Ch 3: Data Mining Fundamentals

About This Chapter

With the lessons, you'll learn about the purpose, basic techniques, and applications of data mining. Explore how you can use data mining in your business reports, in social media, and for other purposes.

Data Mining Fundamentals: Chapter Summary

In today's business world, technology can gather vast amounts of data, but that leaves us with the problem of what to do with all of this assemble information. Data mining processes can help to summarize information or discover patterns and relationships within data sets. These processes can often appear very technical or complex, but his chapter has been designed to reduce your anxiety about data mining. Our easy-to-follow lessons help you get a better grasp on data mining methods and techniques, including how to perform them, what data mining tools to use, and so forth.

You can develop or improve your data mining skills any time, day or night, by logging into your user dashboard on our site. Your personalized dashboard keeps your information organized, shows you what lessons you've recently reviewed, and highlights your most recent quiz scores. As you study up on the basics of data mining, your dashboard also recommends related chapters that may help expand your technical skills even further.

This chapter goes over a full range of topics that get you ready to do the following:

  • Define the process and fundamentals of data mining
  • Explain the applications of data mining
  • Compare the pros and cons of data mining
  • Differentiate data mining from data warehousing
  • Examine data mining techniques
  • Use data mining in Excel
  • Offer examples of data mining algorithms
  • Share the data mining association rules
  • Show the purposes of a decision tree algorithm
  • Determine how data mining can be used with social media
  • Establish how data mining can benefit healthcare
  • Outline the data integration process in data mining

13 Lessons in Chapter 3: Data Mining Fundamentals
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.

Basics of Data Mining

2. Basics of Data Mining

With the advancements of more capable computers, data mining has emerged as a counterweight to outward looking trends in big data. Data mining focuses on what is available to a company.

Data Mining: Advantages & Disadvantages

3. 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: Applications & Examples

4. Data Mining: Applications & Examples

Data mining has a number of applications that can help companies make the most out of the information that they already have. This lesson demonstrates that as well as provides examples.

Data Warehousing and Data Mining: Information for Business Intelligence

5. Data Warehousing and Data Mining: Information for Business Intelligence

Collections of databases that work together are called data warehouses. This makes it possible to integrate data from multiple databases. Data mining is used to help individuals and organizations make better decisions.

Data Mining Techniques

6. 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 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.

Data Mining: Algorithms & Examples

8. 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.

Association Rules in Data Mining

9. 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.

Decision Tree Algorithm in Data Mining

10. 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.

Social Media & Data Mining

11. 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.

Benefits of Data Mining in Healthcare

12. Benefits of Data Mining in Healthcare

Data Mining is exactly what it sounds like - mining the ocean of data we have to obtain meaningful conclusions. Healthcare is only one of many industries benefiting from data mining. In this lesson, we'll learn what data mining is, its advantages and how it is applied to the healthcare industry.

Data Integration in Data Mining

13. 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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Other Chapters

Other chapters within the Big Data Tutorial & Training course

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