Acceso restringido con credenciales UPSA

Enlace del recurso

“…Ingestión de fibra dietética en adultos de La Habana y Ciudad de La Habana. …”

Tabla de Contenidos: “…. -- See also -- Chapter 5: Transform Data -- Technical requirements -- Creating an ingest pipeline -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Enriching data with a custom ingest pipeline for an existing Elastic Agent integration -- Getting ready -- How to do it... -- How it works... -- There's more... -- Using a processor to enrich your data before ingesting with Elastic Agent -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Installing self-managed Logstash -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Creating a Logstash pipeline -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Setting up pivot data transform -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Setting up the latest data transform -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Downsampling your time series data -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 6: Visualize and Explore Data -- Technical requirements -- Exploring your data in Discover -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Exploring your data with ES|QL -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Creating visualizations with Kibana Lens -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Creating visualizations from runtime fields -- Getting ready…”

Tabla de Contenidos: “…Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. …”

Tabla de Contenidos: “…The hamster as a model for human ingestive behavior / Ruth B.S. Harris -- chapter 4. beyond homeostasis : understanding the impact of psychosocial factors on appetite using nonhuman primate models / Mark E. …”

Accés lliure

Materias:

“…Implementing end-to-end real-time data pipelines : from ingest to machine learning…”

“…You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines…”

“…Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key Features Become well-versed with the core concepts of Apache Spark and Delta Lake for building data platforms Learn how to ingest, process, and analyze data that can be later used for training machine learning models Understand how to operationalize data models in production using curated data Book Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. …”

Materias: Enlace del recurso

Tabla de Contenidos: “…Source System Zone functionalitiesUnderstanding connectivity processing; Understanding Intake Processing for data variety; Transient Landing Zone functionalities; File validation checks; Data Integrity checks; Raw Storage Zone functionalities; Data lineage processes; Deep Integrity checks; Security and governance; Information Lifecycle Management; Practical Data Ingestion scenarios; Architectural guidance; Structured data use cases; Semi-structured and Unstructured data use cases; Big Data tools and technologies; Ingestion of structured data; Ingestion of streaming data; Summary…”

Materias: