GlossGenius’ Post

Are you setting up your dbt data platform like Katie Bauer did? In her blog post, she hits on all the things Datacoves does (they are not a customer, but have a very similar setup) VS Code "extensions such as Jinja syntax highlighting, Easier git file exploration, SQLFluff and yaml linters." and a few others on Datacoves to improve productivity Airflow "is constantly helping us glue together services and processes from the data team, feeding ingestions, transformations and even data exports to other services, enhancing our overall efficiency." Datacoves saw this need from the start because complexity is inherent in most orgs. Our customers kick off Glue Jobs, Fivetran, Airbyte, StreamSets Inc., Azure Data Factory, Databricks notebooks, custom python scripts, etc. Oh and by the way, your pipelines don't stop at Transformation. Datacoves also helps companies set up Slim CI and Blue / Green deployments in their CI of choice (Github Actions, Gitlab, Jenkins, etc). There's no lock-in. People use Datacoves because they can implement quickly and they don't have to worry about managing a platform. Kudos to the GlossGenius team for making this happen, it is not simple. Understanding that tools alone are not the answer is also key in how they work. Are you thinking of setting up your dbt data stack? Talk to us, you will find we save you time, headaches, and money. Most importantly, we are in it to make you successful, if you find we are not for you, you can still do it all on your own, we use the same tools you can use. It's your repo, it's your process, it's your platform. Datacoves is just here to simplify things. https://lnkd.in/gsPgnzry

I hear from many companies that say they want to improve their business-making decisions but don’t feel they have the right data. This is fundamentally a process problem. Different teams have different tools to answer the SAME questions 🤔 ⛔. dbt Labs commissioned Forrester to conduct a Total Economic Impact (TEI) study on the value of dbt Cloud. They found that prior to dbt Cloud, organizations had: 🚩 lack of consistency in data transformations 🚩 erroding trust of data across the org 🚩 extensive data rework among engineers 🚩 missed deadline around data-driven initiatives After adopting dbt Cloud, these organizations saw: ✅ Accelerated data development productivity by 30% ✅ $1M+ in avoided data transformation costs of poor data quality ✅ Over 60% time savings on data rework leading to $2M+ in productivity gains Overall, these organizations saw a payback period of 6 months and a 3-year ROI of 194% 📈 🤝 Take a peek at the full report here ➡️ https://lnkd.in/gBjahFVW

If one of your 2024 goals is to eliminate time spent on data pipeline maintenance- allow us to help you 🙌 In our latest case study, we walk you through how Fundrise used dbt Cloud to achieve: ✅ >50% reduction in time to introduce new data sources ✅ 0 time spent on data pipeline maintenance Get all the details, below ⬇️

Join Nasdaq, dbt Labs, and Amazon Web Services (AWS) as we kickoff #awsreinvent2023 with this morning mixer on Nov 27th and discuss Nasdaq's journey to analytics nirvana with #amazonredshift and #dbt.

Over the past couple of years, dbt Labs has made dbt Cloud better and better. I am certainly in the 'Cloud' camp myself, but I have used dbt Core as well, and have found it to be a powerful tool. Check out this article written by Ryan Murphy that details some of the key differences between Cloud and Core, as well as some of the situations where you might want one over the other. #dbt #ClymOn #analyticsengineering #dbtcloud #dbtcore

Check out my blog post on how to choose between dbt Core & dbt Cloud and all the new & exciting dbt Cloud features! #dbt #ClymOn #analyticsengineering #dbtcloud #dbtcore

Building a strong data quality framework is essential to ensure trust in your data and to help catch issues before they impact stakeholders, in this blog Matt Winkler outlines a great framework for testing data in dbt Labs dbt Cloud, including CI/CD, unit testing, source, output testing and more. Read more: https://lnkd.in/ggx4DxQq

We’re excited to see the improvements dbt Labs have made to dbt Cloud! Combining Fivetran and dbt is a lightweight, low-cost way to build a powerful data infrastructure for your startup or e-commerce business. dbt Explorer will be an interesting addition — a move into the data catalog space, which is becoming increasingly important as businesses connect their data assets to LLMs. —— Give a 👍 if you’re an e-commerce company tired of spreadsheets and interested in up scaling your data infrastructure.

Check out Purple's strides with dbt Cloud ☁ 20% less financial data inconsistency 60% fewer support requirements 80% quicker response times to data requests Interested in dbt Cloud's benefits? Feel free to reach out or visit our website for a demo and to chat with the team. Here's more about Purple's success 👇

🚀 Just Published: "Building a Cloud-Based Data Pipeline" 🚀 Thrilled to share a blog post on "Building a Cloud-Based Data Pipeline"! 🌐 If you're interested in unlocking the power of the cloud for data processing, this read is for you. #DataPipeline #CloudComputing #DataEngineering #BlogPost #CloudTechnology #DataDrivenDecisions