How do you efficiently scale your analytics stack when your data and data team grows 10x in 2 years? How do you even start prioritizing what gets done when there's that much growth? In this talk, Felipe Leite and Stephen Pastan of Miro unpack their shift to a Modern Data Stack and share the vital technical changes they made to build a scalable and tech-forward data stack. Come join them in learning how they got to where they are today and what they’re working on for the future. More details coming soon!

Check the slides here: https://docs.google.com/presentation/d/1lLoRBYAv8wlJQuhSrflX4F6y4lqV3SnDNAU7BYxHYR8/edit#slide=id.p

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

In a popular Coalesce 2020 talk, Dave Fowler challenged the relevancy of dimensional modeling and the star schema popularized by Ralph Kimball over 25 years ago, arguing the dimensional modeling method now does “more harm than good,” in the context of the modern data stack. But should we throw the baby out with the bathwater? In this talk, Josh Devlin and Sydney Burns (Brooklyn Data Co) suggests a different approach to bringing Kimball’s system into the modern era.

Check the slides here:https://docs.google.com/presentation/d/1HLP1FfCNZJUIF7JgT1ote5LaG2tDvsNRfrA9vIkf2n4/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Everyone is talking about data lineage these days, and for a good reason. Data lineage helps ensure better data quality across your modern data stack. But not everyone speaks the same lineage language. Data engineers use lineage for impact and root cause analysis. Analysts and Analytics engineers use lineage to trace jobs and transformations in their warehouses. And consumers use lineage to understand why data never reached their expected destination. This results in a narrow, siloed view lineage in which only one group benefits. It’s time to stop using siloed lineage views for pretty graphs and start using end-to-end lineage to drive focused actions. In the talk, you will learn:

• How data quality tailors to specific needs of data engineers, analysts, & consumers

• How data lineage should drive actions

• A real-world example of end-to-end data lineage with Airflow, dbt, Spark, and Redshift

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

dbt’s powerful capabilities allow data teams to deliver data products and analytics solutions to solve business problems faster than ever. Yet still, even with the best modern technologies, challenges arise. How can you be certain what your building will stand up to changing requirements? How can you connect disparate parts of your business to derive new insights? The answer may be a blast from the past—but the fundamentals never change. Learn how to apply fundamental techniques—like dimensional modeling—to modern tools, helping you to build scalable and reusable solutions to solve data problems today, and in the future.

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

The Modern Data Stack is becoming more and more fragmented. With new tools and processes popping up continuously, it’s easy to get stranded on various “data islands”, with everything running independently. In this session, we’ll teach you:

• What benefits you gain by turning your Modern Data Stack into an Integrated Data Stack

• How Shipyard can help you quickly connect the data tools you already use

• How orchestration is the missing step in your data journey to get your team off “data islands”

• How dbt fits into the picture of a connected data stack

Check the slides here: https://docs.google.com/presentation/d/1NT7RnMtTLxb5ew5_VXXzciJusfbBKZJx86B6BtNZv90/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Lineage is a critical component of any root cause, impact analysis, and overall analytics heath assessment workflow. But it hasn’t always been easy to create, particularly at the field level. In this session, Mei Tao, Helena Munoz, and Xuanzi Han (Monte Carlo) tackle this challenge head-on by leveraging some of the most popular tools in the modern data stack, including dbt, Airflow, Snowflake, and ANother Tool for Language Recognition (ANTLR). Learn how they designed the data model, query parser, and larger database design for field-level lineage—highlighting learnings, wrong turns, and best practices developed along the way.

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

In this live, instructor-led hands-on lab, you’ll learn how to build a modern data stack with Databricks and dbt, using dbt to manage data transformations in Databricks and perform exploratory data analysis on the clean data sets using Databricks SQL. Based on the lakehouse architecture and built on an open data lake, data analysts, analytics engineers, and data scientists can use dbt and Databricks to work with the freshest and most complete data, and quickly derive new insights for accurate decision-making.

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

The products that make up the “modern data stack” have all grown to prominence over the past decade. In this heady time, so much has changed about how data work is done.

But some of the “rules of engagement” that defined the original modern data stack are starting to break down. As a result, big changes are coming for the data tooling ecosystem.

The end result? Better, more integrated tooling, used by more humans inside of every company, that actually understands the data that it is operating on.

This modern data stack—if we still want to call it that!—will be unrecognizable to its former self.

Check the slides here: https://docs.google.com/presentation/d/1G0c3w19AwBEWEzyd9vwTKK5zMvXR76-NPQn6x0xZoSg/view

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Got your Modern Data Stack setup, now what? A mature data practice goes beyond setting up the data pipeline, and ensures there are both systems and processes in place to make it easy for everyone to find and understand data. At Select Star, we work with many organizations to enable data discovery, so the “tribal knowledge” of data is searchable and understandable for everyone. In this session, we’ll share the best practices and change management tips for setting up a data discovery portal and making it the single source of truth of data for your business.

