Working Effectively While Remote

Years ago, working remotely was not an option and was practically unheard of in the corporate world. Even with connectivity through the internet, such remote connections were considered to be unique and transitory in nature. During COVID-19, remote work became mainstream, but now many companies are recalling their workforce back into the office. If you are working remotely and wish to remain so or not working remote and wish to begin, this short session will give you some tips and tricks to help make that happen.

Using Standards to Improve Communication and Development Success

Communication is critical to the success of any development project. This is especially true when the team is diverse in geography, time zones, cultures, technologies, and focus. Data and development standards allow teams to use the same “language” through shared terminology, expectations, and documentation. This is exacerbated when requirements are inconsistent, vague, incomplete, or simply non-existent.

Standards are the framework of a solid system architecture. This session will discuss the definition of standards, their use in data and development, and how they improve team effectiveness. We discuss how to keep standards viable, how to deal with exceptions, and when standards should be changed.

Tech Debt: Causes, Effects, and Solutions

Technical debt is a problem that everyone has and it is growing! While there are many causes, the effects are hard to attribute and the solutions are always elusive. Because the solutions usually involve time and resources, the ever growing mountain of tech debt never achieves the priority required to prevent it, let alone reduce it. Generally, this is because of a lack of understanding by upper management of the impact such tech debt has to daily operations, planned expansions, and the bottom line.

Join us in this session as we review the most common types of tech debt, how they occur, and what we can do to prevent it. In addition to slowing the growth of the mountain, We will also discuss some techniques that can help chisel away at the mountain itself.

How to Migrate from SQL Server to Postgres

Many who think of the database as merely a data container assume that moving from one to another is trivial. Although data lives in tables, it is visible through views, processed by procedures, transformed in triggers, and featured in functions. The logic in all these must also be translated to the new platform including:
• Data Types & Extensions
• Tables, Primary/Foreign Keys & Indexes
• SQL queries & Views
• PL/pgSQL in Stored Procedures & Functions
• Triggers & other Miscellaneous Items

Silent but Deadly -- Hidden SQL Performance Assassins

There are many current practices employed when developing queries, views, procedures, and functions that can affect performance. Yes, database engines can be tuned, indexes adjusted, and server settings tweaked, but none of them will overcome bad code. Often, habits and practices begin early in a career and tend to stick with us throughout all subsequent projects unless addressed. This includes:
• Improper selection criteria
• Inefficient joins
• Implicit conversions
• Using procedural processing instead of set-based methods

Surprisingly, the impacts from these practices impact many different platforms alike: SQL Server, Postgres, Snowflake, Redshift, etc. This session will cover the most common and most expensive performance issues found in code out in the wild and what you can do instead to make your code perform its very best!

Navigating the Database Landscape in 2026: The Fight for Control

As organizations have chased speed through AI, multi-platform estates, and Cloud, database complexity has outpaced the practices needed to manage it. Flexibility has increased, but oversight, confidence, and control have weakened.

So how do you regain control in increasingly complex database landscapes?

Join industry experts Kristyna Ferris, Joshua Higginbotham, and Aaron Cutshall in discussion with Redgate’s Louise Domeisen, to unpack the key findings from the 2026 State of the Database Landscape report.

You’ll hear first-hand experience and actionable tips from the panel on the key report topics including:
• The defining tension of 2026: organizations are losing control as everything accelerates.
• Structural complexity is rising again, making control harder than ever.
• AI adoption is exploding, landing on top of unstable data, security, and governance foundations.
• Risks are shifting from technology to ownership, structure, and decision-making.
• To regain control, organizations must fix the data foundations that everything else depends on.

You'll walk away with a clearer understanding of where your organization sits in this landscape and practical steps you can take to start regaining control.

A Postgres Developer's Snowflake Survival Guide

Snowflake is building up steam in the online database world! Because of your experience with Postgres, you are more prepared for Snowflake than you might imagine. This session will cover many features unique to Snowflake, highlight commonalities Snowflake has with Postgres, and point out several differences between them. From this session, you will gain the knowledge and confidence to leverage your experience with Postgres to tackle Snowflake.

A Practical Guide to Set-Based Queries

T-SQL queries, stored procedures, and poorly written functions are the main contributors to performance degradation in SQL Server. SQL Server is optimized for set-based processing over procedural processing. The sad reality is that too much code is written from a procedural point of view because many database developers started as procedural programmers. This session will examine what set-based queries are, how to identify inefficient procedural processes, and how they can be rewritten as efficient set-based queries.

How to Change SQL from Procedural to Set-Based

Most relational databases (like SQL Server, Postgres, etc.) are designed around processing data in sets. This is evident with the declarative nature of Structured Query Language(SQL). Yet, many developers need help transitioning from the procedural programming methodologies they learned in school or while working in procedural languages. Therefore, how can we turn database stored procedures and functions that were written procedurally into more efficient set-based processing? This session will review those issues and help identify helpful tips while working through a real-life example in Postgres.

An Enterprise Data Architecture Framework

One of the challenges facing enterprise architecture is maintaining consistency across the enterprise. This is challenging because data comes from disparate sources and systems representing different purposes, focuses, and objectives. On top of that, there needs to be more clarity regarding the terms Data Lake, Data Warehouse, Operational Data Store, etc. To overcome these challenges at an enterprise level, a framework is necessary to apply data uniformly, consistently, and meaningfully. The framework will transform data from multiple, disparate data sources into an operational data store, a consistent, homogeneous environment, as the single dependable source of truth for all reporting and analytics.

