Materias:

Tabla de Contenidos: “…; Real Versus Fake Data Science; The Data Scientist; Data Science Applications in 13 Real-World Scenarios; Data Science History, Pioneers, and Modern Trends; Summary; Chapter 2: Big Data Is Different; Two Big Data Issues; Examples of Big Data Techniques; What MapReduce Can't Do; Communication Issues; Data Science: The End of Statistics?…”

Materias:

Materias:

Materias: “…Big data Statistical methods…”

Materias:

Materias: “…Big data…”

Materias:

Materias:

Tabla de Contenidos: “…Data Storage - Two Designations - Volatile and Nonvolatile Memory -- Primer on Data Structures and Formats -- Data Stores Topology -- Local File Systems and Network Data Storage -- Operational Data Stores -- Data Marts and the EDWs -- Benefits and Drawbacks of the EDW -- Benefits of an EDW -- Drawbacks of an EDW -- Cluster Computing and Big Data -- What Is Big Data? -- Big Data as a Concept -- Big Data as a Technology -- Why the Push to Big Data? …”

Tabla de Contenidos: “…Table of Contents Fundamentals of Data Engineering Big Data Capabilities on GCP Building a Data Warehouse in BigQuery Building Orchestration for Batch Data Loading Using Cloud Composer Building a Data Lake Using Dataproc Processing Streaming Data with Pub/Sub and Dataflow Visualizing Data for Making Data-Driven Decisions with Data Studio Building Machine Learning Solutions on Google Cloud Platform User and Project Management in GCP Cost Strategy in GCP CI/CD on Google Cloud Platform for Data Engineers Boosting Your Confidence as a Data Engineer…”

Materias: “…Big data…”

Materias:

Tabla de Contenidos: “…Cover -- Copyright -- Contributors -- Table of Contents -- Preface -- Section 1: AWS Data Engineering Concepts and Trends -- Chapter 1: An Introduction to Data Engineering -- Technical requirements -- The rise of big data as a corporate asset -- The challenges of ever-growing datasets -- The role of the data engineer as a big data enabler -- Understanding the role of the data engineer -- Understanding the role of the data scientist -- Understanding the role of the data analyst -- Understanding other common data-related roles -- The benefits of the cloud when building big data analytic solutions -- Hands-on - creating and accessing your AWS account -- Creating a new AWS account -- Accessing your AWS account -- Summary -- Chapter 2: Data Management Architectures for Analytics -- Technical requirements -- The evolution of data management for analytics -- Databases and data warehouses -- Dealing with big, unstructured data -- Cloud-based solutions for big data analytics -- A deeper dive into data warehouse concepts and architecture -- Dimensional modeling in data warehouses -- Understanding the role of data marts -- Distributed storage and massively parallel processing -- Columnar data storage and efficient data compression -- Feeding data into the warehouse - ETL and ELT pipelines -- An overview of data lake architecture and concepts -- Data lake logical architecture -- The storage layer and storage zones -- Catalog and search layers -- Ingestion layer -- The processing layer -- The consumption layer -- Data lake architecture summary -- Bringing together the best of data warehouses and data lakes -- The data lake house approach -- New data lake table formats -- Federated queries across database engines -- Hands-on - using the AWS Command Line Interface (CLI) to create Simple Storage Service (S3) buckets -- Accessing the AWS CLI…”

Materias:

Materias:

Materias: “…Big data…”

Materias:

Materias:

Materias: “…Big data…”