Check the slides here:https://docs.google.com/presentation/d/1F3CPBhWenf2jt5hmXrhXvOBe5wei6hcLUj95jZtVZEw/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

How do you support exponentially growing companies without breaking as a data team? The answer is increasing your leverage with tools and processes. This session centers around four principles to achieve this goal: 1. don’t reinvent the wheel, 2. make your own job easier, 3. save time for innovation, and 4. invest in onboarding.

First, the first data leader at Vendr, the SaaS buying platform with customers like GitLab, Brex, and The Washington Post, will share his learnings on building a stack and team that scaled as the company grew 10x from 30 to 300 employees in under two years.

Second, we’ll give a demo of how Metaplane pulls lineage and metadata from a modern data stack that is centered around dbt. By the end of the demo, you’ll know how to setup tests, extract lineage throughout your data stack, and triage data quality alerts.More details coming soon!

Check the slides here: https://docs.google.com/presentation/d/15dQJIGeGhG0WGO6MLXtxWhmf8neY-u0c8ZLRG9GJB-s/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Academia/open science is an as-yet untapped market for analytics engineering, as well as one that could majorly benefit from the tight coupling of data transformation and software engineering best practices. But introducing dbt into this context comes with its own set of challenges. In this session, Šimon Podhajský (iLife Technologies), explains what’s slowing progress here,, and what academics can do to progress this work.

Check the slides here: https://docs.google.com/presentation/d/1aw_cs6V0n-oT9Lp7Vq3MNcRbthEFJEYwcvkCBfuzlR0/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Pulling data directly out of application databases is commonplace in the MDS, but also risky. Apps change quickly, and application teams might update database schemas in unexpected ways, leading to pipeline failures, data quality issues, data delivery slow-downs. There is a better way. In his session, Charlie Summers (Merit) describes how their organization transforms application event streams into analytics-ready tables, more resilient to event scheme changes.

Check the slides here:https://docs.google.com/presentation/d/1K5PcoVshiHKZs_xI3K4P5JRNYTkbmnQJPMl8NmBlGfo/edit

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

The opportunities for AI and machine learning are everywhere in modern businesses, but today's MLOps ecosystem is drowning in complexity. In this talk, we'll show how to use dbt and Continual to scale operational AI — from customer churn predictions to inventory forecasts — without complex engineering or operational burden.

Check the slides here: https://docs.google.com/presentation/d/1vNcQxCjAK4xZVZC1ZHzqBzPiJE7uwhDIVWGeT9Poi1U/edit#slide=id.g15b1f544dd5_0_1500

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Data apps are the next wave in analytics engineering. The explosion of data volume and variety combined with an increasing demand for analytics by consumers, and a leap in cloud data technologies triggered an evolution of traditional analytics into the realms of modern data apps. Question is: How do you prepare for this wave? In this session we’ll explore real-world examples of modern data apps, and how the modern data stack is advancing to support sub-second and high concurrency analytics to meet the new wave of demand. We will cover: performance challenges, semi-structured data, data freshness, data modeling and toolsets.

Check the slides here: https://docs.google.com/presentation/d/1MC18SgT_ZHOJePjYizz_WT7dVveaycNw/edit?usp=sharing&ouid=110293204340061069659&rtpof=true&sd=true

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

The "socio" is inseparable from the "technical". In fact, technological change often begets social and organizational change.

And in the data space, the technical changes that some now refer to as the "modern data stack" call for changes in how teams work with data, and in turn how data specialists work within those teams. Enter the Modern Data Team.

In this talk, Abhi Sivasailam will unpack the changing landscape of data roles and teams and what this looks like in action at Flexport. Come learn how Flexport approaches data contracts, management, and governance, and the central role that Analytics Engineers and Product Analysts play in these processes.

Check the slides here: https://docs.google.com/presentation/d/1Sgm3J6EkeKQf5D1MKopsLLAMOhAZ05CxDlei2mbDE90/edit#slide=id.g16424dcc8d3_0_1145

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

The real world is unreliable. Planes take off late, trains leave early, and cars break down. Sometimes, we need to get data from a source without a standard connector. Sometimes, a schedule really doesn't cut it. In this talk, we'll build a pipeline that responds to events to ensure that data is delivered quickly and reliably. We'll also ensure it can handle failure and keep bad data from clogging the plumbing.

Check the slides here: https://docs.google.com/presentation/d/1W9p7H4l0fUr7iAJ3GxEGUTmWGtmc_iu02N-MKb2BSFM/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.