Trefoil Academy
Data Operations
Modern data warehousing
The data landscape has changed drastically in the past couple of years, and what it means to build data platforms has evolved alongside it. The organization, tools, languages and architectural patterns have all shifted to take advantage of emerging technologies, cloud scalability and advancements in analytics… but how to you evolve alongside it?
In the first part of this one day workshop we are going to look back on the progress of the world of data warehousing during the last 5-10 years from proprietary enterprise data warehouse and business intelligence platforms to distributed cloud data platform as service. In this workshop we also would like to share with you an architectural perspective that underpins the failure of many data platform initiatives. We would demonstrate how we can adapt and apply the learnings of the past decade in building a successful data platform.
In the second part of the workshop we will introduce you to data infrastructure reference architectures compiled from discussions with many of practitioners. In the following block we will focus on the services that are needed to build such modern platform in Microsoft Azure
Azure data factory
As cloud platforms expand in scale and breadth, there is growing need for an orchestration tool that can bridge the gaps between distributed services. For Azure cloud users, Azure Data Factory provides this glue, pulling together services into a coherent data preparation and transformation pipeline. However, many people make the leap from on-premises SSIS and use Data Factory in the same way – this will get you so far, but successful Data Factory developers write less code, reuse components and harness the emerging Data Flow technologies.
This three day course takes the Data Factory novice, runs them through the fundamentals before taking them on a journey to building code-efficient, agile orchestration solutions. We will look at some of the most common scenarios, including pulling on-premises data into the cloud, hosting SSIS packages and communicating with Web APIs.
Our team and our partners are recognised for creating and delivering fantastic content in a simple and approachable manner. We have a variety of training courses covering the entire data spectrum.
Spark Databricks Essential Training
Data processing and data analysis is being democratised. Tools such as Databricks, mean you do not need to be a Java expert to be a Big Data engineer/analyst anymore. Databricks has made your life much easier! While it is easier, there is still a lot to learn and knowing where to start can be quite daunting.
Too often training courses are academic, teaching theory and not application. We have created an applied Azure Databricks course. We have built this course based on demand and real-world problems faced by our customers. It will teach you how to implement different scenarios in Databricks, but most importantly it will tell you why, when to implement and when not to implement.
This course is designed to take a data professional from Zero to Hero in just 3 days. You will leave this course with all the skills you need to get started on your Big Data Journey. You will learn by experimentation, this is a lab heavy training session. If you are starting a new project and want to know if Databricks is suitable for your problem, then we also offer tailored training around your problem domain.
Azure Synapse Analytics
The data landscape has changed drastically in the past few years, and what it means to build data platforms has evolved alongside it. The tools, languages and architectural patterns have all shifted to take advantage of emerging technologies, cloud scalability and advancements in Data Science… but how to you evolve alongside it?
The typical problems of “Big Data” are becoming more mainstream:
– Data volumes are growing
– There is a boom in sensor & event data
– Exotic data types are now part of many third party integrations
– Business opportunities need immediate reaction and cannot wait on a release cycle that counts in months
We have been building Modern Data Warehouses for the last few years, adapting as tools came and went. The architectural choice is vast and constantly changing but we have a simplified reference architecture, and we want to teach you to master it.
Advancing Analytics use their consultancy experience and close relationships with Microsoft to deliver the most up-to-date Data Lakehouse course available. We will show you what works, what does not work and most importantly how to build a Modern Data Lakehouse for your business. We use hands-on labs to make sure you’re getting the most out of the course and you’ll build a solution to take away with you.
End to End Azure Data Platform
In this workshop you will learn about the main concepts related to advanced analytics and Big Data processing and how Azure Data Services can be used to implement a modern data warehouse architecture. You will learn what Azure services you can leverage to establish a solid data platform to quickly ingest, process and visualize data from a large variety of data sources. The reference architecture you will build as part of this exercise has been proven to give you the flexibility and scalability to grow and handle large volumes of data and keep an optimal level of performance.
In the exercises in this lab you will build data pipelines using data related to New York City. The workshop was designed to progressively implement an extended modern data platform architecture starting from a traditional relational data pipeline. Then we introduce big data scenarios with large data files and distributed computing. We add non-structured data and analytics into the mix and finish off with real-time stream analytics. You will have done all of that by the end of the workshop.
The workshop content will be delivered over the course of three days.
