Logical Data Modeling

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Michael L Gibson - One of the best experts on this subject based on the ideXlab platform.

Thomas E Marshall - One of the best experts on this subject based on the ideXlab platform.

George Tillmann - One of the best experts on this subject based on the ideXlab platform.

  • Logical Data Modeling Definitions
    Usage-Driven Database Design, 2017
    Co-Authors: George Tillmann
    Abstract:

    Software tools for Data Modeling, Database design, and documentation, as well as corporate Data dictionaries and the Database management system, will all have their own documentation standards. This appendix gives examples of the minimum information about Data that needs to be available for Database designers, DBAs, Database maintenance staff, and application designers and programmers.

  • a practical guide to Logical Data Modeling
    1993
    Co-Authors: George Tillmann
    Abstract:

    Provides both the seasoned and novice designer with an understanding of Logical Data Modeling - the stepping stone to structuring viable software systems. The basics of Data Modeling are presented in this guide, focusing on entity-relationships - the most popular Modeling approach in use today. Explanations of how to incorporate popular CASE tools into object-oriented, semantic and relational methods are also included. The author uses a best-practices approach, providing guidelines that make it possible to customize Modeling to suit the specific needs of each practioner. He also provides an thorough explanation of the technique behind each methodology and tool.

Antolović Goran - One of the best experts on this subject based on the ideXlab platform.

  • Conceptual Data Modeling tools
    University of Pula. Faculty of economics and tourism "Dr. Mijo Mirković"., 2016
    Co-Authors: Antolović Goran
    Abstract:

    Napretkom i razvojem informacijske tehnologije javlja se potreba za sve složenijim i naprednijim informacijskim sustavima. Informacijski sustav je model poslovnog sustava. To je skup elemenata koji prikazuju dijelove stvarnog svijeta. Pod-tipovi informacijskog sustava su: Model procesa, Model poDataka i Model resursa odnosno izvršitelja. Izrada informacijskog sustava započinje modeliranjem baze poDataka. Podaci su simbolički prikaz elemenata stvarnog svijeta. Oni predstavljaju jedno obilježje nekog subjekta ili događaja. Ako nekom podatku dodamo kontekst i predstavimo na određeni način, tada on postaje informacija. Informacija je skup poDataka koji imaju neko značenje. Modeliranje informacijskog sustava započinje utvrđivanjem i analizom zahtjeva korisnika za informacijama, a završava izgradnjom stabilne i prilagodljive baze poDataka. Model poDataka pokazuje koji su podaci kojima raspolaže organizacija. Podaci informacijskog sustava spremaju se u bazu poDataka. Baza poDataka je model poDataka poslovnog sustava, koji je segment stvarnog svijeta. To je skup poDataka koji su obrađeni u jednoj organizaciji. Da bi se baza poDataka mogla implementirati, njen razvoj prije mora proći kroz različite faze. Oblikovanje poDataka je vrlo bitno i ključno u razvoju baze poDataka. Cilj modeliranja poDataka je da se odredi pogodna struktura baze za određene podatke i da ti podaci budu međusobno nezavisni. Konceptualno modeliranje poDataka bitan je i osnovni dio modeliranja poDataka. Konceptualnim modeliranjem dobivamo konceptualni model poDataka. Konceptualni model opisuje podatke koji su dio strukture cijelog informacijskog sustava, a izgrađuju ga projektanti koji surađuju sa korisnicima kako bi bolje razumjeli koji su podaci i koje informacije važne i potrebne. Za modeliranje konceptualnog modela koriste se koncepti: entiteti, veze i atributi, a za prikaz modela upotrebljavaju se dijagrami. E-R model proučava, opisuje i promatra stvarni svijet preko entiteta, odnosa između entiteta, i atributa entiteta ili njihovog odnosa. Za promatranje stvarnog svijeta koristi se apstrakcija pomoću koje se lakše uočava i odvaja ono što je bitno od onoga što je nebitno ili manje bitno. Za konceptualno modeliranje poDataka u E-R modelu koriste se tri vrste ili postupka apstrakcije. To su klasifikacija, generalizacija i agregacija. E-R je skraćenica od eng. Entity-Relationship pa se ovaj model zove još i model entiteti-veze gdje veze pokazuju odnose između entiteta, a atributi opisuju entitete. Entitet je nešto što postoji i što se u stvarnom svijetu može identificirati. Može biti objekt koji ima mnogo instanci u bazi poDataka, može biti sastavljen od više atributa i može biti objekt kojeg sami modeliramo. Veza opisuje odnos između entiteta. Ovisno o broju entiteta može biti unarna, binarna, ternarna ili k-narna veza i takva podjela zove se podjela po stupnju veze. Veze između entiteta dijele se još po kardinalnosti i opcionalnosti. Atribut je obilježje entiteta. Služi kao opis entiteta i olakšava određivanje stanja tog entiteta. Postoje indikacijski i opisni atributi. E-R model omogućava izradu dobrog grafičkog prikaza. Samim time znatno je lakše razumjeti model poDataka koji je prikazan. Dijagram E-R modela najčešće se zapisuje Chenovim, Martinovim i Barkerovim prikazom. Chenov prikaz dobio je ime po Peteru Chenu koji je E-R dijagram predstavio 1967. godine. Prikazuje entitete, veze i atribute. Entiteti se u dijagramu prikazuju pravokutnikom. Veze se prikazuju simbolom romba koji je linijom spojen za entitete. Simbol za atribut je elipsa ili krug. Oni su spojeni linijom za entitet kojega opisuju. U Martinovu se prikazu E-R modela entiteti prikazuju simbolom pravokutnika. Atributi se prikazuju pomoću elipse ili kruga. Veze se u Martinovom prikazu crtaju ravnom linijom između dva entiteta. Veza se ne imenuje nego se navode uloge entiteta koje veza spaja. U ovom prikazu koriste se samo unarne i binarne veze. Barkerov prikaz nazivamo još i Oracle Case method. Entiteti se u prikazu označavaju pravokutnikom. Atribute se upisuje u pravokutnik entiteta tako da budu navedeni ispod naziva entiteta. Veza se u Barkerovu prikazu prikazuje kao linija između dva entiteta. Logičko modeliranje poDataka je druga faza u modeliranju baze poDataka. U ovoj se fazi konceptualni model pretvara u relacijski model poDataka. Da bi se baza poDataka mogla implementirati potrebno je napraviti relacijsku shemu, jer se većina današnjih sustava za upravljanje bazom poDataka koristi relacijskim modelom. U relacijskom se modelu entiteti i veze između entiteta pretvaraju u relacije tj. tablice. Relacijski je model, dakle, model u kojem se baza poDataka sastoji od skupa relacija. Relacija je tablica u modelu sa stupcima i redovima koja predstavlja entitet ili vezu. Vrijednost atributa prikazuje se stupcem u relaciji. U relacijskom se modelu, za prikazivanje tipa entiteta, koristi relacijska shema. Za prikaz skupa entiteta koristi se relacija, odnosno tablica. Entitet se prikazuje jednom n-torkom, odnosno jednim retkom u tablici. Atributi koji opisuju entitet postaju atributi relacije. Primarni ključ entiteta postaje primarni ključ relacije. Veze između entiteta nastaju povezivanjem vanjskog ključa jedne relacije sa primarnim ključem druge relacije ili se za prikazivanje veza stvara nova relacija. Razvojem informacijskog sustava povećava se potreba i važnost izrade dobrog konceptualnog modela poDataka. Sukladno tome, dolazi do stvaranja i razvoja alata za konceptualno modeliranje poDataka sa grafičkim sučeljem koji olakšavaju izradu modela. Danas već postoji veliki broj alata za konceptualno modeliranje poDataka koji se mogu spajati na razne sustave za upravljanje bazom poDataka. Toad je alat za konceptualno modeliranje poDataka. Može se spajati na Oracle, SQL server, MySQL, SQLite, Postgre SQL.Radi samo na Microsoft Windows platformi. Navicat je alat za konceptualno modeliranje poDataka sa grafičkim sučeljem koji se spaja na Oracle, SQL Server, MySQL, SQLite, PostgreSQL, MariaDB sustave za upravljanje bazom poDataka Radi na Microsoft Windows, MAC OS i Linux platformi. DbForge Studio je alat za konceptualno modeliranje poDataka sa grafičkim sučeljem. Spaja se na SQL Server, Postgre SQL, MySQL, Oracle sustave za upravljanje bazom poDataka Radi samo na Microsoft Windows platformi. Alati imaju poprilično sličan način rada. Razlike su uglavnom vizualne. Pregledni su i jednostavni za rad. Osim što omogućavaju kreiranje konceptualnog modela i oblikovanje poDataka u modelu, alati omogućavaju, također, pretvorbu konceptualnog modela u logički model, te omogućavaju i izradu baze poDataka.With the progress and development of information technologies there is a necessity for more complex and advanced information system. The Information system is a model of the business system. That is a set of elements that shows parts of real world. The sub-types of the information systems are: process model, Data model and resources or executor model. The construction of the IT system begins with Database Modeling. Data is a symbolic representation of real world elements. They represent a characteristic of some subject