Raw Data to Insights: Data Ingestion & Statistical Analysis
Data Science
| Intermediate
- 10 Videos | 53m 30s
- Includes Assessment
- Earns a Badge
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.
WHAT YOU WILL LEARN
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describe how we can use statistical analysis to add value to datarecorgnize the concept of data correction along with the various essential approaches of implementing data correction which includes data detection localization, imputation and correctiondemonstrate how we can facilitate outlier detection using Rdescribe the layered architecture of data from the perspective of data ingestion, prcoessing, and visualizationlist and compare the various essential data ingestion tools that we can use to ingest data
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set up Kafka and Apache NiFi to ingest datademonstrate the steps involved in ingesting data from databases to Hadoop clusters using Sqoopdemonstrate how we can ingest data using WaveFrontdetect outliers using R and ingest data using Apache NiFi and WaveFront
IN THIS COURSE
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1.Course Overview1m 35sUP NEXT
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2.Statistical Analysis7m 38s
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3.Data Correction6m 34s
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4.Outlier Detection5m 6s
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5.Data Architecture Pattern4m 52s
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6.Data Ingestion Tools4m 30s
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7.Kafka and Apache NiFi10m 32s
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8.Apache Sqoop Ingest5m 9s
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9.Ingest Using WaveFront3m 10s
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10.Exercise: Detecting Outliers and Ingesting Data4m 24s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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