<p>
    <a href="https://datadrivencommunity.com/FutureDataDriven2024.html" target="_blank">Future Data Driven Summit 2024</a>&nbsp;is one of the largest FREE IT Conferences in the Data Community focusing on Data Platform, AI, Business Intelligence, Business Applications, Power Platform, and Analytics. IT Decision Makers, Developers, Business Analysts, IT Professionals, BI Managers, BI Professionals, Database Administrators, Architects, Digital &amp; Big Data business leaders.
</p>
<p>
    <b>Why Future Data Driven:</b>&nbsp;It is a great opportunity to learn from SQL Server Experts, Microsoft MVPs, SQL Server Authors, and Professionals who have been through and can relate to the obstacles you have day to day. This one day training event is unlike any other providing free training and networking.
</p>
<p>
    Don’t miss out on the benefits of early registration. Secure your spot on our special list and stay updated with all the latest news via email.&nbsp;<a href="https://datadrivencommunity.com/fdd2024registration.html">https://datadrivencommunity.com/fdd2024registration.html</a>
</p>
<p>
    <b>When:</b>&nbsp;September 25 2024,
</p>
<p>
    <b>Cost:&nbsp;</b>FREE
</p>
<p>
    <b>Where:&nbsp;</b>Live Stream Event
</p>
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Future Data Driven Summit 2024

Room v3

Join Tzvia Gitlin Troyna for a transformative session that explores the cutting-edge capabilities of Real-Time Intelligence in #MicrosoftFabric. This session will share all the great new capabilities that Fabric Real-Time analytics supports, revolutionizing the handling of events and time-based data. From ingestion to transformation and analysis, discover how Fabric provides an end-to-end solution that empowers you to harness the full potential of your data in real-time.

We will demo an end-to-end experience from Eventstream to Eventhouse and Data Activator, showcasing how real-time analytics isn't just about real-time but also about time-based streams. Additionally, we will share real customer stories that demonstrate how RTI provides more capabilities for both professional data engineers and citizen data users, enhancing efficiency and effectiveness.

Don't miss this opportunity to learn about the latest advancements and how they can benefit your organization

Transforming Real-Time Intelligence with Microsoft Fabric

LinkedIn

Delta has become a widely used tool by data professionals to build effective and reliable Lakehouse’s.  Yet, questions arise regarding its performance with large datasets, its ability to handle skewed data, and its concurrent write management. In this session, will dive deep into optimization options and methods that will improve your Lakehouse performance.

Delta files are not ordinary data files but are key in making Lakehouse efficient, optimal, and scalable.  However, optimizing delta files and tables in Databricks can be challenging and even a daunting task.  Techniques like partitioning and z-ordering can be limited, inflexible, and challenging to implement, especially when your data is constantly changing or growing.
This session will introduce you to the new liquid clustering technique, a cutting-edge approach that is more flexible and adaptable to data layout changes. This will not only enhance your query performance but also simplify your optimization process. 
Furthermore, we will explore various other Delta file optimization techniques, such as data skipping, z-ordering, and vacuuming in Databricks. These techniques will help you maximize the value of your Delta files while minimizing resource utilization and costs.
By the end of this session, you'll have the necessary knowledge and tools to optimize Delta files and tables for your own Lakehouse. 

Quest to Delta Optimisation

X (Twitter)

Terraform lowers the bar to entry for adopting Infrastructure as Code. However, to really get the most out of it we need to look at more advanced patterns and practices to really operationalise it and realise the value when managing infrastructure at scale.

In this session we will look at how to leverage some of the more advanced features of terraform by building our own reusable  modules. As well as built in functions and techniques to ensure a maintainable codebase. Finally, looking at how to automate deployments as part of a wider platform deployment including databases and application code in Microsoft Azure.

Defining and Deploying a Data Platform with Terraform.

As a Microsoft SQL Server DBA, monitoring and analyzing your server’s performance and troubleshooting issues is essential. One of the most effective ways to do this is by utilizing the built-in data collection, which records a wealth of information.
In this session, we will explore six collections (Logs and traces) that can provide valuable insights into your server’s configuration, health, and performance.

• Default trace
• SQL Error log
• SQL Agent Error log
• Cluster log Always On availability group
• AlwaysOn_health
• System_health

I will show you each one's default location, retention, and content captured. We will discuss how to access and interpret these logs and demonstrate how they can be used to identify and diagnose issues such as failed logins and deadlocks, the health of the Windows cluster and availability group, and schema changes. By effectively utilizing the SQL Blackbox, you can ensure the smooth operation of your server and maintain the highest performance and reliability.

Prerequisite: Familiar with SQL Server administration

SQL Server Detective: Investigating Logs and Traces for Optimal Performance

Delta Tables provide amazing out of the box features such as ACID Compliance and Time Travel to your datalake but there's a world of optimization beyond the default settings. 

This session is designed to take your Delta Lake to the next level. We'll start with a brief introduction to Delta Tables and quickly dive into advanced optimization techniques. 

