Explanatory Analysis with Jupyter Notebooks

When it comes to data-driven research, presenting the results is a complicated task. Jupyter Notebook is an open-sourced, extensible, and collaborative modern tool that empowers data professionals to create and share rich documents that contain data, live code, visualizations, and text narrations

Pillars of Cloud Native Architecture

At this session we will discuss the meaning of term "cloud native" and will talk about 4 pillars of a great cloud architecture:
- Availability,
- Scalability,
- Security
- Automation.
We will talk about cloud elasticity and why Data Developers should care about session resiliency. We will see how different traditional application architecture is from Cloud Native architecture and how traditional data pipelines are different from Cloud Native data pipelines

Azure CosmosDB: reach out for the stars.

Azure Cosmos DB is a fully managed, fast and cost-effective NoSQL database with multi write data distribution to any Azure region.
In this session, we will discuss
- how Azure CosmosDB is different from other data management systems,
-Azure CosmosDB throughput and performance
- How costs are calculated
- Different Azure CosmosDB APIs
- Different data modeling techniques.

Analyzing Big Data in Azure cloud using Spark and Databricks

Databricks is one of the best tools for data exploration. It allows us to connect and query any data management service or read files in various formats. Databricks runs on every major public cloud, Azure, AWS, Google, and is tightly integrated with the cloud security, storage, and other cloud services. Databricks allows you to use the SQL language or programming languages like Scala or Python in a rich web interface based on Jupyter Notebooks.
During this session we will talk about Azure Databricks key features, and typical scenarios where Spark can fit, will see a lot of demos and I will share my top list of Azure Databricks best practices.

Question everything

Asking questions is easy. Asking good questions is much more difficult. Lots of times we asking a wrong questions. We know everything about technology but how many times it happened to you when you have solved the problem your customer haven't asked for?
Come to this session to see how our assumptions and "common sense" is leading us to the wrong direction.

Building Tomorrow's Warehouse Today: Modern Data Warehouse Modelling Insights

Application development space is changing rapidly in the modern cloud-based world. Data warehouses space is changing and evolving not less.
This session explores the fundamental shifts in data warehousing architecture and data processing design principles

During this session we will discuss
* Data modelling terminology
* Data warehouses purpose
* Centralized and Decentralized data access architectures
* Modern Data Warehouses Challenges
* Which data its worth keeping

You will leave with understanding how to pull, process and store the company data in the cloud so its ready for decision makers and is easy to analyze.

Develop Any Visual in Power BI

Have a uniqie report idea and cannot find how to visualize it with exisiting Power Bi components?
Come to my session to learn how to visualize anything using your imagination and custom Python libraries.

What is Data Governance and why do you need it in your organization

Come to this session to learn about what Data Governance is and how magically it can transform chaos in your Data Analytics plane.

Easy column lineage extraction from your Snowflake Data Warehouse

Click on any Data Mart in the Data Warehouse and learn where the data in each columm came from. Sounds fun? Come to this session to learn how Snowflake metadata layer allows piece of cake column data lineage extraction.

The Decentralized Data Access Revolution

The traditional centralized data access model faces more and more challenges.

During this session we will discuss why many companies shift towards decentralized data access architectures. We will discuss Data Mesh and Data Fabric paradigms, explore their principles, benefits and challenges.

Session highlights:
* Understand core concepts and principles behind Data Mesh and Data Fabric architectures
* Learn about the challenges and considerations when adopting Data Mesh or Data Fabric within your organization
* Gain insights how decentralized data access models enhance data quality, accessibility and scalability.

Digging Deeper: What You're Paying For in the cloud

Cloud costs can be surprisingly complex, and understanding them fully can save businesses a lot of money.

In this session, we will discuss
- Cloud onion layers of responsibilities
- Unexpected cloud costs
- Complexity of pricing models
- Idle resources
- Data transfers
- Reserved resources
- Vendor lock-in costs

By understanding where your cloud dollars really go, you’ll walk away equipped to optimize spending, prevent surprise charges, and make data-driven decisions that align with your budget and goals.

Snowflake Metadata Mastery: insights and hidden gems

Explore how Snowflake’s metadata tables can unlock valuable insights into your data processing and storage.

In this session, we’ll dive into practical strategies for using snowflake metadata to gain visibility and improve efficiency.

Walk away with actionable techniques to enhance your Snowflake environment.

Mastering Modern Data Pipelines

During this session, we will discuss the core concepts and architectural principles behind building robust, scalable, and reliable data pipelines.
We will look into how decoupling components, leveraging event-driven architectures, and data orchestration can transform your approach to data processing.
This session will equip you with tools and insights to help you design pipelines that power data-driven systems.

The target audience is Data Engineers and Data Architects