Building Data Teams Benefits of cloud migration for the modern data team Kira Furuichi on May 18, 2023 May 18, 2023 Kira Furuichi We're talking about the benefits of cloud migration—all the nitty-gritty on cost savings, security concerns, governance abilities, & scaling your data work.
Building Data Teams 4 cloud migration challenges and realistic solutions Kira Furuichi on May 16, 2023 May 16, 2023 Kira Furuichi Migrating to the cloud comes with *real* challenges. We're unpacking what those cloud migration challenges are and offering pragmatic solutions.
4 data modeling techniques for modern data warehouses Kira Furuichi on April 17, 2023 April 17, 2023 Kira Furuichi Explore the data modeling techniques (relational, ER, dimensional, and data vault) that data teams use to model their data and create actionable insights.
Creating a data quality framework for scale Kira Furuichi on April 5, 2023 April 5, 2023 Kira Furuichi A data quality framework develops trust between your team and the business and establishes a system of governance and accountability for your data quality.
Data transformation process: 6 steps in an ELT workflow Kira Furuichi on March 27, 2023 March 27, 2023 Kira Furuichi The data transformation process can be broken down into six steps: extraction and loading, exploration, transformation, testing, documentation, and deployment.
The 5 essential data quality checks in analytics Kira Furuichi on March 27, 2023 March 27, 2023 Kira Furuichi Foundational data quality checks you should be running on your data cover the concepts of uniqueness, non-nullness, acceptance, referential integrity, and freshness.
Data quality testing: Where and why you should have it Erin Vaughan, Kira Furuichi on March 24, 2023 March 24, 2023 Erin Vaughan, Kira Furuichi Data quality testing is the practice of using code-based and automated data quality tests to know whether these assertions you make about your data are...
Data quality dimensions: Tackling data quality with intentionality Kira Furuichi on March 23, 2023 March 23, 2023 Kira Furuichi Data quality dimensions create a general profile of your data's quality. How you define what "good" data quality is depends on how that data is...
ETL vs ELT: Unpacking the key differences Kira Furuichi on March 15, 2023 March 15, 2023 Kira Furuichi The main differences between ETL and ELT lie in when and where data transformation occurs—changes that might seem small but come with big implications!
Community News 0-to-published in 6 weeks David Krevitt, Jason Ganz, Kira Furuichi on January 30, 2023 January 30, 2023 David Krevitt, Jason Ganz, Kira Furuichi A technical writing mentorship program for the dbt Community, sponsored by dbt Labs.
Opinion Coalesce 2022 from 5 perspectives Amada Echeverría, David Krevitt, Ian Fahey, Julia Schottenstein, Kira Furuichi, Sung Won Chung on November 15, 2022 November 15, 2022 Amada Echeverría, David Krevitt, Ian Fahey, Julia Schottenstein, Kira Furuichi, Sung Won Chung Read this blog post to learn about the five important perspectives gained from Coalesce 2022.
Company News Coalesce 2022: Driving value for the data team and beyond Kira Furuichi on August 23, 2022 August 23, 2022 Kira Furuichi October 17-21, 2022: Coalesce is back and in-person! With 100+ speakers and sessions, 3 global locations and a virtual option, it’s a week you’re not...
How-To Data lessons learned from benchmarking the IDE’s performance Andrew Escay, Kira Furuichi on August 1, 2022 August 1, 2022 Andrew Escay, Kira Furuichi This piece is about how direct collaboration with engineers for event tracking is the best axe to wield in product analytics, and how our data...
Orchestrating my day — Ian Fahey, Analytics Engineer at dbt Labs Ian Fahey, Kira Furuichi on July 13, 2022 July 13, 2022 Ian Fahey, Kira Furuichi This post is part of our “Orchestrating my day” series where data folks walk us through their daily experiences.
The STAR dbt macro Kira Furuichi on July 13, 2022 July 13, 2022 Kira Furuichi The STAR dbt macro generates a a comma-separated list of all fields that exist in the `from` relation and excludes any fields listed in an...
DATE_TRUNC SQL function — Why we love it Kira Furuichi on July 5, 2022 July 5, 2022 Kira Furuichi The DATE_TRUNC function will truncate a date or time to the first instance for a given date part maintaining a date format.
DATEDIFF SQL function — Why we love it Kira Furuichi on July 5, 2022 July 5, 2022 Kira Furuichi The DATEDIFF function will return the difference in specified units (ex. days, weeks, years) between a start date/time and an end date/time. It’s a simple...
How-To How dbt Labs' data team manages OKRs Erica Louie, Kira Furuichi on July 5, 2022 July 5, 2022 Erica Louie, Kira Furuichi dbt Labs recent underwent a massive overhauling of our OKR framework. Erica Louie, Head of Data, shares how we think about OKRs and a solution...
COALESCE SQL function — Why we love it Kira Furuichi on June 29, 2022 June 29, 2022 Kira Furuichi The COALESCE SQL function is an incredibly useful function that allows you to fill in unhelpful blank values that may show up in your data....
EXTRACT SQL function — Why we love it Kira Furuichi on June 28, 2022 June 28, 2022 Kira Furuichi Deep dive into the EXTRACT function, how it works, and why we use it. The EXTRACT function allows you to extract a specified date part...
LOWER SQL function — Why we love it Kira Furuichi on June 28, 2022 June 28, 2022 Kira Furuichi The LOWER SQL Function allows you to return a string value as an all lowercase string. It’s an effective way to create consistent capitalization for...
Orchestrating my day: Erica Louie, Head of Data at dbt Labs Erica Louie, Kira Furuichi on June 28, 2022 June 28, 2022 Erica Louie, Kira Furuichi Erica Louie, Head of Data at dbt Labs, walks us through her typical daily routine, challenges, and workflows.
How-To How dbt Labs' data team approaches reverse ETL Brandon Thomson, Kira Furuichi on June 28, 2022 June 28, 2022 Brandon Thomson, Kira Furuichi This playbook dives into how dbt Labs thinks and implements reverse ETL workflows for our internal analytics work.
