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Raw Data to Insights: Data Ingestion & Statistical Analysis

Raw Data to Insights: Data Ingestion & Statistical Analysis


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

To master data science it is important to take raw data and turn that into insights. In this course you will explore the concept of statistical analysis and implement data ingestion using various technologies including NiFi, Sqoop, and Wavefront.



Expected Duration (hours)
0.9

Lesson Objectives

Raw Data to Insights: Data Ingestion & Statistical Analysis

  • describe how we can use statistical analysis to add value to data
  • recorgnize the concept of data correction along with the various essential approaches of implementing data correction which includes data detection localization, imputation and correction
  • demonstrate how we can facilitate outlier detection using R
  • describe the layered architecture of data from the perspective of data ingestion, prcoessing, and visualization
  • list and compare the various essential data ingestion tools that we can use to ingest data
  • set up Kafka and Apache NiFi to ingest data
  • demonstrate the steps involved in ingesting data from databases to Hadoop clusters using Sqoop
  • demonstrate how we can ingest data using WaveFront
  • detect outliers using R and ingest data using Apache NiFi and WaveFront
  • Course Number:
    it_dsrdindj_01_enus

    Expertise Level
    Intermediate