Databases: OLAP and Recursion

Jennifer Widom, StanfordOnline

This course is one of five self-paced courses on the topic of Databases, originating as one of Stanford's three inaugural massive open online courses released in the fall of 2011. The original "Databases" courses are now all available on edx.org.

This course builds on concepts introduced in Databases: Relational Databases and SQL and is recommended for learners seeking to understand On-Line Analytical Processing (OLAP) and/or recursion in the SQL language.

  • The On-Line Analytical Processing section of this course introduces star schemas, the data cube concept, and OLAP features in relational databases including the Cube and Rollup operators.
  • The Recursion section of this course covers the SQL standard for queries over recursively-defined relations.

About the Database Series of Courses

"Databases" was one of Stanford's three inaugural massive open online courses in the fall of 2011. It has been offered in synchronous and then in self-paced versions on a variety of platforms continuously since 2011. The material is now being offered as a set of five self-paced courses, which can be taken in a variety of ways to learn about different aspects of databases.

Relational Databases and SQL is the most popular course in the Databases series. It is applicable to learners seeking to gain a strong understanding of relational databases, and to master SQL, the long-accepted standard query language for relational database systems. Additional courses focus on advanced concepts in relational databases and SQL, formal foundations and database design methodologies, and semistructured data.

All of the courses are based around video lectures and demos. Many of them include quizzes between video segments to check understanding, in-depth standalone quizzes, and/or a variety of automatically-checked interactive exercises. Each course also includes an unmoderated discussion forum and pointers to readings and resources. The courses are described briefly below. Taught by Professor Jennifer Widom, the overall curriculum draws from Stanford's popular longstanding Databases course.

Why Learn About Databases

Databases are incredibly prevalent -- they underlie technology used by most people every day if not every hour. Databases reside behind a huge number of websites; they're a crucial component of telecommunications systems, banking systems, video games, and just about any other software system or electronic device that maintains some amount of persistent information. In addition to persistence, database systems provide a number of other properties that make them exceptionally useful and convenient: reliability, efficiency, scalability, concurrency control, data abstractions, and high-level query languages. Databases are so ubiquitous and important that computer science graduates frequently cite their database class as the one most useful to them in their industry or graduate-school careers.

What will you learn

Stanford's online offering in Databases is now available as a set of five self-paced courses:

Databases: Relational Databases and SQL

  • Introduction to the relational model and concepts in relational databases and relational database management systems
  • Comprehensive coverage of SQL, the long-accepted standard query language for relational database management systems

Databases: Advanced Topics in SQL (prerequisite: Relational Databases and SQL)

  • Creating indexes for increased query performance
  • Using transactions for concurrency control and failure recovery
  • Database constraints: key, referential integrity, and "check" constraints
  • Database triggers
  • How views are created, used, and updated in relational databases
  • Authorization in relational databases

Databases: OLAP and Recursion

  • Star schemas, the data cube concept, and On-Line Analytical Processing (OLAP) features in relational databases including the Cube and Rollup operators
  • The SQL standard for queries over recursively-defined relations

Databases: Modeling and Theory

  • Relational algebra – the algebraic query language that provides the formal foundations of SQL
  • Dependency theory and normal forms in relational databases as the basis of schema design
  • The data-modeling component of the Unified Modeling Language (UML), how UML diagrams are translated to relations

Databases: Semistructured Data

  • The XML model for semistructured and self-describing data, including DTDs and some features of XML Schema
  • The JSON model for human-readable structured or semistructured data
  • The XPath language for processing XML data, and many features of the more advanced XQuery language
  • An introduction to the XSLT rule-based language for querying and transforming XML data

Dates:
  • 30 June 2020
Course properties:
  • Free:
  • Paid:
  • Certificate:
  • MOOC:
  • Video:
  • Audio:
  • Email-course:
  • Language: English Gb

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