Database Basics

Database Concepts

  • Source context: Enterprise Data Analytics, Database Basics by Jiding Zhang, Assistant Professor of Information Systems, W. P. Carey School of Business.

  • Agenda (as introduced):

    • Database concepts

    • Entity-relationship modeling

  • Core definitions:

    • Database: an organized collection of logically related data.

    • Database Management System (DBMS): a collection of programs that allows users to create and maintain a database; functions include:

    • Define data

    • Construct data

    • Manipulate data: Insert, Delete, Update, Retrieve

    • Data dictionary: a repository that defines data elements and their characteristics; used to ensure data consistency.

    • Metadata: data that describes the structure of the data (self-contained description of the data structure).

  • Key concepts referenced in the slides:

    • Data independence: the separation of data descriptions from the programs that use the data.

    • Data sharing, data security, and controlled access are facilitated by DBMS.

  • Entity-relationship modeling (ER modeling) is listed as an agenda item; no detailed content on ER modeling is provided in the transcript.

Data Models and Data Stores

  • Data stores in the slides are categorized into:

    • Relational data stores (examples): MySQL.

    • Non-relational data stores (examples): HayStack, HBase.

  • Real-world data representations shown as examples:

    • Instagram app data and metadata storages; a JSON-like data sample is shown (see Page 6):

    • The Data example (JSON-like structure):
      $$
      {
      "kind": "software",
      "trackName": "Instagram",
      "sellerName": "Burbn, inc.",
      "description": "Instagram\n\nOver 130 million users love Instagram! It\'s a simple way to capture and share the world\'s moments on your iPhone.",
      "price": 0,
      "currency": "USD",
      "version": "4.1.1",
      "fileSizeBytes": "13394605",
      "sellerUrl": "http:\/\/instagram.com\/