Data Science for Business: Data Mining Process and CRISP DM (Cognitir Learning)

Visit online.cognitir.com to learn about similar topics from the comforts of your home. For additional free resources and information about training courses, please visit www.cognitir.com.
Cognitir offers introductory and interactive training courses on topics including programming, data analytics, machine learning, data visualization, product management, and more. Our courses are specifically designed for non-technical business and finance professionals.
This lesson provides an introduction to the data mining process with a focus on CRISP-DM.
This video was created by Cognitir (formerly Import Classes). Cognitir is a global company that provides live training courses to business & finance professionals globally to help them acquire in-demand tech skills.

[@tariqalsulaimani8161]

1- Business Understanding 1:20
1.1- Determine business objectives.
1.2- Assess the situation.
1.3- Determine data mining goals.
1.4- Produce the project plan.
2- Data Understanding 2:10
2.1- Collect initial data.
2.2- Describe the data.
2.3- Explore the data.
2.4- Verify the quality of the data.
3- Data Preparation 3:13
3.1- Select the data.
3.2- Clean the data.
3.3- Construct the data.
3.4- Integrate the data.
Examples:
a- Converting data to tabular format.
b- Removing or inferring missing values.
c- Converting data to different types.
d- Scaling numerical values.
4- Modeling 4:15
4.1- Select the modeling technique.
4.2- Generate tests for model robustness.
4.3- Build the model.
4.4- Assess the model.
5- Evaluation 5:13
5.1- Evaluate the results.
5.2- Review the process.
5.3- Determine the next steps.
6- Deployment 6:36
6.1- Plan the deployment.
6.2- Plan the monitoring and maintenance.
6.3- Produce the final report of values.
6.4- Review the project.

[@Bestlifeshorts07]

i have a questions sir ?

[@Swarna_222]

thank you.

[@Importclasses]

Thanks for the breakdown!

[@Importclasses]

This is a really helpful breakdown - thank you, Tariq!

[@MutiMichaelPhoya]

Brilliant summary. Thanks.

[@asfahaanmirza2367]

Good one!

[@cmanna285]

So helpful.

[@gcvictorgc]

Thanks, that was a really good introduction

[@Importclasses]

Many thanks, Victor!

[@kristinaconk7973]

Great!

[@ashnaprasannan3588]

Really useful😍😍

[@Luke-Nightingale]

Bravo

[@sarachoukairi5497]

thank you, it helps me a lot

[@Importclasses]

Glad to hear that Sara!

[@kimlebouton]

Helpful. Thank you. Remember SAS is SASsy, not ever spelled out like SAP.

[@Importclasses]

Thanks! :)

[@nowxdi7524]

Can you please tell me what is the best data mining process methodology (CRISP-DM, SEMMA, KDD) that can be used in heart attack prediction and why?

[@thomasshakelton]

Now do we call it data or data?

[@Importclasses]

Hi Thomas - happy to help, but can you please clarify what you mean? Sorry for the delay - our notifications were turned off and we didn't see this comment.

[@nancyanderson5413]

What a bunch of baloney, when Data Scientist that work in the Research and clinical areas where the format of the data and the process to get data is so regulated and strict, all this obvious yara yara is so boring. I hate when they talked to poeple like we are idiots.

[@Importclasses]

Hi Nancy - we are very sorry that you didn't like our video - that's a huge bummer! As we are always looking to improve and offer best-in-class content, do you have any specific recommendations for us? We are happy to integrate your suggestions in future videos.
Thank you very much for your feedback and have a wonderful rest of the week!