Skip to content

First Tutorial Part 1: Benefits Of A Transparent Iterative Model Driven Approach

Jump to bottom
Laurent Hasson edited this page Nov 30, 2019 · 14 revisions
Previous Main Next
Main Part 2 -->

This Tutorial

In this tutorial, we'll cover a simple but non trivial set of scenarios and explore about 80% of the functionality provided by Tilda. We will focus on Pivoting and simple Analytics scenarios with a focus on performance, iterative development and transparency of assets generated and managed under the covers. We will cover:

  • Defining Tables And Columns
  • Defining Views And Columns
  • Joins
  • Aggregates
  • Pivots
  • Formulas
  • Realization And Refills

We expect someone to take about 45mn to get through this 12-parts material, and an accompanying video that shows an actual development session takes between 60 and 90mn to go through. The parts are:

We aim to demonstrate the power of Tilda and highlight through examples what we believe are the strongest points of the framework:

  • The 'T' in Tilda stands for 'Transparent' and the SQL assets it generates should be mostly obvious to someone who understands SQL, but not critical in using the framework.
  • The 'I' in Tilda stands for 'Iterative' and the development process supported by the framework encourages an agile approach to model development:
    • The Migrate utility allows automates many of the tasks that are typically handled by a DBA
    • Tilda models are living breathing models
    • The structure of how models are defined in JSON enable much more team concurrency in maintaining the model
  • Tilda is performance-conscious and implements many patterns that can handle large datasets.
  • Tilda is easy to adopt by a junior team of data engineers with modest database skills

We recognize that Tilda is a very young project and hope to also demonstrate that the risk of adopting it is low because all its assets are plain SQL and could easily be used in another environment.

Pre-requisites

You should have your development environment ready. See Getting Started Tutorial.

  • Have installed on your system Java, PostgreSQL, Eclipse and possibly Apache Tomcat.
  • Have your Eclipse workspace configured and initialized with a base project.
  • Have set up the tutorial project.

Further Readings

In this introductory tutorial:

  • We did not delve into the details of the meta-data kept about formulas declared as measures.
  • We did not discuss the Tilda.KEY table and how primary keys are automatically generated.
  • We did not look at all at the migration process and the iterative approach to data work it encourages. This is more clearly demonstrated in the video.
  • We did not discuss how the structure of the Tilda JSON definition makes managing model assets easy via versioning (in Git for example) compared to other tools where generated assets are not clean. This is more clearly demonstrated in the video.
  • We did not look at any of the Java code generated and the programming model to access Data through Tilda.
  • We did not look at how Java compiler-driven assists help iterate and refactor models dramatically while keeping a handle on your application code.
Previous Main Next
Main Part 2 -->
Clone this wiki locally