Big Data Analyses, Anomaly Detection, and Predictive Models

Name: Big Data Analyses, Anomaly Detection, and Predictive Models
Author: Chintan Thakkar

Learn about infrastructure for Big Data on the public cloud .

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Course: On-Demand

(bright music) Welcome to big data analyses, anomaly detection and predictive models. In these lessons, you'll learn the various types of analysis that can be performed using big data and diagnostic versus descriptive analytics. You'll also acquire knowledge about anomaly detection versus predictive models using big data. Diagnostic analysis is a technique to identify why an issue happens. You're using the large data set and creating the analytics. Once the analytics finishes execution, then it can solve the use case for you. It performs a deep dive into the data and identifies the root cause. An example would be a power plant that isn't generating the expected output. You can collect all the metrics data from the power plant and then generate the analytics. The analytics will run and the output is generated, helping you diagnose the issue. Here's the step-by step-process for the diagnostic analytics. Step one, work with a business analyst to identify the actual problem statement. Step two, analyze the data set and identify the appropriate data for the analytics. Step three, collect all the data. Step four, implement the analytics. Step five, test analytics against the test data and validate the results. Step six, run analytics against the actual data sets and diagnose the issue. The analysis is often performed using data mining, or the data drill down process. The data processing algorithm takes the actual raw data, and then generates the output. The output will help you to identify the actual issue really related to the data set. There are several benefits of using diagnostic analytics. It helps you to diagnose the root issue or get logical reasoning based on actual raw data. It can help you perform a detailed analysis of an issue and come up with a solution. It works very well with the BI platform and generates customizable visualization from the data. It provides specific answers to a business problem. Here are a few more use cases that can be solved using diagnostic analytics. Employee satisfaction. You can collect various data from an employee survey, and then run the analytics on this input data. The analytics provide various diagnostic results that can help the organization identify any issues and retain more employees. Health analytics. Running analytics on health data can help health care providers track the spread of illnesses, find correlations between health conditions, or narrow down a diagnosis. Product marketing. A marketing team can investigate their social media data and determine highly performing products and poorly performing products. The team can then assess the market's poorly performing products and brainstorm ways to improve sales. Sales team. The sales team can use these analytics to determine how to identify the products that aren't performing well in the market.

Beginner Provider : Chintan Thakkar 4 Lessons · 16m in Arabic, German, English, Spanish, French, Portuguese, Urdu, Chinese

Course Description

Diagnostic analysis is a technique used to identify why an issue happens. When you are working with large data sets and creating the analytics, you can use it to identify the root cause. In this Big Data Analyses, Anomaly Detection, and Predictive Models course you’ll learn the various types of analysis that can be performed using Big Data and diagnostic vs. descriptive analytics. You’ll also acquire knowledge about anomaly detection vs. predictive models using Big Data.

Big data analytics is created using historical data from past events, which could have happened anywhere from a few days ago to several months ago. It allows organizations to analyze the data and then predict a future outcome. Behavioral analytics help you answer the question of “what happened” in most situations, and can increase an organization's profit by proper analysis. The skills you learn in this course can help you communicate the changes that happen over time and provide you with trends for the future. It can also help companies learn what future roadblocks to plan for.

What You'll Learn

Perform diagnostic analysis with Big Data to identify why an issue happens and find root causes
Distinguish diagnostic analytics from descriptive analytics
Discuss predictive models and how they use historical data to predict future outcomes
Identify anomalies in Big Data using anomaly detection techniques
Apply trend analysis using Big Data to communicate changes over time
Use behavioral analytics to answer the question of what happened in most situations

Key Takeaways

Diagnostic analysis is a technique used to identify why an issue happens and can pinpoint the root cause in large data sets.
Big data analytics is created using historical data from past events, allowing organizations to analyze data and predict a future outcome.
Behavioral analytics help answer the question of what happened in most situations and can increase an organization's profit through proper analysis.
The skills taught help communicate changes that happen over time and provide trends for the future.
Big Data analysis can help companies learn what future roadblocks to plan for.

Frequently Asked Questions

What will I learn in this course?

You will learn the various types of analysis that can be performed using Big Data, the difference between diagnostic and descriptive analytics, and the difference between anomaly detection and predictive models using Big Data.

What topics do the lessons cover?

The lessons cover Trend Analysis Using Big Data, Descriptive Analysis Using Big Data, Anomaly Detection Using Big Data, and Predictive Models Using Big Data.

What skills will I gain from this course?

You will gain skills in diagnostic skills, anomaly detection, Big Data analytics, data analysis, diagnostic analysis, and predictive analytics.

How can the skills from this course help an organization?

The skills can help communicate the changes that happen over time, provide trends for the future, help companies learn what future roadblocks to plan for, and increase an organization's profit through proper analysis.

What is diagnostic analysis?

Diagnostic analysis is a technique used to identify why an issue happens, and when working with large data sets it can be used to identify the root cause.

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Society for Human Resource Management (SHRM®)

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KnowledgeCity is approved by SHRM as a Recertification General Provider to offer SHRM-CP or SHRM-SCP professional development credits (PDCs). By taking the courses approved by SHRM, KnowledgeCity can award SHRM Professional Development Credits (PDCs) for HR knowledge and competency programs related to the SHRM Body of Applied Skills and Knowledge™ (the SHRM BASK™).