Most large companies have an "ID disparity" problem that prevents them from integrating data quickly and efficiently.
For Example
- The same customer may have multiple IDs in different databases
- The same customer may have duplicate IDs in the same database
- The same customer may have erroneous IDs caused by human error
Without having a single unique ID for each unique customer, it is not possible to create a unified view of your customers. The same applies for your vendors, your products, your employees etc.
The following example may resonate with many data managers.
Most companies have multiple databases that contain customer data. Consider a situation where John Doe is a customer, but a different customer ID is used for this customer in different databases
| Database
1:Customer Table1 |
| ID |
Name |
Address |
City |
State |
Zip |
| 123456789 |
John
Doe |
123
Main St.
|
Middletown
|
YY |
00001 |
| ... |
... |
... |
... |
... |
... |
| ... |
... |
... |
... |
... |
... |
| Database
2:Customer Table2 |
| ID |
Name |
Address |
City |
State |
Zip |
| ABCDEFGHI |
Mr.J.
Doe |
567
Old Main St.
|
Middletown
|
YY |
00001 |
| ... |
... |
... |
... |
... |
... |
| ... |
... |
... |
... |
... |
... |
| Database
3:Customer Table3 |
| ID |
Name |
Address |
City |
State |
Zip |
| A1B2C3D4E |
Dr.
John Doe |
1234
Main St.
|
Middletown
|
YY |
00001 |
| ... |
... |
... |
... |
... |
... |
| ... |
... |
... |
... |
... |
... |
In this situation, it would be very difficult to create an integrated view of your customers, since
- The Customer IDs are different
- The Customer Names have different spellings and variations
- The Customer Addresses are current, old and mistyped address.
The ideal way of solving this problem would be to create a Cross Reference Table for Customer IDs.
| Customer
ID Cross reference Table |
| Enterprise
ID |
DB1:T1 |
DB2:T2 |
DB3:T3 |
| A1B2C3D4E |
Dr.
John Doe |
1234
Main St. |
Middletown |
| ... |
... |
... |
... |
| ... |
... |
... |
... |
Having the Cross Reference Table would provide a mechanism for establishing that the 3 records are related to the same customer. The cross reference table can subsequently be used in data warehouses, ERP systems, CRM systems etc.
Our goal is to help our clients get a unified view of their enterprise IDs by automatically creating:
- A catalog of enterprise IDs, showing where all the different IDs reside
- A cross-reference ID table for many business objects that is of interest.
For example, we can create Cross Reference Tables for the following object
| All
Ind. |
Financial
Services |
Healthcare |
Insurance |
Manufacturing |
Telecom |
| Customers |
Investors |
Doctors |
Policies
|
Materials |
Networks |
| Products |
Regulators |
Patients |
Incidents |
Parts |
Circuits |
| Vendors |
Households |
Providers |
Products |
BOMs |
AccessPoints |
| Suppliers |
Subsidiaries |
Insurers
|
Coverage |
Distributors |
Providers |
| Employees |
Parents |
|
Risk |
Inventory |
Clients |
| Contractors |
|
|
|
Assets |
Services |
| Assets |
|
|
|
|
Routers |
| Facilities |
|
|
|
|
|
| Shareholders |
|
|
|
|
|
Creating - global cross reference tables can be a very time consuming task. By using a combination of software and services solutions, we automate significant portions of the integration effort related to enterprise ID access / movement / aggregation / integration. As a result, we can deliver integrated enterprise IDs to companies that require it, at a cost that is acceptable.
By using our solutions, our clients gain in the following ways
- Significantly reduced costs of ID integration projects
- Ability to handle the complexity associated with hundreds of information sources
- Keep control over a continuously changing ID landscape.
Click here to find out how Global IDs' technology can dramatically reduce time and effort required for global ID integration projects.
