Certifications included: Certified Associate in Big Data (CABD) Certified Professional in Big Data (CPBD)

1. B I G D A T A
GLOBAL COMPETENCE
FRAMEWORK
CERTIFICATION SUMMARY
BIG DATA
CERTIFICATION
SCHEMA AND
SUMMARY
JULY, 2020

2. C E R T I F I C A T I O N D E F I N I T I O N
This certification on Big Data will enable you to work closely with the customer and the
solutions architect to translate the customer's business requirements into a Big Data
solution. You'll earn deep knowledge of the relevant technologies, understand the
relationship between those technologies, and how they can be integrated and
combined to effectively solve any given big data business problem. Ability to design
large-scale data processing systems for the enterprise and provide input on the
architectural decisions including hardware and software.
Maintaining
certification
Competency
credits
NEVER STOP
BUILDING
YOUR
CAREER
W H O S H O U L D A P P L Y ?
The certification is aimed at individuals who are involved in enterprise Big Data analysis, who
require a working knowledge of the principles behind Big Data, who need to know the terminology
used and some of the theory behind the practice.
A Q O N T A B I G D A T A C E R T I F I C A T I O N S C H E M A
Pre-requisite
Exam information
Training and
exam fee
NA NA
40 questions
60 minutes
multiple choice
80 questions
150 minutes
multiple choice
NA
60 CRPs
every 3 years
Available via
CTPs
Available via
CTPs
"This certification was really informative and very well put together. I learned a lot
and more so, learned in a structured manner. For people like me who come from
traditional data background and new to big data concepts this way of
presenting the course is very important and fruitful. I hope to continue my
learning and end up with a good depth in knowledge of big data".
- Big Data credential holder
5 15

3. C O U R S E O U T L I N E
Introduction to Big Data and Data Sciences
Introduction to concepts
Big Data Reference Architecture
Introduction to HDFS and MapReduce (Pig, HBase, Hive, Sqoop)
Industry use cases
Hadoop Installation & HDFS Hands-on
Map Reduce – Deep Dive
Map Reduce – Hands on development & Deployment
Map Reduce – Hands on development & Deployment
PIG deep dive – Theory
PIG hands on
Hive deep dive – Theory
Hive hands on
Hadoop administration & troubleshooting
Big Data Captstone project
T O P 5 R E A S O N S T O G E T C E R T I F I E D
Credibility - Certifications validate knowledge and skills required to excel in your role.
Aqonta certifications are recognized globally and is adapted in major corporations in
the industry.
Competitive advantage - Get the competitive advantage to grow your career faster.
Aqonta certification holders earn an average 28% more than their peers.
Stay relevant - Developed by leaders and practitioners, the certification council works
round the year to implement high quality and current standards in the industry.
Vendor neutral - The framework can be tailored to any industry and organizations of
any scale.
Continually improve - By earning and maintaining your certification you continually
develop your skills, knowledge and abilities.
NEVER STOP
BUILDING
YOUR
CAREER
G L O B A L C O M P E T E N C E P R O G R A M
Your certificate demonstrates your expertise and knowledge. Aqonta Global
Competence Program is structured to boost confidence in employers and brings more
visibility to your career achievements. Earn your competence badge and increase your
credibility and worthiness to your employers.
"The competence badge was a game changer in my job search. I
received more interview calls after I included my skill report and verified
badge earned from the competence program. The recruiters were able
to verify my achievements and potential. It certainly increased my
credibility in the job market".
- Global Competence Program member
© 2020 Aqonta Inc. All rights reserved

4. B I G D A T A D E T A I L E D S Y L L A B U S
In-memory database (IMDB)
Hardware technology advances adopted for In-memory systems
Software technology advances adopted for In-memory systems
Data compression
No aggregate tables
Insert-only tables
Column, row, and hybrid storage
Partitioning
Benefits of NoSQL
Data visualization application
Inbuilt tools and capabilities in Hadoop ecosystem
Hadoop cluster attributes
High availability
Load balancing
High availability and load balancing
Distributed processing and parallel processing
Usage of Hadoop big data cluster
Types of nodes and their roles
Hadoop Cloudera enterprise distribution
Data integration services
Hadoop data storage
Data access services
Database
Unified (common) services
Cloudera proprietary services and operations/cluster management
A Hadoop Hortonworks framework
Data governance and schedule pipeline
Cluster management
Data access
Data workflow
A Hadoop MapR framework
Machine learning
SQL stream
Storage, retrieval, and access control
Data integration and access
Provisioning and coordination
Pivotal Hadoop platform HD Enterprise
A Hadoop ecosystem on IBM big data
A Hadoop ecosystem on AWS
Microsoft Hadoop platform is HDInsight hosted on Microsoft Azure
1. Introduction to Big Data and Data Sciences
1.1 Big data
1.2 In-memory technology
1.3 NoSQL databases
1.4 Data visualization
1.5 Data science
1.6 Summary
2. Big Data Hadoop Ecosystems
2.1 Big data Hadoop ecosystems
2.2 Big data clusters
2.3 Hadoop big data cluster nodes
2.4 Commercial Hadoop distributions
© 2020 Aqonta Inc. All rights reserved

5. B I G D A T A D E T A I L E D S Y L L A B U S
Guideline for estimating and capacity planning
Cluster-level sizing estimates
For master node
Worker node
Gateway node
Summary
Cloud technology concepts
Authentication and security
Presentation tier
Business logic tier
Data tier
Relational databases
NoSQL database
Data storage
Public cloud
Private cloud
Hybrid cloud
Community cloud model
Software as a Service (SaaS)
Single tenant
Multi-tenancy
Multi-instance
Benefits of SaaS
Platform as a Service (PaaS)
Development as a Service (DaaS)
Data as a Service with Paas
Database as a Service with Paas
PaaS tied to SaaS environment
PAAS tied to an operating environment
Open-platform PaaS
Microsoft Azure Portal
Amazon Web Services
Salesforce offerings on cloud
Network as a Service (NaaS)
Identity as a service (IDaaS)
Single Sign-On
Federated Identity Management (FIDM)
OpenID
Data encryption
Encryption in transit
Encryption-at-rest
End-to-end encryption
Backup and recovery
Summary
2.5 Capacity planning for systems
3. Cloud Computing
3.1 Cloud computing technologies
3.2 Multi-tier cloud architecture model
3.3 Cloud architectures
3.4 Cloud offerings
3.5 Cloud security
© 2020 Aqonta Inc. All rights reserved

6. B I G D A T A D E T A I L E D S Y L L A B U S
Data discovery into the system
Data discovery stages
Data quality
Batch processing
RDBMS to NoSQL
Flume
Stream processing
Real-time
Lambda architecture
The data storage layer
Data storage - best practices for better organization and effectiveness
Landing
Raw
Work
Gold
Quarantine
Business
Outgoing
Computing and analyzing data
Apache Spark analytic platform
Spark Core Engine
Spark SQL
Spark Streaming
Visualization with big data systems
Data governance
People and collaboration in accordance with DevOps core concept
Environment management
Documentation
Architecture board
Development and build best practices
Version control
Release management
Client-services presentation tier
Data catalog services
Workflow catalog
Usage and tracking
Security catalog
Processing framework
Ingestion services
Approach to data science
Supervised models
Neural network
Multi layer perceptron
Decision tree
Unsupervised models
Clusters
Distances
Normalization
K-means
4. Building Big Data Applications
4.1Traditional enterprise architecture
4.2 Principles to build big data enterprise applications
4.3 Big data systems life cycle
4.4 Building enterprise applications with Spark
4.5 Data science
© 2020 Aqonta Inc. All rights reserved