Big Data and Machine Learning

Big Data and Machine Learning >> Google Cloud Platform Fundamentals: Core Infrastructure

Data mining and analysis in datasets of known size

Manage datasets of unpredictable size

Migrate on-premises Hadoop jobs to the cloud

Manage data that arrives in realtime

Orchestration

Manual resource management

Reserved compute instances

Extract, Transform, and Load (ETL)

Once in BigQuery, data is not accessible from other GCP services.

BigQuery lets you run fast SQL queries against large databases.

BigQuery is a good choice for data analytics warehousing.

BigQuery requires that you provision database instances ahead of use.

BigQuery is a good choice for online transaction processing.

Storage of binary web content

Decoupling systems

Analyzing streaming data

Executing ad-hoc SQL queries

Internet of Things applications

A managed service for building data pipelines

An open-source software library that’s useful for building machine learning applications

A hardware device designed to accelerate machine learning workloads

A managed service for building machine learning models

It analyzes text to reveal its structure and meaning.

It extracts text in various languages from images.

It translates arbitrary strings into any supported language.

It performs sentiment analysis on audio and video content.

Big Data and Machine Learning >> Google Cloud Platform Fundamentals: Core Infrastructure