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Low Code And High Quality Data Engineering For The Whole Organization With Prophecy

Data Engineering Podcast

Summary There is a wealth of tools and systems available for processing data, but the user experience of integrating them and building workflows is still lacking. Raj Bains founded Prophecy to address this need by creating a UI first platform for building and executing data engineering workflows that orchestrates Airflow and Spark.

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Six Books that Have Shaped My Data Career

Towards Data Science

If you’re interested in those early days, how I grew my career, and advice for newcomers to data, take a look at my earlier article. In this article, I want to focus on my on-again, off-again relationship with books and reading. Even if you haven’t read any of the books below, you’ve probably at least heard of some of them.

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[O’Reilly Book] Chapter 1: Why Data Quality Deserves Attention Now

Monte Carlo

Your downstream data consumers including product analysts, marketing leaders, and sales teams rely on data-driven tools like CRMs, CXPs, CMSs, and any other acronym under the sun to do their jobs quickly and effectively. But what happens when the data is wrong?

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How to Use DBT to Get Actionable Insights from Data?

Workfall

With DBT, they weave powerful SQL spells to create data models that capture the essence of their organization’s information. DBT’s superpowers include seamlessly connecting with databases and data warehouses, performing amazing transformations, and effortlessly managing dependencies to ensure high-quality data.

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How to Treat Your Data As a Product

Monte Carlo

A data product, coined by DJ Patil, Former Chief Data Scientist of the United States, has several components, including a product management process, the domain wrapper comprising a semantic layer, business logic and metrics, and access. Simply put, a data product is much more than a dataset alone. Who needs this data?

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4 Native Snowflake Data Quality Checks & Features You Should Know

Monte Carlo

Adopting a cloud data warehouse like Snowflake is an important investment for any organization that wants to get the most value out of their data. In Snowflake, you can uncover valuable insights about which tables are used, by whom, and how often with the Access History feature (available in Enterprise Edition and higher).

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Managing Big Data Quality And 4 Reasons To Go Smaller

Monte Carlo

At some point in the last two decades, the size of our data became inextricably linked to our ego. 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 manage big data quality at that scale.