Qlik Sense & Big Data. Strategies For Enterprise Deployments

Strategies for ETL on Big Data in Qlik Sense

What you'll learn

ETL of Big Data using partition processing

The use of ODAG and Dynamic Views when working with Big Data

How partitioning works on Databases

ODAG Big Data exploration tool for Big Data tables

The use of control tables in Qlik ETL

Versioning of the data structures in offline data ETL

Parallel extract of the data

Using optimized load for different scenarios of loading the data in the dashboards

Realigning of the data structures to achieve optimized load

Requirements

Students need to have a basic knowledge of Qlik Sense, and should ideally already built a basic Qlik Sense project.

All examples presented in this course are downloadable.

Description

Most of the times when projects fail, they don't fail because a developer didn't know a chart function or a script command in Qlik Sense.They usually fail because the project’s ETL strategy is not aligned to the environment in which the project is developed: database connections are too slow, datasets are too big, dashboard refresh time is too long.When datasets grow larger the whole ETL process might need to be redesigned to tackle this.In this training you will complement your Qlik knowledge with ETL strategies on Big Data and the use of ODAG and Dynamic Views.The course is split into three parts:The first part is an introduction on what Big Data is and how Qlik relates to Big Data.In the second part we will create projects from scratch for different scenarios of extraction, transformation and data load. You will learn some complex strategies on both offline data and database data sources, and the main focus would be on partition processing.The last part of the training is an extensive presentation of ODAG and Dynamic Views functionalities, as they were introduced specially to help developers tackle analysis of large amounts of data.All the examples presented in the training are downloadable and also you can email me regarding the course content in case you have questions.

Overview

Section 1: Intro and Content

Lecture 1 Course Content

Section 2: Introduction to To Big Data

Lecture 2 Introduction

Lecture 3 What is big Data

Lecture 4 Qlik and Big Data

Section 3: Big Data Processing

Lecture 5 Big Data Processing

Lecture 6 Big Data Processing Strategy

Lecture 7 Partitioning

Lecture 8 Big Data Processing High Level Diagram

Section 4: Offline Data Extraction

Lecture 9 Offline Data Extraction

Lecture 10 Simple Offline Data Cases

Lecture 11 Simple Offline Data Diagram and Environment

Lecture 12 Simple Offline Data Extract Example

Lecture 13 Versioning Offline Data Extract

Lecture 14 Versioning Ofline Data Extract Example

Lecture 15 Timestamped Offline Data Cases

Lecture 16 Timestamped Offline Data Extract Example

Lecture 17 AdHoc Extract Offline Data

Lecture 18 AdHoc Extract Offline Data Example

Section 5: Offline Data Transform

Lecture 19 Transform Offline Data

Lecture 20 Simple Offline Data Transformation

Lecture 21 Simple Offline Data Transformation Example

Lecture 22 AdHoc Tranform Offline Data

Lecture 23 AdHoc Tranform Offline Data Example

Lecture 24 Data Realingment Example

Section 6: Big Data ETL on Databases

Lecture 25 Data Extraction on DB Data

Lecture 26 Liniar Data Extraction

Lecture 27 Liniar Data Extraction Example

Lecture 28 Parallel Data Extraction

Lecture 29 Parallel Data Extraction Example

Lecture 30 AdHoc Extraction Example

Lecture 31 Data Transformation

Lecture 32 Data Transformation Example

Lecture 33 Data Load

Lecture 34 Optimezed Load Cases and Examples

Lecture 35 Dashboard Data Load Cases

Lecture 36 Dashboard Data Load Examples

Section 7: ODAG and Dinamic Views

Lecture 37 Introduction to ODAG

Lecture 38 ODAG Template Example

Lecture 39 ODAG Index Example

Lecture 40 ODAG Bindings and ODAG Link Example

Lecture 41 ODAG Other Bindings Parameters

Lecture 42 Dinamic Views

Lecture 43 Dinamic Views Example

Lecture 44 Advanced Data Exploration

Lecture 45 Advanced Data Exploration Using ODAG

Beginner Qlik developers that have a basic knowledge of the Qlik scripting and have built a basic Qlik project,Medium and advanced developers that have work with Qlik on small datasets and want to extend their expertise to enterprise wide, big data projects