• Online, Self-Paced
Course Description

Explore how statistical analysis can turn raw data into insights, and then examine how to use the data to improve business intelligence, in this 10-video course. Learn how to scrutinize and perform analytics on the collected data. The course explores several approaches for identifying values and insights from data by using various standard and intuitive principles, including data exploration and data ingestion, along with the practical implementation by using R. First, you will learn how to detect outliers by using R, and how to compare simple linear regression models, with and without outliers, to improve the quality of the data. Because today's data are available in diversified formats, with large volume and high velocity, this course next demonstrates how to use a variety of technologies: Apache Kafka, Apache NiFi, Apache Sqoop, and Wavefront (a program for simulating two-dimensional acoustic systems) to ingest data. Finally, you will learn how these tools can help users in data extraction, scalability, integration support, and security.

Learning Objectives

Explore how statistical analysis can turn raw data into insights, and then examine how to use the data to improve business intelligence, in this 10-video course. Learn how to scrutinize and perform analytics on the collected data. The course explores several approaches for identifying values and insights from data by using various standard and intuitive principles, including data exploration and data ingestion, along with the practical implementation by using R. First, you will learn how to detect outliers by using R, and how to compare simple linear regression models, with and without outliers, to improve the quality of the data. Because today's data are available in diversified formats, with large volume and high velocity, this course next demonstrates how to use a variety of technologies: Apache Kafka, Apache NiFi, Apache Sqoop, and Wavefront (a program for simulating two-dimensional acoustic systems) to ingest data. Finally, you will learn how these tools can help users in data extraction, scalability, integration support, and security.

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Data Administration