Detail kurzu
Data Engineering Workshop
EDU Trainings s.r.o.
Popis kurzu
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.
This training prepares the learner for a major portion of the Dell Technologies Proven Professional data engineering specialist-level certification exam (DES-7DE1)
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.
This training prepares the learner for a major portion of the Dell Technologies Proven Professional data engineering specialist-level certification exam (DES-7DE1)
Obsah kurzu
Upon successful completion of this course, participants should be able to:Data Warehousing with SQL and NoSQL
Provide an overview of data warehouses
Explain the purposes of databases and their various types
Describe various SQL and NoSQL tools
ETL Offload with Hadoop and Spark
Identify business challenges with ETL (Extract-Transform-Load)
Explain ELT and ETL processes
Describe the Hadoop ecosystem as an ETL offload solution
Data Governance, Security and Privacy for Big Data
Describe data governance, roles, and responsibilities
Discuss data governance models
Describe metadata, metadata types and uses
Explain master data, framework, and purpose
Explain Hadoop security controls
Discuss data governance tools Apache Atlas, Ranger and Knox
Describe cloud security consideration
Explain GDPR and data ethics
Processing Streaming and IoT Data
Describe streaming and IoT data environments
Explain Kafka messaging system with examples
Explain the key features, architecture and various use cases of stream processing tools such as Storm, Spark Streaming, and Flink
Explain various IoT related projects such as Project Nautilus, Pravega, and EdgeX Foundry
Building Data Pipelines with Python
Write Python scripts to perform key data processing activities
Describe data pipelines and tools
Build data pipelines using Python
Cieľová skupina
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
Certifikát
Na dotaz.
Hodnotenie
Organizátor
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