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The course NoSQL Data Access deals with various forms of NoSQL databases, where the data is stored differently than in traditional relational databases.
NoSQL databases are not table oriented and are mainly used to increase the speed of data access and the scalability for large numbers of users. The main types of NoSQL databases are discussed in the course such as wide-columns stores, key-values stores, document databases and graph databases.
Attention is paid to data storage in Google Big table as an example of a column oriented store. This also includes distributed storage and column families, versioning and null handling.
The operation of Cassandra and Redis as implementations of key-value stores is discussed as well. The use of associative arrays and data storage in the cache is explained.
Document oriented databases such as MongoDB and CoucheDB are also discussed. The various document formats such as JSON, XML and YAML and their applications are the subject of the course program.
Finally attention is paid to GrapQL databases of which Neo4J is a well-known example. This includes a discussion of Cypher Queries and Path Finding Queries.
The course NoSQL Data Access is intended for developers and other interested parties who want to get to know the possibilities and applications of NoSQL databases.
Knowledge and experience with SQL and approaching relational databases is beneficial for understanding, but not strictly necessary.
The theory is discussed by means of presentations. Illustrative demos are used to clarify the concepts discussed. The theory is interchanged with experimenting with the demos yourself. Course times are from 9.30 to 16.30.
After successful completion of the course the participants receive an official NoSQL Data Access certificate.
Module 1 : NoSQL Intro
Module 2 : Column Oriented Stores
Module 3 : Key Value Stores
Reasons for NoSQL
No Single Product
Distributed File System
In Memory Snapshot
Redis and Cassandra
Module 4 : Document Databases
Module 5 : Graph Stores
What are Documents?
Semi Structured Data
XML, JSON, BSON and YAML
Cross Language Access
MongoDB and CouchDB
Property Graph Model
Path Finding Queries
Graph Global Operations
Design for Query Ability
In Graph Indexes