Google Cloud Platform: BigData as a service - PUE

Big Data as a service is the topic to be discussed in this PUE Tech Day, in which there will be a tour of some of the Big Data technologies that we find in Google Cloud Platform (GCP). Most of these products are managed, with Google being in charge of managing the infrastructure in order to focus on analyzing our data and paying only for the use we make. In this webinar we will do demonstrations to learn about the functionality of the different tools that Google Cloud Platform (GCP) offers as a Big Data service. We will address the key points for the success of a Big Data project in the Google cloud, so that we can get the most out of each of the components and our data. This seminar is aimed at the profiles of Data engineers, Big Data Administrators, Big Data Architects, Data Analyst, Data Scientist, among others. Google Cloud Platform offers a wide variety of products based on Big Data technology on data analysis and storage; in this webinar / PUE Tech Day we will learn about some of the functions and features offered by tools such as: BigQuery, Cloud Storage, Dataproc, Dataflow, Cloud Composer and Cloud Data Fusion. Among the outstanding products that Google Cloud offers us, we find different solutions, one of the most recognized is BigQuery. BigQuery is a managed data warehouse service in the cloud that does not require any type of server, and by creating a datawarehouse it is possible to store from gigabytes to petabytes at low cost, because you only pay for the storage used and the data consulted. This storage and data analytics alternative is tailored to individual and business needs that will help transform a business with ease. In terms of storage, Google Cloud provides us with the Cloud Storage solution, a highly durable, global object storage service that can scale up to exabytes of data. Cloud Storage is designed to be a safe and durable storage (as a data lake) that offers you the possibility of instantly accessing your data from any kind of storage, in addition you can, through a unified API, integrate storage in your applications and optimize Easily price-performance between different storage classes with object lifecycle management. This Big Data Google Cloud solution offers us that it becomes the fastest, easiest and most profitable method of running Apache Spark and Apache Hadoop is Dataproc. Dataproc is a fast, easy-to-use, fully managed cloud service for running Apache Spark and Apache Hadoop clusters. Operations take just a few minutes or seconds and you only pay for the resources that are used. This powerful data processing and analysis platform is easily integrated with other Google Cloud Platform (GCP) services. When it comes to batching or streaming data in real time, Dataflow is a managed streaming analytics service that leverages autoscaling and batching to minimize latency, processing time, and costs. It offers an almost unlimited capacity to solve challenges that arise with data processing, since it does not require a server. Cloud Composer is a workflow orchestration service that enables you to create, schedule, and monitor processing flows in clouds and data centers on-premises. Cloud Composer is based on the open source Apache Airflow project and uses the Python programming language. And the most effective google cloud biga data solution for data integration is Cloud Data Fusion, a cloud-native data integration service that helps create and manage Extract, Transform, and Load (ETL) data processing flows. and extraction, loading and transformation (ELT) efficiently, thanks to its graphical interface and its extensive open source library. Find out more and find out about new #PUETechDays on our social networks: Facebook:   / ticpue   Twitter:   / ticpue   Linkedin:   / tic-pue   #GoogleCloudPlatform