I once had an engineer tell me that they essentially didn’t want to consider cost as they were building a solution. I was baffled. Don’t get me wrong, yes, when you’re building, you iterate and aim to improve your solutions cost. But from my perspective, I don’t think completely ignoring costs from day one is…
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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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Data warehousing would be easy if all data were structured and formatted in the data source. Maybe we wouldn’t even need to build a data warehouse. But as anyone who has worked with data from more than one source knows, that’s rarely the case. Businesses today need to pull data from a plethora of sources,…
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If you’re a data engineer, then you’ve likely at least heard of Airflow. Apache Airflow is one of the most popular open-source workflow orchestration solutions that gets used for data pipelines. This is what spurred me to write the article “Should You Use Airflow” because there are plenty of people who don’t enjoy Airflow or…
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Image Source: Druid The past few decades have increased the need for faster data. Some of the catalysts were the push for better data and decisions to be made around advertising. In fact, Adtech has driven much of the real-time data technologies that we have today. For example, Reddit uses a real-time database to provide…
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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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SSIS, short for SQL Server Integration Service, is an essential data migration tool for modern businesses. As a key part of Microsoft’s SQL database software, It allows you to easily complete many complex tasks, including data extraction, merging data, loading and transformation, aggregating data, and more. It’s a comprehensive solution to your data management needs. In today’s business landscape,…
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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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Photo by Leif Christoph Gottwald on Unsplash A few months ago, I uploaded a video where I discussed data warehouses, data lakes, and transactional databases. However, the world of data management is evolving rapidly, especially with the resurgence of AI and machine learning. There are numerous other methods that technical teams are utilizing to handle…
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