Punto y principio

As I've said many times, I've been a nerd all my life, so I decided to cheat my Bachelor's degree and do to things: 1) Take some IT courses in the USA 2) Write my Bacherlor's Thesis about Machine Learning, code more than use finance knowledge A short introduction on why : Two of the most important characteristics of Startups are uncertainty (Neumann, 2019) and the absence of quantitative information, the main topics of this work. Both components damage the financing possibilities of the company, especially when they fail to raise suficient funds from Business Angels or investment rounds (in the US only 0.96% obtain funds from Venture Capital or Business Angels (Entis, 2013)). As explained before, small and medium investors rarely have information about the financial statements, key technologies and audit reports of a startup, etc., the opposite of what happens with a company with a solid trajectory and, especially, is listed on stock markets. Therefore, efforts should b...

CK (Candidate Key). These are the Keys that may be defined as Primary keys, and must enforce these properties. Properties: Uniqueness . It must have a unique value, that is we cannot have at any given time the same value for the attribute at more than one tuple. Example: we cannot have the same SSN for two or more individuals, or a person can't have more than one SSN. Minimality . If it is a composite attribute (as an address), no component of the attribute can be deleted without destroying the uniqueness property. PK (Foreign Key). The most representative CK or CKs (we can have a composite PK) of the Entity Set are selected to use them to identify each Entity of an Entity Set. Example: The Entity Set "Student" has "Student Identification Number" as a PK. FK (Foreign Key). What if we have a table with Students which include, for each student, the "Identification Number" of each student's advisor (that is the PK of "Student advisor...

When we want to create a relational database, we must comply with four integrity constraints in order for our DB to work correctly . Entity integrity constraint. A PK (Primary Key) cannot allow null values Enforcement: check for null values when enter data. Key integrity constraint. No two tuples can have the same attribute value. Enforcement: check duplicity. Referential integrity constraint. We cannot have any unmatched FK (Foreign Key). That is, if B references A, A must exist. Enforcement: Restriction. The Update/delete of PK is restricted to not having a matching FK. Nullification. Update/delete of PK can only be done after setting any FK to null. Cascading. Update/delete of PK cascades to any FK. Semantic integrity constraint. We must use data that makes sense. We look for semantic correctness. Enforcement: use restrictions when enter data such as: length, legal values (i.e. car brands), types of data (i.e. currency, date, etc.), range, etc.

What are the main and necessary steps in the DB design and implementation process? Let's enumerate and explain them... User requirements . First we need them, we need a user capable of using a computer, understanding our language, etc. Conceptual design . This is used to describe information that the DB will contain. This is where we typically use the ER (Entity - Relationship) model, although some people refer to this design as drawing a simple schema about relationships without using the full version of ER model.  Input: Requirement specifications to build the DB Output: Conceptual schema Logical design . Used to describe the structure of the DB that can be processed by the DBMS (Database Management System), it can depend on the type of data the DBMS can used but not on the DBMS itself. Here we'll use the ER, including Attributes and Primary, Foreign an Alternative keys. Input: Conceptual schema Output: Logical schema  Physical design . At this point we create...

Users . Obviously, why would we want a DB if we don't have users? DBMS (Database Management System, such Microsoft Access). That includes DDL (Data Definition Language). Which creates and modifies the logical structure of the DB (objects). DML (Data Manipulation Language). It's used to manipulate and process data (retrieve, update, add) of the DB. I.e.: SQL. DBA (Database Administrator). It has two main functions: Plans, designs, implements and do maintenance and protection functions for the DB Defines data dictionary, which means that defines the meaning of data and describes interrelations between data items. DB itself. Finally we have the Database, which has its physical format and it's a collection of data.

What are the main functions of a DB (Database) ? Data definition . A DB should allow us to accept data definitions as those provided by the different types of schemas we had made to build our DB. This also includes a language processor component for each of the DDL (Data Definition Language: used to create and modifiy the logical structure (objects) of the DB) Data manipulation . Users will retrieve information, as well as update and add new information. This includes a processor for DML (Data Manipulation Language: which allows the user to do such actions (retrieve, update, add); SQL is a DML). Data security and integrity . Must have some mechanisms to control users requests and enforce the rules (security & integrity) defined by the DBA (Database Administrator). Data recovery and concurrency . What's concurrency? That's data at the same time , okay, never though of what happens when two users are editing at the same time the same tuple? That's a concurrency pro...

One of the first lectures of my Database design class was the explanation of the differences between the file-oriented approach and the database approach when dealing with the storage and manipulation of data. In a nutshell, we can say distinguish between the following advantages VS disadvantages. But first, what is file-oriented approach ? That's an "old" system where files are stored separately and each one of them is independent from the others . On the other side, a database approach allows us to associate data and keep and interdependent system. File-oriented approach disadvantages Data redundancy. There will be duplicates, as the files are created independently. This increases maintenance costs And also leads to data inconsistency, due to duplicates and/or similar data stored in different formats. Lack of data integration. This means we cannot associate data, as there are no association mechanisms. Program/data dependence to the physical format (th...