Big Data



Référence de la formation

KDS009

Niveau

Beginner

Nombre de jours

2 Days

Prix

1.390,50 € HT

Lieu de la formation

V: v-learning, virtual class



Pre-requis

None

Public

Project Managers, Product people and Managers, Developers and Architects who wants to know about Big Data.

Objectifs de la formation

Today companies have the capability to collect large amount of data. Handling large amount of data requires new technologies that are able to collect, cleanse, process and store effectively significant amount of information.
Many companies reached the conclusion that not using this collected data is actually loosing large amount of money. Big Data market is estimated to surpass $200 billion this year.
There is a tremendous business in Big Data and with the right methodologies and tools this row Data can be available for use.
This course provide the basis for Big Data and NoSQL DB environment, architecture, process and available tools. The course
will also present Big Data methodologies and deployment recommendations

Contenu du cours

Table 1: KDS009 - Course Contents
Chapter Description
Introduction • Definition: Big Data, NoSQL
• The need for Big Data technology
• Tradition technologies Vs Big Data technologies
• Big Data project requirements
• Big Data Project workflow
Big Data
Architecture
• Big Data project definitions
• Data sources & development resources
• Big Data technologies evaluation
− The need for POC
Data Collection
& Ingestion
• Streaming Concept
− Rest API
• Apache Kafka
− AWS Kinesis, Azure Event Hub
• Apache Flume
• ELK package
− Logz.io
Hadoop – Introduction • What is Hadoop?
• Hadoop Architecture
• Hadoop File System (HDFS)
− Architecture
− NameNode & DataNode
• Hadoop MapReduce
• Apache YARN
• Apache Oozie, ZooKeeper
• Project non-functional support
− Sentry, Tez, Ambri, Knox, Falcon
Project decision – Hadoop deployment • Hadoop Distribution
− Examples: Cloudera, Hortonworks
• Hadoop as a service
• Can Big Data project switch environments?
• Hadoop deployment requirements
• Hadoop Performance Best Practices
Hadoop project POC • POC environment
• Using Apache Pig! & Apache Sqoop for POC
Large-scale data processing framework • Apache Storm
• Apache Spark
− Concept & Architecture
− Programming with Spark
− Spark Streaming
− Spark SQL
− MLlib
− GraphX
Project development cycle & deployment – Spark • Big Data – Development methodologies
− Waterfall Vs Agile
• ETL development cycle & deployment
• Tests Cycle
Big Data DB types • Key-Values Stores
− Redis
• Column Family Stores (Wide Column Stores)
− Apache HBase
− Apache Cassandra
• Document Databases
− MongoDB
• Graph Databases
 – Mathematical Graph as a DB
Big Data & RDBMS • Product logic
• Apache Hive
− Architecture – Batch Processing
• Apache Impala
− Massively Parallel Processing (MPP)
Big Data Northbound Interfaces • Big Data to OLAP
• BI Visualization
• Scaling BI over Big Data
Big Data – system ATP • Big Data – system ATP
The End • Trends & Conclusions
• Q&A
• Course’s Evaluation

Dates


30 Sept 2020 au 01 Oct 2020


NOTE :
ATTENTION CETTE FORMATION EST SUR MESURE
CE COURS EST REALISABLE TOUTE L'ANNEE AVEC UN MINIMUM DE 5 PARTICIPANTS


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+33 (0) 950 20 91 64


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