Big Data Analytics (CEMS)

The course consists of the following parts:

1. Undarstand relational database - participants will learn what are the database mechanisms, what are the basic clauses of SELECT statement. The course is focused on how to retrieve data from database for further analysis in different business cases of different complexity. These cases reflects real company business needs as regards to data - starting from detailed row level of one table, ending with aggregates built on plenty of tables. The course will employ different methodologies to accomplish this goal: lectures, practices, discussion of solutions.

2. Analysing and Visualizing Data with Tableau. Tableau is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations? data. Students will walk through Tableau, end to end. They will start from learning how to connect and import data to end with creation of the storytelling dashboard

The goal of the course is to introduce topics concerning Big Data Visualisation and Big Data Analytics as well as foundation for the relational database understanding and usage. Big Data is the next generation of data warehousing and business analytics and is poised to deliver top line revenues cost efficiently for enterprises.

Literatura podstawowa:

1. Jason Price. Oracle Database 12c McGraw-Hill Education; June 2013 ISBN: 9780071799362

2. Dan Muray, Tableau Your Data, Wiley 2016

Literatura uzupełniająca:

1. Sam Alapati, Darl Kunhn, Bill Padfield. Oracle Database 12c Performance Tuning Recipes: A Problem-Solution Approach (Expert's Voice in Oracle); Apress 2013

2. Ryan Sleeper, Practical Tableau, O'Reilly Media, Inc. 2018

Publikacje własne:

Doświadczenie zawodowe lub doświadczenie dydaktyczne: Autor oferty ma ponad dziesięcioletnie doświadczenie dydaktyczne w prowadzeniu przedmiotów o problematyce big data.

Kryteria oceniania:

egzamin testowy: 40.00%

kolokwium: 5.00%

ocena z ćwiczeń: 5.00%

inne: 10.00%

projekty: 40.00%

The course consists of the following parts:

1. Undarstand relational database - participants will learn what are the database mechanisms, what are the basic clauses of SELECT statement. The course is focused on how to retrieve data from database for further analysis in different business cases of different complexity. These cases reflects real company business needs as regards to data - starting from detailed row level of one table, ending with aggregates built on plenty of tables. The course will employ different methodologies to accomplish this goal: lectures, practices, discussion of solutions.

2. Analysing and Visualizing Data with Tableau. Tableau is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations? data. Students will walk through Tableau, end to end. They will start from learning how to connect and import data to end with creation of the storytelling dashboard

The goal of the course is to introduce topics concerning Big Data Visualisation and Big Data Analytics as well as foundation for the relational database understanding and usage. Big Data is the next generation of data warehousing and business analytics and is poised to deliver top line revenues cost efficiently for enterprises.

Literatura podstawowa:

1. Jason Price. Oracle Database 12c McGraw-Hill Education; June 2013 ISBN: 9780071799362

2. Dan Muray, Tableau Your Data, Wiley 2016

Literatura uzupełniająca:

1. Sam Alapati, Darl Kunhn, Bill Padfield. Oracle Database 12c Performance Tuning Recipes: A Problem-Solution Approach (Expert's Voice in Oracle); Apress 2013

2. Ryan Sleeper, Practical Tableau, O'Reilly Media, Inc. 2018

Publikacje własne:

Doświadczenie zawodowe lub doświadczenie dydaktyczne: Autor oferty ma ponad dziesięcioletnie doświadczenie dydaktyczne w prowadzeniu przedmiotów o problematyce big data.

Kryteria oceniania:

egzamin testowy: 40.00%

kolokwium: 5.00%

ocena z ćwiczeń: 5.00%

inne: 10.00%

projekty: 40.00%

The course consists of the following parts:

1. Undarstand relational database - participants will learn what are the database mechanisms, what are the basic clauses of SELECT statement. The course is focused on how to retrieve data from database for further analysis in different business cases of different complexity. These cases reflects real company business needs as regards to data - starting from detailed row level of one table, ending with aggregates built on plenty of tables. The course will employ different methodologies to accomplish this goal: lectures, practices, discussion of solutions.

2. Analysing and Visualizing Data with Tableau. Tableau is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations? data. Students will walk through Tableau, end to end. They will start from learning how to connect and import data to end with creation of the storytelling dashboard

The goal of the course is to introduce topics concerning Big Data Visualisation and Big Data Analytics as well as foundation for the relational database understanding and usage. Big Data is the next generation of data warehousing and business analytics and is poised to deliver top line revenues cost efficiently for enterprises.

Literatura podstawowa:

1. Jason Price. Oracle Database 12c McGraw-Hill Education; June 2013 ISBN: 9780071799362

2. Dan Muray, Tableau Your Data, Wiley 2016

Literatura uzupełniająca:

1. Sam Alapati, Darl Kunhn, Bill Padfield. Oracle Database 12c Performance Tuning Recipes: A Problem-Solution Approach (Expert's Voice in Oracle); Apress 2013

2. Ryan Sleeper, Practical Tableau, O'Reilly Media, Inc. 2018

Publikacje własne:

Doświadczenie zawodowe lub doświadczenie dydaktyczne: Przedmiot jest prowadzony we współpracy z firmą Hilti. Autor oferty prowadzi wykład do tego przedmiotu , którego problematyka jest zbliżona do przedmiotu "Big data", który był prowadzony wielokrotnie przez autora zarówno w SGH jak i w Wojskowej Akademii Technicznej,

Kryteria oceniania:

egzamin testowy: 40.00%

kolokwium: 5.00%

ocena z ćwiczeń: 5.00%

inne: 10.00%

projekty: 40.00%

The course consists of the following parts:

1. Undarstand relational database - participants will learn what are the database mechanisms, what are the basic clauses of SELECT statement. The course is focused on how to retrieve data from database for further analysis in different business cases of different complexity. These cases reflects real company business needs as regards to data - starting from detailed row level of one table, ending with aggregates built on plenty of tables. The course will employ different methodologies to accomplish this goal: lectures, practices, discussion of solutions.

2. Analysing and Visualizing Data with Tableau. Tableau is quickly gaining popularity among professionals in data science as a cloud-based service that helps them easily visualize and share insights from their organizations? data. Students will walk through Tableau, end to end. They will start from learning how to connect and import data to end with creation of the storytelling dashboard

The goal of the course is to introduce topics concerning Big Data Visualisation and Big Data Analytics as well as foundation for the relational database understanding and usage. Big Data is the next generation of data warehousing and business analytics and is poised to deliver top line revenues cost efficiently for enterprises.

Literatura podstawowa:

1. Jason Price. Oracle Database 12c McGraw-Hill Education; June 2013 ISBN: 9780071799362

2. Dan Muray, Tableau Your Data, Wiley 2016

Literatura uzupełniająca:

1. Sam Alapati, Darl Kunhn, Bill Padfield. Oracle Database 12c Performance Tuning Recipes: A Problem-Solution Approach (Expert's Voice in Oracle); Apress 2013

2. Ryan Sleeper, Practical Tableau, O'Reilly Media, Inc. 2018

Publikacje własne:

Doświadczenie zawodowe lub doświadczenie dydaktyczne: Przedmiot jest prowadzony we współpracy z firmą Hilti. Autor oferty prowadzi wykład do tego przedmiotu , którego problematyka jest zbliżona do przedmiotu "Big data", który był prowadzony wielokrotnie przez autora zarówno w SGH jak i w Wojskowej Akademii Technicznej,

Kryteria oceniania:

egzamin testowy: 40.00%

kolokwium: 5.00%

ocena z ćwiczeń: 5.00%

inne: 10.00%

projekty: 40.00%