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Introduction Big Data (NL)
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Volume, Velocity, Variety, Veracity. Also known as the 4 V's when it comes to Big Data. But what makes this Big Data? And what can you do with this?
Training codeCGAINBD-CESpoken LanguageDutchLanguage MaterialsEnglishDayparts2Price€750,00excl. VAT No extra costs.Book Introduction Big Data (NL) now
In group training, we use several learning methods to help you obtain the knowledge, give you helpful insights and get you inspired. Check the Spoken language and Language materials on the left for language info.
What is Introduction Big Data
Big Data is a collection of data that is huge in volume and grows exponentially over time. It is data of such a large size or complexity that traditional databases cannot efficiently store or process it. During the 'Introduction Big Data' training you will learn that there is still value to be gained from this data.
You will learn the basic concepts and techniques of Big Data and how this fits within the data architecture.
Various trends and developments will be discussed.Who should attend Introduction Big Data
The Introduction Big Data training is suitable for:
- Starters at the beginning of their career
- People who make a career switch towards Big Data
- People who work in IT, especially in departments such as Data Management
- Data Engineers
- Business Analysts
- Information Analysts
Prerequisites
There are no specific requirements to participate in this training.
Objectives
In the 'Introduction to Big Data' training we cover the following topics:
- Reasons for having a data warehouse/data lake and business intelligence.
- Reasons for using Big Data technology.
- Terminology around Big Data.
- Big Data and Data Lakes.
- Trends and developments in the field of Big Data.
Volume, Velocity, Variety, Veracity. Also known as the 4 V's when it comes to Big Data. But what makes this Big Data? And what can you do with this?
Training codeCGAINBD-CESpoken LanguageDutchLanguage MaterialsEnglishDayparts2Price€750,00excl. VAT No extra costs.With an Incompany training you have several advantages:
- You choose the location
- You experience the training with your colleagues, so it is always in line with your practice
- The trainer can tailor explanations, examples and assignments to your organization
- In consultation exercises can be adapted to organization-specific questions
Request more information or a quote.What is Introduction Big Data
Big Data is a collection of data that is huge in volume and grows exponentially over time. It is data of such a large size or complexity that traditional databases cannot efficiently store or process it. During the 'Introduction Big Data' training you will learn that there is still value to be gained from this data.
You will learn the basic concepts and techniques of Big Data and how this fits within the data architecture.
Various trends and developments will be discussed.Who should attend Introduction Big Data
The Introduction Big Data training is suitable for:
- Starters at the beginning of their career
- People who make a career switch towards Big Data
- People who work in IT, especially in departments such as Data Management
- Data Engineers
- Business Analysts
- Information Analysts
Prerequisites
There are no specific requirements to participate in this training.
Objectives
In the 'Introduction to Big Data' training we cover the following topics:
- Reasons for having a data warehouse/data lake and business intelligence.
- Reasons for using Big Data technology.
- Terminology around Big Data.
- Big Data and Data Lakes.
- Trends and developments in the field of Big Data.
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e-CF competences with this course
At Capgemini Academy we believe in transparency and clarity in the training landscape. That is why, in the table below, we show you to which e-CF competence this training or certification contributes. For more information about how to use the e-Competence Framework read more here. If you want to know how you can apply the e-CF within your organization, read more on this page.
| e-Competence Level | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| A.6.Application Design | |||||
| B.2.Component Integration | |||||
| D.10.Information and Knowledge Management | |||||
| A.5.Architecture Design |