Much of the data we have used for analysis in traditional enterprises has been structured data. It’s easy for humans to break down, understand, and, in turn, find insights from it. However, much of the data that is being created and will be created comes in some form of unstructured format. However, the digital era…
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A key responsibility for any data team is to understand the core metrics driving their business. Starting from the top, these metrics often include figures like gross revenue and expenses. However, these high-level metrics can feel too far removed and abstract from the actual business. Many companies, therefore, break down these top-line metrics into more…
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If you work in data, then AI is everywhere at this point. But whether AI is hype or reality doesn’t change the fact that data engineers will play a major role in ensuring that the data sets that are utilized for the growing use cases are usable both by machines and humans. Whether that data…
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How companies data model varies widely. They might say they use Kimball dimensional modeling. However, when you look in their data warehouse the only part you recognize is the word fact and dim. Over the past near decade, I have worked for and with different companies that have used various methods to capture this data.…
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Many data engineers and analysts don’t realize how valuable the knowledge they have is. They’ve spent hours upon hours learning SQL, Python, how to properly analyze data, build data warehouses, and understand the differences between eight different ETL solutions. Even what they might think is basic knowledge could be worth $10,000 to $100,000+ for a…
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Big data is big business these days. Organizations that hope to get ahead in crowded markets must utilize data from a variety of often highly disparate sources to understand how they’re performing and what customers are saying about them. However, data without the right analysis and reporting tools is just a waste of digital storage…
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It’s that time of year again. When data leaders, VPs and Directors need to start planning out their data roadmap. Of course, this brings up an important question, how should you start planning out your data roadmap? Especially if you’re data team has found itself stuck in the data service trap. Simply providing data and…
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Photo by Austin Distel on Unsplash Success in the data world hinges on team setup. I’ve delved into onboarding and standards in previous articles, but never into the structure of data teams. Typically, there are three configurations: Centralized, Decentralized, and Federated. Most companies I’ve seen use a mix of these. While the newest tech breakthroughs…
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Photo by Lukas As you increase your analytical processes and abilities, you’ll unavoidably increase costs. But there are definite ways to avoid having your costs grow at an unsustainable rate. This is the topic of a panel at the Modern Data Stack Conference featuring Maura Church, ex-director of data science and data engineering from Patreon.…
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Photo by Fotis Fotopoulos on Unsplash Recently several consulting calls started with people asking, “Do we need a data warehouse?” This isn’t a question about whether you need data warehouse consultants, but instead whether you should event start a data warehouse project. Which is a very fair question. Not every company needs a data warehouse.…
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