or event. If we add a contest to a Data and represent it in a certain way, then it becomes an information. An information is a set of Data that has some meaning. The Modeling of the IT system begins with the identification and analysis of user requirements for information, and ends with the construction of a stable and flexible Database. The Data model shows what Data are available to the organization. The Data of the IT system are stored in the Database. The Database is a Data model of the business system, which is a segment of the real world. It is a set of Data that are processed in an organization. Before the Database could be implemented, its development must go through different phases. Data Modeling is very important and crucial for Database development. The goal of Data Modeling is to determine the appropriate Database structure for specific Data and that the Data are independent of each other. Conceptual Data Modeling is an important and essential part of Data Modeling. With the conceptual Data Modeling we raise a conceptual Data model. The conceptual model describes Data that are part of the structure of the whole IT system, and it's built by designers who collaborate with customers to better understand what Data and what information are important and necessary. Concepts: entities, relationships and attributes are used for Modeling a conceptual model, and diagrams are used for model view. The E-R model studies, describes and observes the real world through entities, relationships between entities and entity attributes and their relationships. For the observation of the real world there is an abstraction used to help to notice and separate what is important from what is irrelevant or less important. For the conceptual Data Modeling in the E-R model there are three types or process of abstraction. These types are called classification, generalization and aggregation. E-R stands for Entity-Relationship, so in this model, links shows relationships between entities and attributes describes entities. An entity is something that exists and can be identify in the real world. It can be an object that has many instances in the Database, can be composed of multiple attributes and it can be an object that we can model ourselves. The bound describes the relationship between the entities. such a division is called the division by the degree of connection. Depending on the number of entities, the bound can be unary, binary, ternary or N-ary bound and such a split is called the connection degree split. The bounds between entities are divided also by cardinality and optionality. An attribute is a characteristic of the entity. It serves as a description of entities and facilitates the determination of the status of that entity. There are indication and descriptive attributes. The E-R model enables the creation of a good graphic display. Therefore, it's much easier to understand what is the Data model showing. To write an E-R model diagram, we usually use Chen, Martin, and Oracle case method notation. Chen notation was named after Peter Chen who presented his diagram in 1967. It shows entities, relationships and attributes. Entities are represented by rectangles. Relationships are represented by a turbot symbol which is connected to entities. The symbol for the attribute is an ellipse or a circle. They are connected to the entity that describe with lines. In Martin notation of E-R model entities are represented by rectangles. Attributes are represented by ellipses or circles. Relationships are draw by a straight line between two entities. We don't name the relationship, but we do indicate the roles of the entities that the relationship bonds. There are only unary and binary relationships in this notation. In the Oracle case method notation entities are represented by rectangles. The attributes are inserted in the entity rectangle, in the way that they are listed below the name of the entity. Relationships are represented by a line between two entities. Logical Data Modeling is the second phase of Database Modeling. At this stage, a conceptual model turns into a relational Data model. In order to be able to implement the Database it is necessary to make a relational schema, since most of today's Database management systems uses a relational model. In the relational model, entities and bounds between entities converts into relations/tables. So, a relational model is a model where the Database consists of a set of relations. A relation is a table in the model with columns and rows that represents an entity or a bound. The value of an attribute is displayed by a column in the table. A relational schema is used to display the type of the entity in the relational model. A relation, or table is used to show a set of entities. An entity is shown by one row in the table. The attributes that describe the entity become attributes of relation. The primary key of the entity becomes the primary key for the relation. Bounds between the entities are formed by connecting an external key of one relation with the primary key of another relation, or they can be displayed with the creation of a new relation. With the development of the IT system, the necessity and the importance of making a good conceptual Data model increase. Accordingly to that, there comes the generation and development of conceptual Data Modeling tools with a graphical interface that facilitate the development of a model. Today there is already a large number of conceptual Data Modeling tools that can be connected to a variety of Database management systems. Toad is a conceptual Data Modeling tools. It can be connected with Oracle, SQL server, MySQL, SQLite, Postgre SQL DBMS. It works only on the Microsoft Windows platform. Navicat is a conceptual Data Modeling tool with a graphical interface that connects to Oracle, SQL Server, MySQL, SQLite, PostgreSQL, MariaDB DBMS. It works on Microsoft Windows, MAC OS and Linux platform. DbForge Studio is a conceptual Data Modeling tool with a graphical interface. It connects to SQL Server, Postgre SQL, MySQL and Oracle Database management system. Works only on Microsoft Windows platform. The tools have a quite similar working mode. The differences are mostly visual. They are transparent and easy to work on. In addition to enabling the creation of a conceptual model and Data Modeling in the model, the tools allow, also, the conversion of a conceptual model into a Logical model, and allow the creation of a new Database

Mark J Heumann - One of the best experts on this subject based on the ideXlab platform.

  • Logical Data Modeling what it is and how to do it
    2004
    Co-Authors: Alan Chmura, Mark J Heumann
    Abstract:

    Getting Started.- The Art Gallery Web: A Data Modeling Example.- Building the Data Map.- The Art Gallery Web (Continued).- Keys and Valid Associations.- The Art Gallery Web (Continued).- Defining Attributes.- The Art Gallery Web (Continued).- Verifying the Data Model.- Validating the Data Model.- Design Patterns.- From Logical to Physical.- The End and the Beginning.

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