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Big Data Engineering Course

Big Data Engineering Course
from 4 to 360h flexible workload
certificate recognized by MEC

What will I learn?

Unlock the power of data with our Big Data Engineering Course, designed for Business Intelligence professionals eager to excel. Dive into data storage solutions like HDFS and cloud options, master scalable data pipeline architectures, and explore real-time processing with Apache Kafka. Gain hands-on experience with prototyping, implementation, and documentation, while overcoming real-world challenges. Elevate your skills with cutting-edge frameworks like Apache Spark and Flink, and transform data into actionable insights. (Tsamaya mo go itseng thata ka tsamaiso ya data ka thuto ya rona ya Big Data Engineering, e diretsweng batho ba ba itseng ka Business Intelligence go tokafatsa bokgoni jwa bone. Ithute ka ditsela tsa go boloka data jaaka HDFS le cloud options, itse go aga dipipeline tsa data tse di ka dirisiwang ke batho ba bantsi, mme o ithute ka real-time processing ka Apache Kafka. O tla nna le boitemogelo ka go itirela dilo, go di tsenya tirisong, le go kwala ditokomente, mme o fenye dikgwetlho tsa botshelo. Tokafatsa bokgoni jwa gago ka diframework tse di gaisang jaaka Apache Spark le Flink, mme o fetole data go nna dintlha tse di ka dirisiwang.)

Elevify advantages

Develop skills

  • Master HDFS: Efficiently store and manage big data with HDFS expertise. (Itseng HDFS: Boloka mme o tsamaise big data ka botswerere ka HDFS.)
  • Design Pipelines: Create scalable data pipelines for seamless data flow. (Aga Dipipeline: Tlhama dipipeline tsa data tse di ka dirisiwang ke batho ba bantsi go thusa gore data e tsamaye sentle.)
  • Real-time Processing: Implement real-time analytics for instant insights. (Real-time Processing: Tsenya tirisong real-time analytics go bona dintlha ka bonako.)
  • Apache Spark Skills: Harness Apache Spark for powerful data processing. (Botswerere jwa Apache Spark: Dirisa Apache Spark go tsamaisa data ka maatla.)
  • Kafka Integration: Integrate Kafka for robust data ingestion solutions. (Go Kopanya Kafka: Kopanya Kafka go bona ditsela tse di thata tsa go gopela data.)

Suggested summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

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EmersonPolice Investigator
The course was essential to meet the expectations of my boss and the company where I work.
SilviaNurse
Very great course. Lots of rich information.
WiltonCivil Firefighter

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