Jan-Willem Middelburg
The Enterprise Big Data Framework
Building Critical Capabilities to Win in the Data Economy
Jan-Willem Middelburg
The Enterprise Big Data Framework
Building Critical Capabilities to Win in the Data Economy
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Transform enterprise big data into valuable assets with this comprehensive guide to data analysis, data engineering, algorithm design and data architecture.
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Transform enterprise big data into valuable assets with this comprehensive guide to data analysis, data engineering, algorithm design and data architecture.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Kogan Page Ltd
- Seitenzahl: 496
- Erscheinungstermin: 3. November 2023
- Englisch
- Abmessung: 238mm x 168mm x 29mm
- Gewicht: 830g
- ISBN-13: 9781398601710
- ISBN-10: 1398601713
- Artikelnr.: 61961457
- Verlag: Kogan Page Ltd
- Seitenzahl: 496
- Erscheinungstermin: 3. November 2023
- Englisch
- Abmessung: 238mm x 168mm x 29mm
- Gewicht: 830g
- ISBN-13: 9781398601710
- ISBN-10: 1398601713
- Artikelnr.: 61961457
Jan-Willem Middelburg
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
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
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
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