Exploratory data analysis sits at the core of any insightful data work. Performingloganalysis in search for threats is no different.
Data!
Whether you are a security analyst triaging alerts or a detection engineer looking for detection opportunities from logs,the ability to understand data is what determines your success.
Now that security logs are…
In the fast-moving conditional field of Data Science, it is an art to ensure that your code works effectively anywhere you run it. When it comes to different operating systems and their machine, it can be tiresome, prone to possible inconsistency, and take a lot of time. Using Docker, a unique tool, you can achieve a consistent workspace everywhere. In this article, we will learn the basics…
Innuendo aside, “big” data is getting smaller and faster. Data leaders need to adjust to the new paradigm.
At some point in the last two decades, the size of our data became inextricably linked to our ego. The bigger the better.
Big Data
We watched enviously as FAANG companies talked aboutoptimizing hundreds of petabyes in their data lakesor data warehouses.
We…
Forward: A Data Engineering Movement Afoot?
We ran into Andrew, a team lead and senior engineer atGoCardless, at our London IMPACT event.
He talked about implementing data contracts and how GoCardless has eschewed what has started to solidify as the industry standard ELT modern data warehouse approach.This approach typically involves complex pipelines, large data dumps, and…
Self-serve systems are a big priority for data leaders and a principle of nearly every modern data strategy, but what exactly does it mean?
Data self-service
Data self-service, the ability for stakeholders in the organization to answer their own business questions with data, is a top initiative for nearly every data leader I’ve spoken to this year.
It’s so foundational to…
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KPIs & Data Team
As analytics professionals, we deal in data: serving ad-hoc reports on a minute’s notice, pulling queries for executives, and generally forecasting company performance across a variety of metrics.But how can we be truly successful if we don’t measure our own performance, too?
In this article, we discuss six important steps to setting goals for our own…
Even with the most well-designed data platforms, systems will break. Without embracing risk, you’re playing with fire.
Say it with me:broken data is inevitable.
Bad Data?
It doesn’t care about how proactive you are at writing dbt tests, how perfectly your data is modeled, or how robust your architecture is. The possibility of a major data incident (Null value?
The data gatekeeper is dead, long live the…oh no what have we done?
A silent alarm rings in my head whenever I hear someone utter the phrase, “data is everyone’s responsibility.”
Data Warehouse
You can just as easily translate this to mean that “data is no one’s responsibility,” too.This, readers, is what I call the “data tragedy of the…
What’s in store for the future of data engineering? In this article, I share some of my topline predictions for 2023 — and beyond.
End of the year prediction articles are hokey, but they serve a purpose. They help us rise above the daily grind and consider where to place our longer term bets.
Next for Data Engineering in 2023?
They also tend to be an exercise in humility as we…
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…