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Big Data Architecture & Technology Concepts

Big Data
COURSE FEATURES
Course Duration
Duration
4 Days
Skill Level
Skill level
All levels info Course tailored to participants' expertise.
Course Language
Language
Romanian
Course Type
Type
In-class / Online-live
Assesments
Assessments
Yes
Price for Custom Training
Custom Training
1800 Eur / Day
Price for Open Class Course
Open Class
850 Eur / Participant

The course is designed to make sure the participant will understand the usage and applicability of big data technologies like Hadoop, Spark, Cassandra, Hbase, Kafka, and which aspects to consider when starting to build a big data architecture. 

This course is intended for:

– Existing architects from different other domains interested in understanding what architecting a big data solution means

OR

– Solution responsables/engineers knowledgeable in different big data solutions (Hadoop, Spark, NoSQL solutions, ETL components, ML) that would like to understand “the big picture” of what architecting a big data solution means. 

This course is taught in Romanian, with course materials available in either English, or Romanian. The course can be customized - on request.

DAY
1

TOPICS

9

TOPICS
9
Specific technologies overview and details:
Storage: NoSQL databases (random reads on data)
Overview of different NoSQL solutions
Cassandra detailed overview
Main concepts: data partitioning, distribution, replication, consistency, how to write and read data, compaction
How data is inserted / updated / deleted
Understand the main patterns and anti-patterns
Basic data modeling rules for Cassandra best performance
Use case based on Cassandra – hands on session
DAY
2

TOPICS

5

TOPICS
5
Main concepts recap
Differences to Cassandra
Main data modeling aspects: how data is best read
How to choose a noSQL solution – the considerations
Recap storage options: long term storage of immutable data (HDFS) & random writes/reads of data (Hbase/Cassandra/..).
DAY
3

TOPICS

10

TOPICS
10
Overview of different solutions : Storm, Spark , …
Distributed computations and Stream processing with Spark
Spark as ETL tool – examples and demo
Examples on using Spark and Spark streaming + demo session
Data Analysis
SQL on everything options: Hive, Impala, Spark SQL, Apache Drill
Integrate Cassandra with Spark SQL for data analytics, what kind of analytics can be performed
Hands on exercises for analytics with Spark SQL and Cassandra
Search solutions – the extra capability needed besides an SQL engine:
Overview of the capabilities of Solr, Elastic – what extra functionalities those bring to a SQL Engine solution
DAY
4

TOPICS

4

TOPICS
4
Why a messaging bus in a big data architecture?
Kafka demo in combination with Spark streaming
Clustering and Resource Management : Mesos
End to End example including Machine Learning – (we will complete/demo a noSQL + Spark app with ML)

Contact Us

Feel free to leave us your thoughts so we can discover the solution together!

EMAIL

academy@esolutions.ro

Get in touch

0753.029.187

Our address

Budisteanu Office Building, Strada General Constantin Budisteanu Nr. 28C, Sector 1, Bucuresti

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EMAIL

academy@esolutions.ro

Get in touch

0753.029.187

Our address

Budisteanu Office Building, Strada General Constantin Budisteanu Nr. 28C, Sector 1, Bucuresti

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