Data Engineering Workshop
For over 10 years, there has been an intense focus by companies to extract business value from their data.Out of this activity, a role called the data scientist emerged. However, it quickly became obvious that a majority of a data scientist’s time was spent on data preparation or moving analytical models into production environments. Thus, the data engineer has emerged as a highly desirable and indispensable member of an analytics project team. This instructor-led workshop covers the content and hands-on lab exercises provided in the following five courses: Data Warehousing with SQL and NoSQL, ETL Offload with Hadoop and Spark, Processing Streaming and IoT Data, Building Data Pipelines with Python, and Data Governance, Security and Privacy for Big Data.
Virtual Training nebo e-Learning?
Máme dostatečnou flexibilitu, takže vybírat můžete jak prezenční termíny, tak online kurzy.
Zkuste živý kurz virtuálněTarget Group
This course is intended for data engineers, data scientists, data architects, data analysts or anyone else who wants to learn and apply data engineering principles and tools. Possible workshop participants include:
- Current business and data analysts looking to add data engineering to their skillset
- Database professionals looking to expand their Big Data skills
- Managers of teams of business intelligence, analytics, and big data professionals
What will you learn
- Data Warehousing with SQL and NoSQL
- ETL Offload with Hadoop and Spark
- Data Governance, Security and Privacy for Big Data
- Processing Streaming and IoT Data
- Building Data Pipelines with Python
Prerequisites
To complete this course successfully and gain the maximum benefits from it, a student should have the following knowledge and skill sets:
- Experience with a programming language such as Java, R, or Python
- Familiarity with the non-statistical aspects of the Data Science and Big
Data Analytics v2 content - Understanding of the data engineer role provided in the Introduction to
Data Engineering (course id #: ES731OCMIDENG)
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Naposledy shlédnuté
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Jsme vám k dispozici na telefonním čísle +420 222 553 101 vždy od pondělí do pátku: 9:00 - 17:00.
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