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Ch 4: Elements of Data Mining

About This Chapter

Use this chapter on the elements of data mining to make sure your employees understand these concepts fully. Our corporate training chapter is available to your teams around the clock which allows for complete flexibility.

Elements of Data Mining - Chapter Summary

We've included short lessons in this chapter on the elements of data mining that you can review with your employees at any time. Topics presented here include the process of data mining, the techniques used and decision tree algorithms. Because this chapter is self paced, your employees can work independently at their own speeds until they feel confident with this material.

How It Helps

  • Covers applications: Many applications of data mining are presented, from social media to Excel, giving your teams plenty of related information.
  • Develops competence: Employees who understand these data mining concepts become more capable of carrying out their job responsibilities.
  • Explains data mining techniques: This resource is designed to teach the elements of data mining and related techniques to individuals within your company.

Skills Covered

Our handy chapter is designed to ensure your employees know how to:

  • Define data mining and interpret its process
  • Outline the advantages and disadvantages of data mining
  • Discuss the techniques involved in data mining
  • Detail data mining algorithms
  • Explain the decision tree algorithm as it pertains to data mining
  • Describe data mining association rules
  • Identify how data mining works in Excel
  • Outline social media and data integration

9 Lessons in Chapter 4: Elements of Data Mining
Test your knowledge with a 30-question chapter practice test
What is Data Mining? - Definition & Process

1. What is Data Mining? - Definition & Process

While big data may be getting a lot of buzz, for many companies data mining is a more attractive option. In this lesson, we learn what exactly data mining is, and its applications, from TV sales to baseball.

Data Mining: Advantages & Disadvantages

2. Data Mining: Advantages & Disadvantages

While many people may be excited about the opportunities that data mining can provide companies, there must still be attention paid to some of the disadvantages of this technique.

Data Mining Techniques

3. Data Mining Techniques

Data mining is a helpful skill for a company to be able to use, but how exactly is it done? This lesson looks at the most basic part of data mining techniques, which are the relationships that data miners hope to find.

Data Mining: Algorithms & Examples

4. Data Mining: Algorithms & Examples

In this lesson, we'll take a look at the process of data mining, some algorithms, and examples. At the end of the lesson, you should have a good understanding of this unique, and useful, process.

Decision Tree Algorithm in Data Mining

5. Decision Tree Algorithm in Data Mining

Decision trees, and data mining are useful techniques these days. In this lesson, we'll take a closer look at them, their basic characteristics, and why they are so useful.

Association Rules in Data Mining

6. Association Rules in Data Mining

Data Mining is an important topic for businesses these days. In this lesson, we'll take a look at the process of Data Mining, and how Association Rules are related. At the end of the lesson, you should have a good understanding of both.

Data Mining in Excel

7. Data Mining in Excel

Mining implies digging, and using Excel for data mining lets you dig for useful information - hidden gems in your data. In this lesson, we'll define data mining and show how Excel can be a great tool for finding patterns in information.

Social Media & Data Mining

8. Social Media & Data Mining

While you may think of social media as a place to post photographs or congratulate people on a birthday or a promotion, many companies think of it as a gold mine of information about potential clients.

Data Integration in Data Mining

9. Data Integration in Data Mining

We want our information to give us more than simply the sum of its parts. We want information to be seamless and timely. We want to learn things from the information we collect, and we want the information to be accurate and relevant. In this lesson, we'll look at data mining and data integration and how the two are related.

Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
Not Taken
Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
Not Taken

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