This session will present that framework and discuss the following:
• The challenges facing data analytics and reporting due to multiple disparate data sources
• An introduction to the various terms used today for data storage
• The purpose of an Operational Data Store and how it improves data usability
• The data zones for Raw, Refined, and Published data
• How data standards simplify and enhance data usability
• A method to provide primary and foreign keys across disparate data

Migrating AdventureWorks to Postgres

One of the advantages that SQL Server developers have enjoyed is a comprehensive sample database that touches on all aspects and operations of a database. That same sample database, AdventureWorks, is now available for Postgres! However, it is not just the data in tables but all views, triggers, procedures, functions, and other database objects. Data type differences, procedural differences, and others are highlighted and discussed. This session highlights several differences between SQL Server and Postgres using AdventureWorks as an example.

The Power of Window Functions

Window functions have nothing to do with the Windows operating system but provide a "window" in a data set when used in SQL queries. They are powerful, set-based methods to view data in unexpected ways. Window functions provide easy, set-based solutions to solve some common problems:
• Using running totals
• Performing operations on intervals
• Identifying data gaps and islands
• Performing aggregates without losing detail

Many people are confused by window functions and do not know how to use them properly. This session will explore window functions, how they work, and how to use them. Demonstrations with several examples will solidify how window functions can simplify queries and make them more powerful.

The Lost Science of Set Theory

Many database developers today do not have a Computer Science degree and may also have begun their career developing software using procedural programming languages (Java, C#, etc.). As a result, they may not have the background needed to conceptualize solutions in terms of sets of data and therefore may not be able to develop efficient set-based queries. In this session, we will review the basics of set theory, relational algebra and how they apply to database development to turn cursors, loops, and other procedural programming practices into efficient set-based operations that make the most use of a relational database engine.

Tally Ho! — Explore the Varied Uses of Tally Tables

Relational databases are designed to operate efficiently with set-based queries; they do not perform as well with loops and cursors. However, there are situations where you need a loop of some fashion. Tally tables give you the best of both worlds by allowing you to effectively “loop” through records in a set-based manner. We’ll explore what tally tables are, how they work, and, more importantly, review some of the many ways you can use them to turn your loops and cursors into efficient set-based operations.

SQL Team Six: How to Build Effective Teams

Teamwork is important in all areas, including development, QA or other teams that we interact with daily. Lessons learned from highly effective teams show that there are six major impacts to team effectiveness: chain of command, team cohesion, standard operating procedures, training, mission objectives and after action analysis. A failure in any of these areas can impact team effectiveness. In this session, learn what can improve or destroy team effectiveness and what you can do about it.

This session describes the attributes of successful leadership and team effectiveness, highlights the issues that can cause their downfall, and provides steps to improve them.

How to Give a Technical Presentation

Most people don’t like to speak in public and technical folks are certainly no exception. Yet, you’ve got some ideas for a great presentation but just don’t know how to go about putting it all together. On top of that, how do you go about giving the presentation itself? This session will cover how to pull your material together in an organized fashion and present it such that your audience (both in person and virtual) can follow along and get the message you want to relay. We’ll also discuss how to deal with issues that cause presenters stress to help you to make the process enjoyable and rewarding for all.

Defining What’s Normal — The Basics of Database Normalization

Determining how to efficient design database structures for a given application has always relied on the same old answer: “It depends!” So, how do you determine what level of normalization your data requires? This session will review the principles of data normalization, show the impact that normalization can have on performance and data integrity, and just as importantly, show you when it’s OK to break the rules and denormalize. We will cover some case situations where it’s better not to be normal!

SQL Team Six: How to Build Effective Teams (Workshop)

Teamwork is essential in all areas of our work life, including how we interact with other teams daily. Lessons learned from highly effective teams, such as SEAL Team Six, show six significant impacts on effectiveness:
• Chain of Command
• Team Cohesion
• Standard Operating Procedures
• Training
• Mission Objectives
• After-Action Analysis

Failure in any of these areas can impact team effectiveness. This workshop explores these six areas to understand what can build or destroy team effectiveness. The exercises and discussions teach several techniques that will enable you to become better leaders, build better teams, and be more effective team members.

Each attendee will walk away with a better understanding of the six significant impacts on team effectiveness and how they can affect change to improve each impact. The discussions and exercises in this session apply to both leaders and team members. The knowledge and skills gained can be directly used for an immediate impact.

Data Governance Begins with Data Architecture

Most organizations who successfully recognize a need for a data governance program do so after the fact -- after all critical source systems are in operation. They may feel they are done once they have a data catalog in place and their data governance goals have been met. However, proper data governance is not just cataloging data assets. Having the catalog on the virtual bookshelf does not do anyone any good, regardless of how much attention is given to it. Proper data governance is proactive and guides data projects before, during, and after implementation. In most industries, it is essential. In healthcare, it is critical! It all begins with data architecture before systems are designed or purchased. This session will address many of the questions you have:

• Who Should Be Involved?
• What Is Data Governance?
• When Should Data Governance Begin?
• Where Is Data Governance Needed Most?
• Why Begin with Data Architecture?
• How Do I Get Started?

Learn what data governance is and how to do it initially and during all data projects instead of only at the end. Leverage your data assets to support compliance and reporting requirements.

Leadership Essentials for Data Teams

Most people think that leadership is about solving problems. However, leadership isn't just about having power, authority, and making the big decisions. It's about taking ownership and responsibility for the consequences of those decisions and being accountable for how you will respond to problems that arise.

On top of that, leaders aren’t just judged by what they do, but also by what their people do. Leading a data team presents further unique challenges as most data teams consist of people from widely different backgrounds, skills, aptitudes, and attitudes. Plus, todays data teams are often scattered across multiple time zones, geographies, and languages. This session addresses the primary principles of leadership plus tips on how to:
• Handle Personality Conflicts
• Deal with Incomplete or Missing Requirements
• Enforce Standards & Documentation
• Foster Growth & Cohesion

If you lead a data team or want to, this session is for you!