Data Models Flashcards
What is Data modeling
the process of creating a specific
data model for a determined problem domain.
A representation, usually graphic, of a
complex “real-world” data structure.
4 importance of Data modelling and explain.
- Communication tools: allows interaction between designers, programmers and end users
- enhanced organizational understanding: gain new insights into how different components of a business interconnect
- Diverse views on data: allows different level of business to view data differently based on their roles
-holistic view: gives a blueprint of the model.
Attribute
A characteristic of an
entity or object.
(column)
relationship
Association between entities
types of relationships
One to one ( 1:1)
One to Many (1:M)
Many to Many (M:N)
Define business rules?
Brief, precise and unambiguous description of a policy, procedure or principle within a specific organization.
What does business rules help with?
It helps establish entities, attributes and constraints for our model.
It allows the designer to understand the scope of the data and procedures of the business to create and appropriate model.
in business rules, nouns and verbs can translate into which data model components?
Noun - entity
Verb - relationship
What are Network models
Models which represent complex data through a collection of records in 1:M relationships.
- improve database performance
- more effective than Hierarchical models.
Who introduced the relational model
E.F. Codd in 1970
Desc the relational model
Relation -> Table
Contains tuples (rows) and attributes (cols).
-great idea but huge demand computationally.
pros of relational model
Performs the same functions as the Network and
Hierarchical Models, but makes it easier to implement and understnand
- Hides complexity from user.
what are the 3 things that a SQL - RDBMS consists of?
- End-user interface
- Collection of tables stored in the database
- SQL engine (handles all the queries)
Crows foot notation
graphical representation of entity relationship diagrams (ERDs)
lines, unlike chen which got diamond shape between entities.
Explain the Object- Oriented Model.
- Both data and its relationships are contained in single structures (objects)
- objects with similar characteristics are grouped in classes.
- typically depicted in Unified Modeling language (UML) class diagrams
explain class hierarchy and inheritance in the OO model.
- classes are organized in a class hierarchy. objects within the class hierarchy can inherit the attributes and methods of those above it.
Extended relational data model
Allows many of OO features such as objects. Better suited for business applications.
Characteristics of Big Data databases.
Volume: amount of data
Velocity: speed which data grows and is processed
Variety: The different data formats which data is collected in.
Relational approach problem with big data challenges.
Doesnt always match the needs of big data.
e.g. Its not always possible to fit unstructured data into tables.
Solutions to Big data related problems
- Apache Hadoop
- Hortonworks Data Platform
- Vertica Advanced Analytics Platform
- NoSQL
Apache Hadoop
- large-scale data processing,
- unstructured or semi-structured data.
- ideal when cost-effective storage and batch processing are key considerations.
Hortonworks Data Platform
- managing big data within the Apache Hadoop ecosystem.
- governance, security, and operations alongside Hadoop.
Vertica Advanced Analytics Platform
- Excels in high-performance,
- advanced analytics on massive volumes of data.
- It’s optimal for use cases requiring fast query performance on large, structured data sets.
NoSQL:
- scenarios requiring high scalability and flexibility,
- particularly when working with unstructured or rapidly changing data.
- Ideal for web applications, real-time analytics, and handling large volumes of data with varying
structures.
