Data Science

6 Reasons Why Companies Fail at Data Governance

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 governancedifferently. Reasons In this article, I’ll share six of the top reasons that we have seen data…
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Panda vs. Pony: Data Science & Exploratory Analysis Showdown

Docker for Data Science for Beginner's

Data Science

6 Steps to Making Data Reliability a Habit

Some organizations approach data quality like a crash diet. Instead, try these 6 steps for sustainable data quality at scale. Making Data I like to think of operationalizing data reliability within the context of physical fitness. You can get in shape with hard work,but staying in shape requires good habits.And above all else it’s a mindset and a lifestyle. You…
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Panda vs. Pony: Data Science & Exploratory Analysis Showdown

Docker for Data Science for Beginner's

Data Science

Zero-ETL, ChatGPT, And The Future of Data Engineering

The post-modern data stack is coming. Are we ready? Zero-ETL If you don’t like change, data engineering is not for you. Little in this space has escaped reinvention. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. As part of this movement, Fivetran and dbt fundamentally…
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Panda vs. Pony: Data Science & Exploratory Analysis Showdown

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Blog

The Next Big Crisis for Data Teams

Data teams are more important than ever before — but they need to get closer to the business. Here’s how we can right the ship. Data Teams Over the past decade, data teams have been simultaneously underwater and riding a wave. We’ve been building modern data stacks, migrating to Snowflake like our lives depended on it, investing in headless BI, and growing our teams…
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Understanding Machine Learning Models Explained

What Is Machine Learning: A Beginner's Guide

Data Science

61 Data Observability Use Cases From REAL Data Teams

I wanted to share this article we put together that illustrates how real data teams are benefiting from data observability. Data observability, an organization’s ability to fully understand the health and quality of the data in their systems, has become one of the hottest technologies in modern data engineering. In less than three years it has gone from anidea sketched out in…
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Panda vs. Pony: Data Science & Exploratory Analysis Showdown

Docker for Data Science for Beginner's

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Blog

Are You a Data Ticket Taker or Decision Maker?

The characteristics and value of reactive vs. proactive data teams Data Ticket Fundamentally, there are two different types of data teams in this world. There are those who are reactive to the wants of the organization, and then there are those who proactively lead the organization towards its needs. The first is helpful, but a cost center. The second is a value generator.In…
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Understanding Machine Learning Models Explained

What Is Machine Learning: A Beginner's Guide

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All I Want To Know Is What’s Different — But Also Why and Can You Fix It ASAP?

If you want to build data trust, you can’t just gut-check the final output. You need to monitor data as it is ingested and flows across your data pipeline. Here’s why. I Want To Know! I link to Benn Stancil in my posts more than any other data thought leader. I might not always agree with his answers, but I almost always agree with his questions. True to form, last…
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Understanding Machine Learning Models Explained

What Is Machine Learning: A Beginner's Guide

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How to Build a 5-Layer Data Stack

Spinning up a data platform doesn’t have to be complicated. Here are the 5 must-have layers to drive data product adoption at scale. Like bean dip and ogres, layers are the building blocks of the modern data stack. Data Stack Its powerful selection of tooling components combine to create a single synchronized and extensible data platform with each layer serving a unique…
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Understanding Machine Learning Models Explained

What Is Machine Learning: A Beginner's Guide

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Pioneering Data Observability: Data, Code, Infrastructure, & AI

Outlining the past, present, and future of architecting reliable data systems. Pioneering Data When we launched thedata observabilitycategory in 2019, the term was something I could barely pronounce. Four years later, the category has squarely established itself asa core layer of the modern data stack. Data Observability isa G2 category,recognized by…
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Understanding Machine Learning Models Explained

What Is Machine Learning: A Beginner's Guide

Data Science

Your Data’s (Finally) In The Cloud. Now, Stop Acting So On-Prem

The modern data stacks allow you to do things differently, not just at a larger scale. Take advantage of it. Imagine you’ve been building houses with a hammer and nails for most of your career, and I gave you a nail gun. But instead of pressing it to the wood and pulling the trigger, you turn it sideways and hit the nail just like you would as if it were a hammer. You would…
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Panda vs. Pony: Data Science & Exploratory Analysis Showdown

Docker for Data Science for Beginner's