Importing historical cases
Historical or legacy case data can be imported into the system, ensuring you can view and report on all your data in one place. The imported data will be displayed as part of the customer record and also within the reporting tool, and can be logged as a separate historical case type or as the same case types as natively generated cases. Data can be imported for closed cases only, or for both open and closed cases. The latter approach may require additional analysis by one of our consultants, as the requirements can be more complex.
How it works
We can configure the historical or legacy case to include any data you require. You should review your source data and your reporting requirements to ensure that all relevant data is exported and linked to the correct customer record.
The import usually consists of two files: one customer file with a row for each customer, and columns named for the standard iCasework contact details fields; the second with the data to be imported including customer Id of the customer to which the case relates to. Case and customer data should be limited to a maximum of 5000 rows per spreadsheet to ensure optimum performance, and should be imported in batches.
Once historical cases are created, historical documents can be imported using the import utility described below.
Import file format
For your customer import file, produce a CSV file with columns populated as below. Please ensure you check which fields your system uses if you already record customer data, specifically regarding custom fields.
Name | Value |
---|---|
Id | The customer’s unique reference |
Title | The customer’s title (Mr, Mrs, Ms etc) |
FirstName | The customer’s first name |
Surname | The customer’s surname |
Organisation | The organisation this customer belongs to, if any |
Address | The street component of the customer’s address |
Town | The town component of the address |
County | The county, province or region component of the address |
Country | The country component of the address |
Postcode | The zip or postcode component of the address |
The customer’s email address | |
Phone | The customer’s landline phone number |
Mobile | The customer’s mobile phone number |
ContactMethod | How the customer would prefer to be contacted (e.g. Email, Phone, Letter) |
ContactTime | What days or times of day the customer would prefer to be contacted if contact is made by telephone |
ContactLanguage | The ISO 639 two letter code for the customer’s preferred contact language (e.g. fr, en, nl) |
ContactConsent | Whether the customer agrees to be contacted again in future |
Category | A category or type assigned to the customer |
Custom1 | Custom data to be held directly against the customer. |
Custom2 | Custom data to be held directly against the customer. |
Custom3 | Custom data to be held directly against the customer. |
Custom4 | Custom data to be held directly against the customer. |
Custom5 | Custom data to be held directly against the customer. |
Custom6 | Custom data to be held directly against the customer. |
Custom7 | Custom data to be held directly against the customer. |
Custom8 | Custom data to be held directly against the customer. |
Custom9 | Custom data to be held directly against the customer. |
Gender | The gender of the customer |
EthnicOrigin | The ethnicity of the customer |
Sexuality | The sexuality of the customer |
Faith | The faith of the customer |
DateOfBirth | The date of birth of the customer |
AgeGroup | The age group of the customer |
Disability1 | Any disability the customer may have |
Disability2 | Any disability the customer may have |
Disability3 | Any disability the customer may have |
Disability4 | Any disability the customer may have |
Disability5 | Any disability the customer may have |
Disability6 | Any disability the customer may have |
Disability7 | Any disability the customer may have |
Disability8 | Any disability the customer may have |
Disability9 | Any disability the customer may have |
The case import file should be developed based on the data you wish to import - each row should relate an individual case, each column, a data item within that case. Our consultants will then use your spreadsheet as a basis for creating the historical case type.
Ensure you include the following data where needed.
Name | Value |
---|---|
Customer.Id | The unique reference of the customer in the case |
ExternalId | Any ID for the case in an external system, or from the original source system |
[Additional case attributes] | Any number of columns reflecting the historical data to be imported |
The import process
The process we generally follow is:
- Client provides data fields to be captured
- Consultant creates the historical case type with appropriate attributes
- Make the new case type temporarily available for manual input and testing
- Client provides a sample number of customers in the spreadsheet provided (no more than 5)
- Client to provide a sample historical case data as a csv file (no more than 5)
- Consultant imports the sample customer and cases files
- Client to review the imported cases
- Consultant imports the final customer and case files which are populated by the client
- Documents linked to cases as outlined below
Importing legacy documents
iCasework systems include an import utility to be used by our consultants to allow documents to be loaded onto legacy cases. Please follow the instructions below to prepare your documents and environment.
Exporting documents from source system
In order to support the import process we need all documents exported from the source system and given a filename that will link the document to the newly created "legacy" case in iCasework, using the iCasework ExternalID field containing the original case reference. This filename requirement will need to be part of your export process or handled with a shell script or similar afterwards.
Ensure that the filename is in the following format:
[ExternalID]#[DateTime]#[Filename].[Extension]
e.g. for a document called CustomerLetter.pdf from a legacy case that had the reference 12345 in the source system, the filename would be "12345#2020-01-04T13~45~00#CustomerLetter.pdf"
The DateTime format would be YYYY-MM-DDThh~mm~ss, and if the time is not available it can be specified as 00~00~00 e.g. "12345#2020-01-04T00~00~00#CustomerLetter.pdf"
The # character is the default separator between case ID and filename, but any other consistent separator character can be used - please ensure this character is not part of the filenames themselves, and inform your consultant.
Providing iCasework access to legacy documents
To complete the migration iCasework needs to have secure access to your documents in a format that allows for efficient data transfer. Please upload your documents to an Amazon Web Services S3 bucket. You will need to apply a set of permissions to the bucket, and set up an IAM user with API key based access to your AWS account, and permissions as described below. Your AWS account details should then be added to the iCasework system in Administration >> General settings >> AWS API Credentials.
S3 Bucket policy
{ "Version": "2012-10-17", "Statement": [ { "Sid": "DelegateS3Access", "Effect": "Allow", "Principal": { "AWS": "arn:aws:iam::[ICASEWORK_ACCOUNT_ID]:root" }, "Action": [ "s3:ListBucket", "s3:GetObject" ], "Resource": [ "arn:aws:s3:::[YOUR_BUCKETNAME]/*", "arn:aws:s3:::[YOUR_BUCKETNAME]" ] } ] }
IAM Permissions
{ "Version": "2012-10-17", "Statement": [ { "Sid": "ListObjectsInBucket", "Effect": "Allow", "Action": [ "s3:ListBucket" ], "Resource": [ "arn:aws:s3:::[YOUR_BUCKETNAME]" ] }, { "Sid": "AllObjectActions", "Effect": "Allow", "Action": "s3:*Object", "Resource": [ "arn:aws:s3:::[YOUR_BUCKETNAME]/*" ] } ] }
Replace YOUR_BUCKETNAME with the unique name of your S3 Bucket. ICASEWORK_ACCOUNT_ID will be provided by your iCasework project team.
Loading legacy documents
Once your have exported your documents and prepared your S3 environment talk to an iCasework consultant to run the import utility on your behalf. This will happen at an agreed time - you may wish to test on a small set of documents first before running against a large dataset.
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