to which Salesforce fields. ## General Mapping Information ### Lookup Relationships 💡 Use Lookup Relationships to link records with other records in Salesforce e.g. link a Contact with an Account You can link, and lookup relationship records in Dataimporter, using any Text, Email, or Phone field in Salesforce. To do this, choose the source column you want to use for the lookup, and the Salesforce object and field you want Dataimporter to look for records with:

If you have the Salesforce Id in the source data then you can map it directly without using a lookup relationship:

### Formulas Here, you can map your formulas, to the corresponding Salesforce field:

Formulas are shown with the ♾️ symbol before them. ## Insert One the Mapping page for an Insert Job you will choose which source fields should map to which Salesforce fields.

## Update & Upsert On an Update or Upsert Job, you will have the same mapping options as the Insert Job, plus an additional mapping to select which Source and Salesforce fields should be used to determine which records to update:

{% hint style="info" %} For Update Jobs, you can choose any Text, Number, or Id Field to match records. For Upsert Jobs, you can choose any Field marked as External Id. {% endhint %} ## Delete For a Delete Job, you simply choose the source field, which contains the Salesforce Id values for the records which you want to Delete. ![](/files/9S6KzuXgl1SAnWt78jkP) # Query {% hint style="info" %} Here you will choose which columns in your Source data should be mapped to which Salesforce fields. {% endhint %} ## Export For an Export job you will define a Query used to Select and Export the Salesforce records:

Use the quick select features, such as Select All or Select Custom Fields to quickly add fields to the query, or you can also type the Field API Names directly into the SELECT box. User Filters to select only certain records and place the filter into the WHERE box. # Preview 💡 Preview the data, as well as the Salesforce Fields that you have mapped to. ## Import Jobs You will see all of the source columns, 3 example records, and the matching Salesforce fields that you have mapped to.

💡 It is important that you check and confirm that you have correctly mapped the data, and that any formatting has been done correctly. ## Export Jobs You will see the Salesforce fields that you selected in your query, as well as a Sample of up to 10 records.

# History 💡 The history page shows you all the previously run jobs, as well as giving you access to the success and error files. ## What does History show? The History page shows the following information: 1. The name of the Job, as well as if this was a Retry, or Rollback. 2. How long the Job took to complete. 3. The Date & Time at which the Job was started. 4. The total number of records processed in the job. 5. The number of successful records processed. 6. The number of failed records processed. 7. The Links to the Successful & Failed Records.

## How long is the History available for? The History for each Job Run is available for 14 days after the Job Run has finished. At this time, the Job Results are deleted permanently from the Server and will not be available for you to view. # Retry 💡 Retry lets you reprocess the failed records from a Job run, without needing to go through the steps, or create a new job again. ## When can I Retry? You can Retry the failed records of any job run. This is available for up to 14 days after a job run. ## How to Retry From the Failed records page of a Job run, you will see the Retry button at the top right:

Clicking this button, and confirming on the next screen, will then create a new job run, with Retry appended to the name:

# Rollback 💡 Rollback is a quick method to let you undo (delete) previously Inserted records. ## When can I Rollback? You can Rollback any Insert Job. This includes when sampling is used, and for Retry jobs. Rollback will be available for a Job run for up to 7 days after the job is complete. ## How to Rollback From the Successful records page of an Insert Job, you will see the Rollback button at the top right:

Clicking this button, and confirming on the next screen, will then create a new job run, with Rollback appended to the name:

# Run Remaining 💡 For Jobs where you have taken a Sample of the data, you can use Run Remaining to process the remaining records. ## How to Run Remaining You can Run Remaining by going to the Successful Records of a Sample Job run, and clicking on Run Remaining:

After confirming on the next page, a new job run will be created with Remaining appended to the name:

## When can I use Run Remaining? You can use Run Remaining, for any job where you have Sampled the data in a Job Run. The Run Remaining feature is available for 14 days after the sample has been run. # Wildcard Names For external sources, you can use wildcard names when selecting the source data. This is used where the name of the source file is dynamic e.g. Account\_Import\_TODAYS\_DATE.csv. Using wildcards you can let Dataimporter search through your data source for matching CSV files, and choose the latest file to be used for the job: The following pattern matches are defined:

