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Barr Moses
Barr Moses

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Published in Towards Data Science

·Pinned

What’s Next for Data Engineering in 2023? 7 Predictions

What’s in store for the future of data engineering? In this article, I share some of my topline predictions for 2023 — and beyond. End of the year prediction articles are hokey, but they serve a purpose. They help us rise above the daily grind and consider where to place our longer term bets. They also tend to be an exercise in humility as we try to paint a coherent “big picture” of an…

Data Science

8 min read

What’s Next for Data Engineering in 2023? 7 Predictions
What’s Next for Data Engineering in 2023? 7 Predictions
Data Science

8 min read


Published in Towards Data Science

·Dec 22, 2022

6 Reasons Why Companies Fail at Data Governance

And how to avoid falling into the same traps — Everywhere we go in the cloud data space today, we’re hearing one message loud and clear: “you should be thinking about data governance”. It’s a sentiment that we wholeheartedly endorse, but we like to take it a little bit further — you should be thinking about data governance differently. In…

Data Governance

8 min read

6 Reasons Why Companies Fail at Data Governance
6 Reasons Why Companies Fail at Data Governance
Data Governance

8 min read


Published in Towards Data Science

·Oct 17, 2022

The Fight for Controlled Freedom of the Data Warehouse

The data gatekeeper is dead, long live the…oh no what have we done? — A silent alarm rings in my head whenever I hear someone utter the phrase, “data is everyone’s responsibility.” You can just as easily translate this to mean that “data is no one’s responsibility,” too. This, readers, is what I call the “data tragedy of the commons.” Here’s why. The term…

Data Quality

6 min read

The Fight for Controlled Freedom of the Data Warehouse
The Fight for Controlled Freedom of the Data Warehouse
Data Quality

6 min read


Published in Towards Data Science

·Sep 8, 2022

Can You Out-Architect Bad Data?

Even with the most well-designed data platforms, systems will break. Without embracing risk, you’re playing with fire. — Say it with me: broken data is inevitable. It doesn’t care about how proactive you are at writing dbt tests, how perfectly your data is modeled, or how robust your architecture is. The possibility of a major data incident (Null value? Errant schema change? Failed model?) that reverberates across the…

Data

10 min read

Can You Out-Architect Bad Data?
Can You Out-Architect Bad Data?
Data

10 min read


Published in Towards Data Science

·Jul 16, 2022

How to Set KPIs for Your Data Team

Or, defining what success looks like for data leaders — As analytics professionals, we deal in data: serving ad-hoc reports on a minute’s notice, pulling queries for executives, and generally forecasting company performance across a variety of metrics. But how can we be truly successful if we don’t measure our own performance, too? In this article, we discuss six important…

Data Analysis

10 min read

How to Set KPIs for Your Data Team
How to Set KPIs for Your Data Team
Data Analysis

10 min read


Published in Towards Data Science

·Jul 14, 2022

Is “Self-Service” Data’s Biggest Lie?

Self-serve systems are a big priority for data leaders and a principle of nearly every modern data strategy, but what exactly does it mean? — Data self-service, the ability for stakeholders in the organization to answer their own business questions with data, is a top initiative for nearly every data leader I’ve spoken to this year. It’s so foundational to creating a data-driven organization, that most of the questions surrounding it focus on the “when”…

Data Science

8 min read

Is “Self-Service” Data’s Biggest Lie?
Is “Self-Service” Data’s Biggest Lie?
Data Science

8 min read


Jul 7, 2022

Implementing Data Contracts: 7 Key Learnings

What are data contracts and do they make sense for your organization? — Forward: A Data Engineering Movement Afoot? We ran into Andrew, a team lead and senior engineer at GoCardless, at our London IMPACT event. He talked about implementing data contracts and how GoCardless has eschewed what has started to solidify as the industry standard ELT modern data warehouse approach. This approach typically involves complex pipelines, large…

Data Engineering

9 min read

Implementing Data Contracts: 7 Key Learnings
Implementing Data Contracts: 7 Key Learnings
Data Engineering

9 min read


Published in Towards Data Science

·Jun 23, 2022

I Don’t Care How Big Your Data Is.

Innuendo aside, “big” data is getting smaller and faster. Data leaders need to adjust to the new paradigm. — At some point in the last two decades, the size of our data became inextricably linked to our ego. The bigger the better. We watched enviously as FAANG companies talked about optimizing hundreds of petabyes in their data lakes or data warehouses. We imagined what it would be like to…

Big Data

8 min read

I Don’t Care How Big Your Data Is.
I Don’t Care How Big Your Data Is.
Big Data

8 min read


May 24, 2022

Monte Carlo’s Series D and the Future of Data Observability

When it comes to building a category, it’s all about your customers. Here’s our vision for the future of reliable data. Four years ago, I was leading a data team at Gainsight, a customer success company, responsible for generating the analytics that powered our executive dashboards. I was regularly getting…

Data

4 min read

Monte Carlo’s Series D and the Future of Data Observability
Monte Carlo’s Series D and the Future of Data Observability
Data

4 min read


Published in Towards Data Science

·May 19, 2022

Data Stewards Have the Worst Seat at the Table

The data steward has an impossible job. Here’s why and what we can do to empower them. — In his seminal 2017 blog post, The Downfall of the Data Engineer, Maxime Beauchemin wrote that the data engineer had the worst seat at the table. Data technology and teams have changed tremendously since that time, and now the Preset CEO and creator of Apache Airflow and Apache Superset has…

Data Stewardship

8 min read

Data Stewards Have The Worst Seat At The Table
Data Stewards Have The Worst Seat At The Table
Data Stewardship

8 min read

Barr Moses

Barr Moses

9.4K Followers

Co-Founder and CEO, Monte Carlo (www.montecarlodata.com). @BM_DataDowntime #datadowntime

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