Discover the crucial Architecturally Significant Requirements (ASR) for distributed systems, including Availability, Durability, Resiliency, Reliability, and Scalability. Learn how these factors impact system design and performance.

Machine Learning is based on the idea that analytic systems can learn to identify patterns and make decisions with minimal human involvement

Understand the CAP and PACELC theorems in distributed systems. Learn how to navigate tradeoffs between consistency, availability, and partition tolerance for optimal system design.

Caching... There is so much in that word - the pain of invalidation and the joy of reusing computation. In Spark, this is known as an optimization technique

I am very annoyed that all sorts of big data engineers confuse S3 and HDFS systems, assuming that S3 is the same as HDFS. That’s not true.

So much hype around serverless architectures but what it's really bringing to the table for us? Is it the next standard in application development?

Another portion of tips to Apache Spark usage, now it's about caching and checkpointing data

There are many pitfalls that inexperienced engineers may encounter when building pipelines based on Cloud Dataproc, let's look into them.

Learn how to use MLflow for performing reproducible Bayesian experiments.

Learn more about the latest release of Apache Spark™, version 3.2, including pandas API on Spark, Adaptive Query Execution, and ANSI mode and how you can begin using it through Databricks Runtime 10.0.

Learn more about the Pytorch-based GPU-accelerated sentiment analysis package from Huggingface and how it leverages the Databricks platform to simplify and scale the analysis of text for sentiment.

Leadership skills != subject matter expertise

Learn how we optimized our workflow at Intelematics by creating a library to work with geospatial data using python on the Databricks Lakehouse platform.

The Oakland Athletic

22F here- working through my MBA while working full time as a senior purchasing specialist. My school (not an ivy league, but a good school...

Incode, a company developing an AI-powered identity verification product, has raised $220 million in venture capital.

MoEngage, a startup developing an AI-driven customer engagement platform, has closed a $30 million venture capital round.

Об авторах: Майк Дель Бальсо, генеральный директор и сооснователь компании Tecton Виллем Пиенаар, создатель хранилища признаков FeastСпециалисты по работе с данными постепенно понимают, что для...

Dragonboat, a startup developing a product management platform, has raised $12 million in venture capital funding.