Agile datawarehouse design and sub-second SQL analytics on massive datasets with Apache Kylin and Kyligence Analytics

2,000.00€
Agile datawarehouse design and sub-second SQL analytics on massive datasets with Apache Kylin and Kyligence Analytics

COURSE DESCRIPTION

In this instructor-led live training, participants will learn how to use Apache Kylin and use KAP monitoring. Apache Kylin™ is an open source, community supported, Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) for extremely large data sets on Hadoop. Kyligence Analytics Platform (KAP) is an Enterprise Data Warehouse powered by Apache Kylin that include enterprise-grade tools for agile model design, monitoring and performance optimisation.

 

LEARNING OUTCOMES

After this course students will be able to:

  • Understand  key basic concepts (Cube, CubeID, Engine, UHC, ..)
  • Identify Apache Kylin & KAP  architecture  and components
  • Learn how to design a Data Model for multi-dimensional analysis
  • Create different type of cubes: In memory Build, Layer Build
  • Optimize cubes: Derived Dim, Joint Dim, Hierarchy Dim, Mandatory Dim, AGG
  • Integrate Apache Kylin with  traditional BI tools like Apache Zepellin or Tablaeu
  • Consume real-time streaming data with Kylin
  • Use KyAnalyzer and KyStudio to monitor and optimize your cube.
  • Identify Apache Kylin and KAP use cases
  • Perform Apache Kylin and KAP demo

 

TRAINER

Alberto Ramón, has been working with Hadoop from 2014 as Big Data Engineer and is s currently working in UK for a large multinational bank while supporting the Apache Kylin project as a committer. He has been certified by Cloudera and Microsoft as Hadoop Administrator (CCAH) in CDH4 & CDH5, HBase specialist (CCSHB) and MS SQL Server Administrator and Developer(MCITP)

Course Features

  • Lectures 0
  • Quizzes 0
  • Language English
  • Students 0
  • Assessments Self
Curriculum is empty.

Reviews

Average Rating

0
0 rating

Detailed Rating

5 stars
0
4 stars
0
3 stars
0
2 stars
0
1 star
0
2,000.00€