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Develop Big Data Pipelines with R & Sparklyr & Tableau

4.7

(23 students)
Last updated:November 5, 2024
Language:English

Develop Big Data Pipelines with R & Sparklyr & Tableau

4.7

(23 students)

Rated Excellent on

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Overview

This course offers a comprehensive guide to building and managing big data pipelines using R, Sparklyr, and Tableau. As organizations increasingly rely on data to drive decisions, the need for efficient data processing and visualization is more critical than ever. This course will guide you through each stage of a big data pipeline, from data ingestion and cleaning to transformation, modeling, and visualization. You’ll start by learning how to leverage R and Sparklyr for handling large datasets, implementing transformations, and performing distributed computing. Following that, you’ll dive into Tableau for data visualization, creating dashboards and reports that provide actionable insights. This practical course is perfect for those who want to build a complete skill set for managing and analyzing big data, helping them to stand out in data science and analytics roles.

Learning Outcomes

By the end of this course, you will be able to:

  • Understand the fundamentals of big data pipelines.
  • Develop skills in data ingestion and cleaning using R.
  • Apply Sparklyr for distributed data processing.
  • Master data transformations and modeling techniques.
  • Create insightful visualizations in Tableau.
  • Build end-to-end data workflows.
  • Optimize data pipeline performance.
  • Communicate data insights effectively to stakeholders.

How will I get my certificate?

You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.

Who is This course for?

This course is designed for data analysts, aspiring data engineers, and professionals interested in big data who want to deepen their expertise in building data pipelines. It’s suitable for anyone aiming to add data engineering skills to their portfolio.

Requirements

A basic understanding of R programming and data analytics is recommended. Familiarity with data visualization tools like Tableau is beneficial but not essential, as this course includes beginner-friendly modules. A computer with internet access and the latest versions of R, Sparklyr, and Tableau is required.

Career Path

  • Data Engineer
  • Data Analyst
  • Big Data Specialist
  • Data Pipeline Developer
  • Business Intelligence Developer

Course Curriculum

  • 5 sections
  • 18 lectures
  • 2 hours, 47 minutes total length
Expand all sections
  • video Introduction
    00:12:00

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This course includes:

  • Duration:
    2 hours, 47 minutes
  • Access:
    1 year access
  • Units:
    18
  • Level:
    Intermediate
  • CPD Points:
    10
  • Certificate:
    Yes