Photo by Shubham Dhage on Unsplash Learning about how to data models from basic star schemas on the internet is like learning data science using the IRIS data set. It works great as a toy example. But it doesn’t match real life at all. Data modeling in real life requires you fully understand the data…
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Good Design Is Easier to Change Than Bad Design – The Pragmatic Programmer Programming is just one aspect of the difficulties of tech work for data engineers. Creating simple yet robust systems that help manage your data infrastructure is equally important. This challenge of building a simple yet robust data infrastructure remains even with no-code/low-code solutions. Just…
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Photo by Sigmund on Unsplash 2022 is coming to an end. What is the state of data infra? Are Snowflake and Databricks still fighting over total cost of ownership? Is everyone switching to DuckDB? Are data engineers all learning Rust? Let’s try to answer these questions. Building field-level lineage for modern data systems Lineage…
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Companies of all sizes are looking for faster and easier ways to take advantage of data through analytics and BI. In particular, knowing who your customers are, how they interact with your business, products and services is a modern necessity. In a customer-centric world where data can help improve the overall customer experience and relationships,…
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Scaling data talent is hard. It’s hard to hire. Hard to grow and just overall hard in terms of managing processes and output. But there are brilliant leaders and managers doing it everyday. I recently interviewed Veronica Zhai, the principal product manager at Fivetran. She has led Fivetran’s analytical team for nearly the last year…
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Photo by NEW DATA SERVICES on Unsplash Many companies treat data as an afterthought, like a chef throwing parsley on a dish and calling it a garnish. That’s because many companies don’t live and die by their data. They don’t eat, breathe and sleep data. Well, I have. Or at least, I have worked for…
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Photo by Isaac Smith on Unsplash Analyzing data is a skill required but more than just data analysts and data scientists in 2021. Many roles require some form of data analysis whether it be done in Excel, Jupyter Notebooks, or Tableau. However, data analysis is not generally a course taught in college. It might be…
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Photo by Kaleidico on Unsplash Companies of all sizes have embraced using data to make decisions. However, according to a 2019 report from Goldman Sachs it’s actually quite difficult for businesses to use data to build a sustainable competitive advantage. Our team has worked with and for companies across industries. We have seen the good, the bad and the…
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Photo by ev on Unsplash There are plenty of cliches about data and its likeness to oil or companies being data-driven. Is there truth to all this hype about data strategy, predictive modeling, data visualization, and machine learning? In our experience, these cliches are true. In the past few years, we have already helped several…
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Photo by Sean Pollock on Unsplash Banks from Seattle to New York trust us with their data science solutions. Why’s that? The short answer: while the finance industry has been leveraging data science and statistics for decades, times are changing. Data science and financial strategy are evolving. This means teams need to stay current in order to maximize…
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