Discussion 1 (Chapter 9):  Discuss the correspondences between the ER model constructs and the relational model constructs. Show how ER model construct can be mapped to the relational model. Discuss any alternative mappings? Student 1:The entity set, relationship set, and attributes make up the E-R Model. Where the entity set is made up of all the entities, the relationship set is made up of all the relationships between the entities, and the attribute is made up of the properties of the entities.An example can be used to explain it. Take two real-world entities, Employ and Department, and you've got yourself an Entity set. We can now easily deduce a relationship between these two entities: an Employer and a Department. This is how we can get the E-R Model's relationship set.Tables can contain any number of rows, but they must have a set amount of columns. Each row in a table is referred to as a Tuple, and it holds all of the information on a certain item in the table. Because a set of Tuples is referred to as a record, the Relational model is referred to as a Record-based Model.A table's attributes are the columns that explain the table's properties (relation). Each attribute must have a domain that specifies what kind of value it can hold. Similarly to the E-R Model In a Relational Model, keys are also crucial since they uniquely identify a tuple in a relation or table.Data maps are an optional administration feature that you may use to identify linked records to delete or archive as part of your system's health and maintenance. Other ways for purging and archiving records are shown in the table below, in addition to data mapping. Multiple joins should be defined (Each data map record can only define one join). The purge/archive feature is not integrated. Destruction of linked records in a cascade (data mapping can only delete records as part of a purge process). Student 2:There exist several correspondences between the ER model constructs and the relational model constructs. For instance, entity type parallels to "entity" relation in the relational model. Similarly, the concepts of simple attribute, value set, multivalued attribute, key attribute, and composite attributes in the ER model are referred to as the attribute, domain, relation, and foreign key, primary or otherwise secondary key, and a set of simple component attributes respectively in the relational model constructs (Elmasri & Navathe, 2020). Furthermore, in the relational model, foreign key or relationship relation correspond to 1:1 or 1:N relation types in the ER. Comparatively, while the ER model describes the n-ary relationship style, the relation model relates it as relationship relation and n foreign keys. Therefore, a close similarity exists between the two types of constructs. According to Elmasri and Navathe (2020), the ER model can be mapped on the relational model through the following algorithmic steps. First, regular entity types are mapped. Secondly, the weak entity types are also mapped. Next, the binary 1:1, 1:N, binary M:N, multivalued attributes, and n-ary relation types are mapped, respectively. Finally, the mapping of generalization is carried out as multiple relations and single relations. The subsequent relations are conveniently split into super-classes, subclasses, one-type, and multiple type categories (p. 299). There are three alternative mappings of binary 1:1 relationship types. First, the foreign key approach is one in which one of the relations S is chosen, and the primary key of T is included as a foreign key in S. The second method is the merged relation approach. Here, an alternative mapping is possible by merging two entity types and the relationship into a single relation. The third alternative mapping is the cross-reference approach. In this approach, a third relation R is set up to cross-reference the primary keys representing the entity types (Elmasi & Navathe, 2020)ReferencesElmasri, R., & Navathe, S. (2020). Fundamentals of Database Systems. Pearson. 

The purpose of this assignment is to demonstrate steganographic encryption using Python.Locate and obtain the collaged photo from Topic 6.Encrypt the simple text message "Gotcha!" into the photo.Use the completed collage photo from Topic 6.Generate a secret text message. Picture of the message must be the same size as the collaged picture.Use Python to create and implement a steganography algorithm that will embed the message within the collage photo. [encode]In a separate program, prompt the user to decode the steganography algorithm and provide the decode functionality to match. [decode]Submit the following in compressed, zip file format:Your 2 Python programs. Naming convention is: firstInitial+lastName+StegoEncode.py and firstInitial+LastName+StegoDecode. Example: dHaralsonStegoEncode.py and dHaralsonStegoDecode.pyAt least one screen capture per program demonstrating that each of your programs were functional.Original message file, original picture, encoded picture and decoded picture.ZIP file naming convention is: firstInitial+lastName+stego.zip