We'll explore topics such as Delta Transaction Log retention, deletion vectors, liquid clustering, change data capture, and generated columns. 
 
Join me to unlock the full potential of your Delta Lake and make informed decisions that go beyond just leaving things at their defaults.


Optimizing Your Delta Lake: Beyond the Defaults

Discover the power of Azure AI Studio for full lifecycle development of generative AI applications using your own data. From prompt engineering to deploying copilots, Azure AI Studio offers a unified platform equipped with pre-built Azure AI skills, multi-modal application development, and advanced evaluation tools.

Why You Should Attend:

Discover how Azure AI Studio provides a centralized environment for prompt engineering, enabling seamless integration of language, vision, and speech capabilities into your AI applications.

Deploy an Azure OpenAI Model and Chat with Your Data: Explore the deployment of an Azure OpenAI model and engage in insightful conversations with your company's data, laying the groundwork for copilot training.

Custom Orchestration with Prompt Flow: Gain insights into the custom orchestration capabilities of Azure AI Studio's prompt flow tool, empowering you to guide the behavior of your applications to better fit your specific use case requirements.

Deploy the Flow for Consumption: Take the final leap by deploying your well crafted copilot flow for consumption, empowering your company with an AI-driven assistant ready to enhance customer interactions and streamline operations.


Azure AI Studio: Orchestration, Prompt Flow and Copilots

Twitter

Join me for an enlightening session as we delve into the revolutionary world of Microsoft Copilot Studio. In this session, we will explore the cutting-edge capabilities of Copilot Studio, Microsoft's groundbreaking AI-powered Copilot Studio, designed to enhance organization bots and streamline the Bot development process.

Throughout this interactive session, participants will learn:

- Introduction to Copilot Studio: Gain a comprehensive understanding of Copilot Studio and how it empowers developers to create personalized coding assistants. Learn about the underlying AI technologies and the philosophy behind Copilot Studio's design.

- Designing Your Assistant: Explore the intuitive interface of Copilot Studio as I walk you through the process of designing your assistant. From defining user preferences to integrating data sources, discover how to tailor your assistant to suit your's org requirements.

- Training Your Assistant: Dive into the training process as I will demonstrate how to train your assistant to understand context, identify patterns, and generate relevant prompts using Topics.

- Advanced Features and Use Cases: Delve deeper into advanced features and use cases of Copilot Studio, such as collaboration tools, and plugin development. Gain insights into how developers will create Bots to not only unified search engine but also accelerate their workflows and unlock new possibilities.

By the end of this session, you will be equipped with the knowledge and tools to embark on your journey of building and customizing your own Copilot-inspired assistants with Copilot Studio. 

Exploring the Future of Coding Bots: Introducing Microsoft Copilot Studio

How well do you really understand data security, and are you thinking of the impact artificial intelligence (AI) has on it? Data is data regardless of where you put it, and data security is still data security, even as we explore AI’s role in data. As business leaders and security experts, our muscle memory reaction is built around traditional methods such as encryption and data masking. However, there’s a better road to increased business value and secured data in the age of AI. Some of the largest names in data security are still missing this fundamental concept, but as data leaders, we can’t continue to afford these levels of misunderstandings if we’re to leverage AI effectively.  

Anthony Cammarano will discuss these data security misunderstandings in an age of AI and educate the audience on key concepts such as:  

The rise of Large Language Models (LLMs) creates more risk and exposure of sensitive personal identifiable information (PII). By connecting sensitive data to these pipelines, you’re removing the existing data controls in place and oftentimes granting full and clear access to that data. In other words, you can no longer restrict access only within the data store. More data sharing means more exposure and more risk.  

Generative AI (GenAI) increases the surface area for misunderstandings in data security. Access and masking aren’t enough to protect data in these AI models. If you’re deploying data controls in transit and at rest, what happens while it is in use? We are just beginning to understand the data flow associated with these models, along with the stages of AI development and deployment that each carry unique risks at their respective levels.  

There is more nuance to data security and protection than ever as we explore AI’s role across tech stacks. By discussing existing misunderstandings and pitfalls in data security, we can begin to uncover better business value in AI without compromising sensitive information.  

Your Data Security Isn’t Enough for AI – Yet

Event-driven paradigm has been more and more popular thanks to serverless solution able to catch process and scale according to the event.

But when you have a serverless data warehouse, such as BigQuery on Google Cloud, how can you leverage event driven design to synchronize different sources in data mesh architecture? You have several solution and even an open source solution that I create and released this year!

Data platforms synchronisation journey at Carrefour

Organizations often face challenges converting raw data into valuable insights due to fragmented tools and teams. Microsoft Fabric provides a comprehensive solution that streamlines data science, engineering, and analytics. 

This session offers a practical introduction to Fabric's data science features, even for those without prior experience. Discover how to navigate the platform, utilize its tools, and create your initial machine learning model.

