The best preparation for building an end-to-end, analytical warehouse solution with real-time insights.

Decision Tech for Business Growth

Relevant and rigorous training

Our developer course provides students with a comprehensive understanding of the procedures and techniques necessary to design NO-ETL schemas, rapidly load data, build advanced dashboards, ingest streaming, semi-structured data, and to implement predictive analytics.

Experience Builds Confidence

Hands-on, project-based learning

Through instructor-led discussion and interactive project-based labs, students will master Incorta key concepts, terminology and topics for on the job success.

Superheroes Wanted!

Audience prerequisites

Designed to serve the learning goals of data warehouse and database developers, this course requires experience with structured data, relational database systems, SQL, and shell scripting.

Although not required, we recommend that students have familiarity with a modern programming language such as PySpark and Spark MLib.

Data Warriors, Champions, and Visionaries

Professional certification for stardom

Incorta Certification establishes your leadership credentials and validates your expertise.

You can achieve Incorta certification by completing this course and by passing a certification exam. With a few clicks, you can easily add your digital certificate to your LinkedIn profiles.

Curriculum

Course modules

  • 1

    Details and Downloads

    • BYOL and Software Requirements

    • Student Workspace
  • 2

    Demystifying Variables and Filters

    • Formula Builder (New)

    • System Variables

    • Session Variables

    • Presentation Variables

    • Prompts

    • Insight Filters

    • Measure Filters

    • LAB: Session Variables

    • LAB: Presentation Variables

    • LAB: Runtime Security Filters
  • 3

    No-ETL Schema Design

    • Formula Columns in Schema Design

    • Simulating Join Types

    • Table Alias

    • Incorta Table

    • LAB: Cohort Analysis with Incorta Table

    • No Show: Data Hub stuff
  • 4

    Schema Workshop

    • Create the Schema

    • Sanity Check

    • Check #1: Count of Employees and Average Salary

    • Check #2: Count of Employees by Department and Title

    • Check #3: Average Department Salary and Distinct Employee Count

    • Check #4: Average Salary by Department Name and Title
  • 5

    Hierarchies

    • Hierarchies
  • 6

    Advanced Data Loading Strategies

    • Loading Data

    • Incremental Schema Loads

    • Snapshots

    • LAB: Dense Snapshot

    • LAB: Sparse Snapshot

    • Slow Changing Dimensions

    • LAB: SCD Type II

    • Data Integration from Multiple sources

    • Strategies for Semi-Structured Data

    • Additional PySpark resources

    • Data Hub = PostgreSQL Protocol for SQL
  • 7

    The Path From Dashboards to AI

    • Incorta Maturity Model

    • About Apache Kafka

    • Incorta Apache Kafka Connector

    • LAB: Streaming Ingest with Apache Kafka and JSON

    • Machine Learning and Predictive Analytics with Apache Spark

    • LAB: Predicting Airfares
  • 8

    Certification Exam

    • Requirements