Sapient Synapse is a data requirements tool that allows business and technology users to track and see how data is used within the organization. Data requirements can include but are not limited to information related to data dictionaries, glossaries, data mappings, data lineage and taxonomies. Synapse can capture these requirements and their relationships to sufficiently support regulatory demands.
There are five Key Concepts within Synapse that you need to understand before exploring the solution. They are Entity, Relationship, Attribute, Level and Level Columns. The definitions for each of these concepts are outlined in this user guide and are specific to Synapse. Understanding the key concepts and how they relate to each other will enable you to effectively configure your data in Synapse. The configuration process is critical because it defines how your data would be presented to your end users.
An Entity represents an instance of a concept. For example, Mark Zuckerberg is a person. Facebook is a company. In Synapse, they are both individually represented as an Entity.
An Entity Type represents the nature of the concept. For example, Mark Zuckerberg and Facebook can be categorized as People and Company, respectively, and are represented as Entity Types.
A Relationship represents an instance of the association between concepts. For example, Mark Zuckerberg is associated to Facebook, therefore he has a relationship with Facebook.
A Relationship Type represents the nature of the association between concepts. As shown in the example above, Mark Zuckerberg has a relationship with Facebook. The type of relationship in following scenario is Employment as he is employed by Facebook.
An Attribute provides additional information pertaining to a concept. As stated earlier, the Entity Type used to describe Mark Zuckerberg is People. Similarly, the Entity Type used to describe Facebook is Company. People and Company can have characteristics that define or describe them. People can have a First Name, Last Name, Birth Date and Phone Number, among other attributes. A Company can have a Legal Name, Address and Country of Incorporation, among other attributes.
A Template groups attributes together in a set. An Entity Type would call on a template to access the Attributes. In the example above, First Name, Last Name, Birth Date and Phone Number are all part of a Template called “Profile.”
A Level helps to classify a context of related concepts. In any given company, a single person can have many relationships to different concepts whether they are People, Company or Physical Sources. In the diagram below, Mark Zuckerberg is the center. His many relationships span across related concepts which are highlighted using the same color scheme.
Mark Zuckerberg, Mary Jane and Peter Zu are People; therefore they are related concepts and can be classified together. In this example, the Level that they are classified under is “Organization Hierarchy.” Salesforce and Excel are another example of related concepts because they are tools used by the business. As such, they are classified under the Level: “Physical Sources and Technology.”
A Column provides more granularities about related concepts. For the majority of the classification, Level and Level Column illustrate a one-to-one relationship. This means that in the Level known as Organizational Hierarchy, the Level Column can also be known as Organizational Hierarchy. This is because most Levels do not need additional granularities. Level Column is best applied when a Level is used to classify Physical Sources and Technology. In data requirements, Physical Sources and Technology are the most complex concepts to grasp because of their intricacies and various layers. Physical Sources and Technology can include system name, API name, database name, table name, field name, etc. Sapient Synapse recognizes the critical need to drill down, and thus enables the functionality for you to do so through Level Column.
In the diagram below, you can further classify the Physical Sources and Technology Level as three separate Level Columns: Applications, Components and Physical Fields. The Level Column known as Applications is used to capture the name of the physical sources, which in this case is either Salesforce or the name of the Excel Workbook. The Level Column known as Components is used to capture the module name of the Applications, which in this case is either LeadGen of Salesforce or the name of a sheet in the Excel Workbook. Lastly, the Level Column known as Physical Fields is used to capture the names of the fields within the Module or the Excel sheet.