CASSANDRA ADMINISTRATION

A comprehensive Cassandra Administration course for Data Professionals, Developers and Administrators. Extensively covers Cassandra Architecture & Data Modelling along with CQL Querying, IOT and AI for Big Data.
COURSE OBJECTIVE:
​This course helps participants to understand core Cassandra and its implementation to handle Big Data applying Nosql principles. This course emphasizes on building Administrative and development skills to help participant implement the right topology to meet identified QOS.
This course also covers developing solutions using CQL and other different ways of managing data with best industry practices.

LESSON PLANS

SESSION 1: UNDERSTANDING BIG DATA PROBLEM
Session Goal:
Introduction to the topology of common existing limitations when dealing with a large amount of data along with the common solutions. The goal here is to lay down the foundation of a heterogeneous architecture that will be described in the following Sessions.
  • Identifying Big Data Symptoms.
  • Understanding the Big Data Projects Ecosystem.
  • Creating the foundation of a long-term Big Data Architecture.

SESSION 2: EARLY BIG DATA WITH NO-SQL
Session Goal:
Understanding how a NoSql Database can be a starting point for your Big Data Project and how it can deal with large amount of data. Limitations of this model and how it can be scaled to a full-fledged Big Data Project.
  • Choosing the right No-SQL Database.
  • Introduction to Couchbase.
  • Introduction to Elastic Search.
  • Using NoSQL cache in a SQL based Architecture.

SESSION 3: CASSANDRA ARCHITECTURE
Session Goal:
Objective of this session is to understand Cassandra Architecture and its important components. You will master Cassandra's internal architecture by studying the read path, write path, and compaction. Topics such as consistency, replication, anti-entropy operations, and gossip ensure you develop the skills necessary to build applications..
  • Cassandra Architecture.
  • Setting up Cassandra Peer to Peer architecture.
  • Understanding Replication.
  • Implementing Consistency.

SESSION 4: CASSANDRA DATA MODELLING
Session Goal:
This session will focus on Conceptual Data Modelling techniques, Principles and Methodology, Design Techniques and Optimization. Participants will learn primary techniques for successful Apache Cassandra and DataStax Enterprise deployment while reviewing select Data Modelling use cases simultaneously.
  • Understand Principles of Cassandra Data Modelling.
  • Building Cassandra Data Models.
  • Understanding Basic Rules of Data Modelling.
  • Sample Data Model Implementation.
  • Implementing and Building Indexes.

SESSION 5: QUERYING USING CQL
Session Goal:
Participants will be taught extensively on leveraging the Processing work through long-term & real-time Data Querying in this session along with practical implementation of CQL usages.
  • Creating and updating Keyspaces.
  • Using User-defined Types
  • Working with CQL Clauses.
  • Slicing and Batching.
  • Working with Collections and Transactions.
  • Managing Consistency Changes.

​SESSION 6: LEARNING FROM YOUR DATA
Session Goal:
Understanding the concept of Machine Learning at different level of the preceding described patterns and through different relative methodology.
  • Introduction to Machine Learning.
  • Supervised and Unsupervised Learning.
  • A simple example of Machine Learning.
  • Using MLlib for Machine Learning.

SESSION 7: GOVERNANCE CONSIDERATIONS
Session Goal:
Monitoring; and more generally Governance is extremely important when dealing with Architecture that involve all the previously studied patterns. This Session will help safeguard participants from major issues, gain visibility and control over the Architectures.
  • ​Data Quality.
  • Architecture Scalability.
  • Security.
  • Monitoring.

SESSION 8: IOT & ARTIFICIAL INTELLIGENCE IN BIG DATA
Session Goal:
​Internet Of Things is bringing in great deal of data from various devices. Collecting, cleansing and using these data to extract value to help businesses decide and fine-tune their business model or even identify a new Business Opportunity can be made possible through Predictive Analysis applying proper Data Science and Machine Learning Algorithms.
CASE STUDY AND PROJECTS
Case studies are integral part of training. As part of this course we will ensure you  implement Real-time Case studies ​in various domains which includes:
  • Banking.
  • Telecom
  • Ecommerce.
  • HealthCare.​
These case studies will be evaluated by domain experts and you would get an opportunity to get Feedback on the work.
TRAINING FEATURES
1) Extensive Real Time Live Examples, Projects & POCs for improved practical competency, ensure deployment readiness and implementation.
2) Custom Lab, Software and Environment provided with Real-time Project Simulation.
3) Recorded Videos complemented with corresponding lecture ppts, materials & lab guides. (Provided in the form of MP4 videos, pdf, ppt for offline access as well).
4) Certification and Job-Interview Counselling & Coaching after every training.