Pattern	Meaning
*	Matches zero or more characters
?	Matches exactly one character
[seq]	Matches any character in a sequence
[!seq]	Matches any character not in a sequence
today()	Evaluates to today's date e.g. 2026-01-01
now()	Evaluates to current timestamp e.g. 2026-04-22 231650

### Example Using the pattern Account\_Import\*.csv would select the following file in the SFTP Server:

Although the File is named with an earlier date, **Dataimporter will always take the latest modified file that matches the Wildcard pattern**. If no file can be found using the pattern then you will receive a message 'No File Found'. ### Examples 1. **Using `?`**: * Pattern: `file?.csv` * Matches: * `file1.csv` * `fileA.csv` * `file_.csv` * Does **not** match: * `file.csv` (no character in place of `?`) * `file12.csv` (two characters in place of `?`) * `files.csv` (two extra letters in place of `?`) 2. **Using `*`**: * Pattern: `data*.csv` * Matches: * `data.csv` (zero characters after `data`) * `data1.csv` * `data_set.csv` * `dataXYZ.csv` * Does **not** match: * `mydata.csv` (does not start with `data`) * `data.json` (different file extension) # Dataimporter Formatting Using Dataimporter you can perform a number of Configuration, Formatting, and Automation settings. # Replace Null Values By default, when updating existing Salesforce records, where the data is populated in Salesforce e.g. email, and the source data has a blank value, Salesforce will simply ignore the update. By selecting this option, the Blank values will be accepted by Salesforce, and the field data will be deleted.

This is only available for Upsert and Update operations. # Deduplicate Select this option when you want to remove duplicates from your source data. You will be able to define the field(s) that you want Dataimporter to look at, when considering whether records are duplicates or not:

By selecting multiple fields, Dataimporter will check both columns, and **only when both columns match, will records be considered duplicates**. Dataimporter will always perform an exact match when looking at removing duplicates e.g. 'Acme Account' and 'acme account' will not be considered duplicates. # Filter Data This feature allows you to select a Formula, which will evaluate to True or False, and can then be used to Filter your Data.

# Sample Data This allows you to choose a number of random sample records to process for the job. Use this to test Jobs before process the entire data.

Enter the number of records you would like us to randomly select in the Sample Size. The remaining records will then be available to process on the [Run Remaining](/jobs/run-remaining) page # Automation Control {% hint style="info" %} This feature is available for Enterprise Customers {% endhint %} As part of your Jobs, you can configure Flows, Validation Rules, and Triggers to be automatically toggled before the Jobs are processed, and returned to their original state after the Job has finished.

Flows, Validation Rules, or Triggers which are currently **Active**, will be show in the on position, with a blue toggle: ![](/files/lPOEezw1HrGt7L0ZevLB) Flows, Validation Rules, or Triggers which are currently **Inactive**, will be show in the off position, with a grey toggle: ![](/files/tNRd5CeLQMSHYBiJRheq) Flows, Validation Rules, or Triggers which are currently **Active and have been set to deactivate in Dataimporter**, will be show in the off position, with a red toggle: ![](/files/myLphntRCQ1SWdwDFVUI) Flows, Validation Rules, or Triggers which are currently **Inactive and have been set to activate in Dataimporter**, will be show in the on position, with a green toggle: ![](/files/yPS4pc48pkw6oLJURdt7) Dataimporter uses the API Name of the Metadata when toggling in your Org, so the Jobs can easily be changed between Sandbox and Production Orgs. #### Triggers When using the Toggle feature for Triggers, the following process takes place:\ \ In Production Orgs: 1. The triggers are set to Active/Inactive depending on what you have chosen. 2. Using the Metadata API, the changes are sent to production. 3. All Local Tests are run in your Production Org. 4. If the Tests are successful, the Trigger status is changed. 5. After Job Processing in Dataimporter, the same process is run, with the status set back to original. In Sandbox Orgs: 1. The triggers are set to Active/Inactive depending on what you have chosen. 2. Using the Metadata API, the changes are sent to production. 3. No test are run. 4. Trigger status is changed. 5. After Job Processing in Dataimporter, the same process is run, with the status set back to original. # Schedule {% hint style="info" %} For Import jobs where there is an External data source, or for Export jobs, you can schedule the jobs to be run automatically. {% endhint %} ## How to Schedule There are two places from which you can schedule jobs ### 1. From the Job Submit page After you preview the data, you will be given the option to Schedule the job:

