Buch, Englisch, 496 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 1259 g
Building Critical Capabilities to Win in the Data Economy
Buch, Englisch, 496 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 1259 g
ISBN: 978-1-3986-0171-0
Verlag: Kogan Page
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
- Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
Weitere Infos & Material
- Section - ONE: Introduction to Big Data;
- Chapter - 01: Introduction to Big Data;
- Chapter - 02: The Big Data framework;
- Chapter - 03: Big Data strategy;
- Chapter - 04: Big Data architecture;
- Chapter - 05: Big Data algorithms;
- Chapter - 06: Big Data processes;
- Chapter - 07: Big Data functions;
- Chapter - 08: Artificial intelligence;
- Section - TWO: Enterprise Big Data analysis;
- Chapter - 09: Introduction to Big Data analysis;
- Chapter - 10: Defining the business objective;
- Chapter - 11: Data ingestion – importing and reading data sets;
- Chapter - 12: Data preparation – cleaning and wrangling data;
- Chapter - 13: Data analysis – model building;
- Chapter - 14: Data presentation;
- Section - THREE: Enterprise Big Data engineering;
- Chapter - 15: Introduction to Big Data engineering;
- Chapter - 16: Data modelling;
- Chapter - 17: Constructing the data lake;
- Chapter - 18: Building an enterprise Big Data warehouse;
- Chapter - 19: Design and structure of Big Data pipelines;
- Chapter - 20: Managing data pipelines;
- Chapter - 21: Cluster technology;
- Section - FOUR: enterprise Big Data algorithm design;
- Chapter - 22: Introduction to Big Data algorithm design;
- Chapter - 23: Algorithm design – fundamental concepts;
- Chapter - 24: Statistical machine learning algorithms;
- Chapter - 25: The data science roadmap;
- Chapter - 26: Programming languages 26 visualization and simple metrics;
- Chapter - 27: Advanced machine learning algorithms;
- Chapter - 28: Advanced machine learning classification algorithms;
- Chapter - 29: Technical communication and documentation;
- Section - FIVE: Enterprise Big Data architecture;
- Chapter - 30: Introduction to the Big Data architecture;
- Chapter - 31: Strength and resilience – the Big Data platform;
- Chapter - 32: Design principles for Big Data architecture;
- Chapter - 33: Big Data infrastructure;
- Chapter - 34: Big Data platforms;
- Chapter - 35: The Big Data application provider;
- Chapter - 36: System orchestration in Big Data