Programming to NoSQL Data Storage

Course Information

  • Weekdays Course (Monday-Thursday) Duration: 4 Days
  • Weekend Course
    Sat & Sun)
    Duration: 2 Weeks
  • Study Modes: (Classroom/Virtual/OnSite)
  • What is included:
    instructor-led hands training,
    passing guarantee or free retraining, Lab access during the course, Course Material

From £1300

Interest Free Available

Enquire Now

Course Insight

Developing and working on the database using NoSQL is now being considered as a key skill in the arena of Big Data. The content of ‘Programming to NoSQL Data Storage Training’ is designed to let you know and learn about the process of storing data in a database without using tables. Relational Database Management System (RDBMS) works effectively as long as you are working with structured data, which fits perfectly with the rows and columns. But this course will provide you with adequate knowledge on how to work on unstructured data. This is where you are required to have enough skill in the NoSQL database management system. This course will let you learn about how to work with configurable schema, which is designed to handle information that is not a good fit for a table.

Through this course, you will learn how to deploy Cosmo-DB system in the IT infrastructure of the organization. Here, you will also learn about the difference between the schema-less and the relational model of data management. This course also includes the graph database training and the integration method of Mongo DB API (Application Programming Interface). Gradually, you will learn about how to extract data from different and diversified source (which are not structured) and develop a database using No-SQL. The key focus of this training is to make you an expert on working with the non-relational database.

  • You are expected to have a basic to advanced level of understanding of DBMS (Database Management System).
  • It is ideal if you have fluency in at least one high level language, but not required.
What will you gain after this course

The Data Science and Big Data Analytics course gives down to earth establishment level preparing that empowers prompt and successful interest in Big Data and different Analytics ventures. It incorporates a prologue to Big Data and the Data Analytics lifecycle to address business challenges that influence Big Data. The course gives establishing in essential and progressed systematic techniques and a prologue to Big Data Analytics innovation and instruments. Lab sessions offer chances to see how these strategies and devices might be connected to true business challenges by a rehearsing Data Scientist. This course gives an industry accreditation to business investigators, information distribution center specialists or different experts with comparative foundations to help them change into the universe of Data Science and Big Data Analytics that has extraordinary difficulties and opportunities.

  • Associate Solution Architect
  • Data Scientist
  • Software Engineer
  • Database Engineer
  • Database Analyst
Corporate Group Training
  • Customized Training
  • Onsite / Virtual
  • Instructor-led Delivery
  • For small to large groups

Dates & prices

This is an On-Demand course. Please call us on 02085347556 to arrange the training as per your requirement.

Course Contents

  • What Is Meant By NoSQL?
  • Distributed and Decentralized
  • Elastic Scalability
  • High Availability and Fault Tolerance
  • Brewer’s CAP Theorem
  • Row-Oriented
  • Schema-Free
  • High Performance
  • Introduction to Cassandra
  • Describe Apache Cassandra
  • Common use cases – large deployments, lots of writes, statistics
  • Cassandra architecture
  • Select and install a Cassandra version
  • Configure Cassandra for a single node, multinode
  • Start and stop a Cassandra instance
  • Installing Cassandra on Windows, Mac, Ubuntu
  • Basic CLI Commands
  • Understand basics of data modeling
  • Key Space
  • Column Family, Column Family Options
  • Wide Rows, Skinny Row
  • Column Sorting
  • Super Columns
  • Counter Column Family
  • Composite Keys and Columns
  • Time To Live
  • Indexing in Cassandra: primary, secondary and custom
  • Secondary Indexes in Cassandra
  • Difference between Custom and Secondary Indexes
  • Difference between Relational Modeling and Cassandra Modeling
  • Patterns and Anti-Patterns in Cassandra Modeling
  • Understand replication
  • Understanding data partitioners
  • How nodes communicate – Peer-to-Peer Model
  • Anatomy of Read/Write operation
  • How are Deletes handled in Cassandra
  • Gossip and Failure Detection
  • Anti-Entropy and Read Repair
  • Memtables, SSTables, Commit Logs, Flushing, Row Merging, Cache (Key, Row)
  • Hinted Handoff
  • Compaction: Choose and implement compaction strategies
  • Bloom Filters, Tombstones
  • Managers and Services
  • VNodes
  • Indexes and Caches
  • Tuning Cassandra
  • Backup and Recovery methods
  • Balancing
  • Bootstrapping
  • Node Tools Commands
  • Monitoring critical metrics
  • Configure nodes and clusters using CCM
  • Bulk Loading Data to Cassandra
  • Bulk Export of Data from Cassandra
  • Populate and test nodes using Cassandra-stress
  • Cassandra Security: Authentication, Authorization, Physical Security
  • Different deployment models
  • Installing MongoDB On Windows
  • Installing MongoDB On MAC
  • Installing MongoDB On Ubuntu
  • Starting and stopping MongoDB server
  • How the drivers work in general
  • Driver APIs with examples
  • Drivers Install Java
  • Introduction to the MongoDB API
  • Performing Queries Overview
  • Performing Queries Using The Cursor
  • Performing Queries Query Modifications
  • Adding Information Database, Collection And Document
  • Adding Information Arrays
  • Adding Information Objects
  • Adding Information The _Id Field
  • Performing Modifications Basic Document Updates
  • Performing Modifications Updating Arrays And Fields
  • Performing Modifications Deleting Documents

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