26-28 November, 2019, Vilnius

Conference is over! See you next year.

Valdas Maksimavičius

Cognizant, Lithuania



Crowne Plaza Vilnius
(M. K. Čiurlionio str. 84, Vilnius, Lithuania).


Time & Date

10:00, 26 November




Valdas is an IT Architect at Cognizant, where he leads Data Lake and Data Science platform implementations on Azure Cloud for various sectors in the Nordics. He helped design and develop product recommendation, sales optimization, product pricing and churn reduction use cases. Valdas is passionate about AI, Formula 1 and Space Exploration.


Build a Modern Data Platform in Azure


In this 1-day workshop, you will learn about the main concepts related to data processing and data engineering with Azure Data Services. You will understand 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. Together we will implement a modern data platform architecture – a proven setup to give you flexibility and scalability to grow and handle large volumes of data and keep an optimal level of performance. 

Technologies you will use: Azure Data Factory, Databricks (w/Spark), Azure SQL, Azure Data Lake Gen 2, Event Hub, Stream Analytics, Power BI


  • Workshop Overview | 15 minutes
  • Modern Data Platform Concepts: Part I (Data Storages and Data Movement) | 15 mins
  • Lab 1: Load Data into Azure Data Lake Gen 2 and Azure SQL using Azure Data Factory Pipelines | 60 mins
  • Modern Data Platform Concepts: Part II (Data Exploration and Transformation) | 15 mins
  • Lab 2: Explore and Transform Big Data using Azure Databricks | 60 mins
  • Modern Data Platform Concepts: Part III (ML and Cognitive Services) | 15 mins
  • Lab 3: Add AI to your Big Data Pipeline with Cognitive Services | 60 mins
  • Modern Data Platform Concepts: Part IV (Real-time pipelines) | 15 mins
  • Lab 4: Ingest and Analyse real-time data with Event Hubs and Stream Analytics | 60 mins

Throughout a series of 4 labs, you will progressively implement a modern data platform architecture.

First, we introduce the concepts of the data lake and big data challenges. You start ingesting various data types to your Azure Data Lake Gen 2 storage. Then, you have to use Databricks and the power of Spark clusters to explore data files. Later, you incorporate AI into your data pipeline by invoking Cognitive Services and store results in Azure SQL database. Finally, you use car telemetry events as a source of streaming events that you will capture, store and process in real-time with Event Hubs, Stream Analytics, and Power BI.

Target audience

Prior working knowledge of the Azure Data Platform components is not required, but attendees should be familiar with the services at the theoretical level. Each lab will contain multiple exercises of different difficulty levels.

Target audience: BI Developers, Data Engineers, Data Scientists, Data Analysts, Database/Sys Admins

Technical requirements