Remove Big Data Remove Data Engineering Remove Fashion Remove Machine Learning
article thumbnail

Data engineers vs. data scientists

O'Reilly Media - Data

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

article thumbnail

Why Are We Excited About the REAN Cloud Acquisition?

Hu's Place - HitachiVantara

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces.

Cloud 78
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Formulating ‘Out of Memory Kill’ Prediction on the Netflix App as a Machine Learning Problem

Netflix Tech

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

article thumbnail

The Data Science Iron Triangle – Modern BI and Machine Learning

Cloudera

The three components of the data science iron triangle all have their challenges and strife. Only when organizations understand these challenges will they begin to harmonize and put them to work in a seamless fashion. Below we deconstruct three data science iron triangle dilemmas. How do I wrangle in my data science community?

article thumbnail

The Year Ahead for BPM -- 2019 Predictions from Top Influencers

BPM

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. As we move into a world that is more and more dominated by technologies such as big data, IoT, and ML, more and more processes will be started by external events.

article thumbnail

Incremental Processing using Netflix Maestro and Apache Iceberg

Netflix Tech

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. data arrives too late to be useful).

Windows 84
article thumbnail

Data Product Strategies: How Cloudera Helps Realize and Accelerate Successful Data Product Strategies

Cloudera

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.