SQL vs NoSQL

Mostly I worked with structured databases (SQL) when I crossed the path of NoSQL found some interesting match between SQL and NoSQL. Some says, to learn NoSQL you need to start with clean slate, though my view is a bit different. The story is looking at NoSQL database from the view of a SQL database professional and compare basic differences.

Securing sensitive data in a Modern Data Warehouse by using Azure Synapse Analytics

In recent years, the number of data breaches is growing exponentially. Data security is therefore a major concern for every organization. Cloud platforms like Azure, Amazon, or Google are promising that data stored in their platforms is almost impossible to hack. And should it be leaked, it would be encrypted so no one from the outside could use the data.
However, there are security issues that can arise from the inside, like rogue employees mishandling sensitive data like Personally identifiable information (PII) and there needs to be a process in place to deal with this. In this session, we will highlight how a modern data warehouse can act as a safeguard against malicious data exposure or misusage.
This highly demo-driven session will show you different ways to protect PII data in both production and non-production environments by using the latest capabilities of Microsoft Azure Synapse Analytics.

Move your NoSql database to Azure by using Azure data Factory

NoSQL database have grown popularity in recent years due to the flexibility of data modeling and scaling up capabilities. NoSQL database also have been using in big data landscape. The demo rich session will elaborate difference between SQL and NoSQL. And end to end solution for data moving capabilities from NoSQL database MongoDB by using Azure data factory.

Empowering Data Engineers with Microsoft Fabric

In today's data-driven world, the role of data engineers has become increasingly crucial in enabling organizations to extract meaningful insights from vast amounts of data. Microsoft Fabric, a powerful data processing and integration platform, has emerged as a game-changer for data engineers seeking seamless and efficient data management solutions.
The demo driven session will demonstrate different data engineering components those exists in Azure Synapse and Azure Data factory how that differs in Microsoft Fabric. What additional items you need to consider while you are working with Microsoft Fabric. We will go through different components of Fabric including Synapse Pipelines, Data Warehouse, Lake house and so on.

Prior knowledge with cloud based ETL e.g. Azure Data Factory or Synapse Analytics will assist but not required to join the session.

Empowering organizations through self-service Data Engineering

In the world of data and analytics, self-service analytics tools like Power BI and Tableau are often the go-to solutions. However, as the data and analytics landscape evolve with the proliferation of low-code and no-code tools and the integration of AI, the demand for self-serve data engineering capabilities in the industry is on the rise.

OMERS as a Canadian pension plan distinguishes itself as an industry pioneer, not only embracing but also delivering self-serve Data Engineering capabilities to empower the organization by using Microsoft Data and AI technologies, including Microsoft Fabric. The session will explore strategies for empowering organizations with self-service Data Engineering capabilities, discussing both their benefits and limitations, along with effective methods to overcome challenges. Additionally, we'll delve into the circumstances where enabling self-service data engineering capabilities is most advantageous, leveraging tools such as Microsoft Fabric

Bridging Azure and Snowflake: Seamless Data movement with Microsoft Fabric

In today’s hybrid data landscape, businesses frequently navigate across diverse platforms for optimal performance. If your organization operates within both Snowflake and the Microsoft data stack, you may encounter the necessity for effortless data transfers between Azure Data Lakehouse and Snowflake Data Warehouse.

The demo-driven session will showcase how you can copy data between Azure Data Lakehouse and Snowflake using Microsoft Fabric. It will also demonstrate the basic components of Snowflake and Microsoft Fabric. Additionally, it will touch upon Mirroring Snowflake, which is currently in preview.

Modern Enterprise Data Strategy in the Era of GenAI

In a world increasingly shaped by AI agents and generative AI, organizations must rethink their enterprise data strategies to stay competitive. As the leader of the Enterprise Data Platform team in our organization, I have spearheaded a program to establish a future-proof data strategy that ensures organizational data remains safe, secure, and compliant. I will share my experiences with designing and implementing this strategy, including the challenges faced, lessons learned, and key successes that have positioned the organization for long-term success in an AI-driven world.
The session will provide actionable insights into aligning data architecture, governance, and culture to set the foundation for a modern enterprise data strategy. From integrating AI agents into your workflows to redefining your approach to data democratization, discover practical strategies to unlock the full potential of your enterprise data in this AI-driven age.