### From the Jobs page:

## Updating a Schedule To update an existing schedule, simply follow the same process as above and click on Save Schedule, and it will be updated automatically. ## Unscheduling a Job To Unschedule a Job, click on Actions next to the Job, and click on Unschedule: # Hour ![](/files/0A66YG4HWr6DwvwMvkgo) Scheduling by Hour gives you the following options: * The days which the job should run. * How often the job should run on each day 1. Every 15 Minutes 2. Every 1 Hour 3. Every 3 Hours 4. Every 12 hours * The start time for the schedule Choose what time the job should start running. Select 00:00 (midnight) for the job to run all day. * The end time for the schedule Choose what time the job should stop running. {% hint style="info" %} **Note that this time is inclusive e.g. if you select 17:00 as the end time, then any jobs due to be run from 17:00 to 18:00 will also be run.** {% endhint %} * The Timezone that the schedule should run. ### Day Select this option if the job should run once per day: ![](/files/5Fb6CgjMJDjhJnsKaWF9) * The days which the job should run. * The start time for the schedule * The Timezone that the schedule should run. ### Month Select this option if the job should be run on certain days of the month Selecting Month gives you the following options: * The days which the job should run. * The start time for the schedule * The Timezone that the schedule should run. ## Updating a Schedule To update an existing schedule, simply follow the same process as above and click on Save Schedule, and it will be updated automatically. ## Unscheduling a Job To Unschedule a Job, click on Actions next to the Job, and click on Unschedule: # Day Select this option if the job should run once per day: ![](/files/5Fb6CgjMJDjhJnsKaWF9) * The days which the job should run. * The start time for the schedule * The Timezone that the schedule should run. ### Month Select this option if the job should be run on certain days of the month Selecting Month gives you the following options: * The days which the job should run. * The start time for the schedule * The Timezone that the schedule should run. ## Updating a Schedule To update an existing schedule, simply follow the same process as above and click on Save Schedule, and it will be updated automatically. ## Unscheduling a Job To Unschedule a Job, click on Actions next to the Job, and click on Unschedule: # Month Select this option if the job should be run on certain days of the month Selecting Month gives you the following options: * The days which the job should run. * The start time for the schedule * The Timezone that the schedule should run. # Flow Dataimporter also gives you the option to create a Schedule Flow. This is useful when you have multiple Jobs that need to be run in order e.g. 1. Import Accounts from SFTP 2. Import Contacts from PostgreSQL 3. Export Products to SFTP Typically, you would define a time for each Job to run, however if Jobs are delayed or finish quicker than expected you will quickly run into errors. The Flow Scheduler lets you define a time for the first Job to run, using the Hour, Day, or Month options. The next Jobs can then be run after the previous jobs have been finished e.g. ![](/files/Z2ZZHOXltXJssKLVUUby) {% hint style="info" %} The Flow option will only appear, once you have scheduled another Job. {% endhint %} You will then be able to see the scheduled job on the Jobs page:

# View Integrations To create a new Integration, click on Integrations and then New Integration # Database Dataimporter offers you Integrations with many common Database Systems. * [PostgreSQL](/integrations/database/postgresql) * [MySQL](/integrations/database/mysql) * [SQL Server](/integrations/database/sql-server) * [Azure SQL Database](/integrations/database/azure-sql-database) * [Heroku Postgres](/integrations/database/heroku-postgres) # Azure SQL Database ### Configuration {% hint style="info" %} You may need to whitelist the Dataimporter [IP Addresses](/security/ip-addresses) {% endhint %} You will need to enter the following information to create a MySQL Integration: **Name**\ **Host**\ **Port**\ **Username**\ **Password**\ **Database** ![](/files/dIPix3uxZ45IFOGnR9cb) {% hint style="info" %} Please ensure that these are all entered correctly when creating a connection. {% endhint %} ### Import On the Upload screen, you will select which Table you want to Extract, and which Salesforce Object you want to Import into.