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Terraform your Cloud Infrastructure
So, you have an existing infrastructure in the cloud and want to wrap it up as code in a new, shiny IaC style? Splendid! Oh… it’s spanning through two…
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Anomaly detection implemented in podcasting company
Being a Data Engineer is not only about moving the data but also about extracting value from it. Read an article on how we implemented anomalies detection for one of our clients that works in the podcasting industry, Acast. With the mechanisms we implemented, Acast employees are notified on the podcasts that suddenly gain or lose the audience. The results reveal trendsetting podcasts (the influencing ones, that grow episode after episode), hot topics (on shows that publish an episode that is listened all over the world) and also weird podcasts applications behaviour (sudden spikes in the listening pattern). All these anomalies notifications are based purely on the data and simple logarithm curve fitting - it's unbelievable what you can achieve with data&math!
6 April 2020
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eBook: Power Up Machine Learning Process. Build Feature Stores Faster - an Introduction to Vertex AI, Snowflake and dbt Cloud
Recently we published the first ebook in the area of MLOps: "Power Up Machine Learning Process. Build Feature Stores Faster - an Introduction to…
Read moreTowards better Data Analytics - Google Cloud Bootcamp
“Without data, you are another person with an opinion” These words from Edward Deming, a management guru, are the best definition of what means to…
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Deploy your own Databricks Feature Store on Azure using Terraform
A tutorial on how to deploy one of the key pieces of the MLOps-enabling modern data platform: the Feature Store on Azure Databricks with Terraform as…
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Feature Store comparison: 4 Feature Stores - explained and compared
In this blog post, we will simply and clearly demonstrate the difference between 4 popular feature stores: Vertex AI Feature Store, FEAST, AWS…
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5 questions you need to answer before starting a big data project
For project managers, development teams and whole organizations, making the first step into the Big Data world might be a big challenge. In most cases…
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