What Is Data Preparation?

What Is Data Preparation?

Analytics Canvas Tutorial: What is Data Preparation? nModal Solutions Inc. All Rights Reserved Analytics Canvas Tutorial: Course Introduction What is Data Preparation? Myth: Data preparation is a time-consuming manual process that is heavily prone to errors. Fact: Data preparation, when done with the right tools, empowers users to maintain control, while accelerating the process and providing a better foundation for decision-making. Better decision- making starts with better data. To an extent, data preparation is synonymous with, or related to: data pre-processing, data scrubbing, business intelligence, data cleansing/cleaning, and ETL (“Extract, Transform, and Load”). In this course, we are going to take a broad view of data preparation. Here is the definition we will work with: data preparation is a step in the data analysis process, in which data from one or more sources is cleaned, and transformed and enriched to improve its quality prior to its use. Data- driven decisions Knowledge discovery Data Science Descriptive analytics and reporting Data preparation Data Sources Figure 1: Data Preparation in the Data Analysis Process The figure above illustrates the position of the data preparation in the data analysis process. It is easy to see the importance of data preparation - as the foundation of business decisions. nModal Solutions Inc. All Rights Reserved Analytics Canvas Tutorial: Course Introduction Conclusion Thank you for reading this tutorial. We invite you to continue with the tutorial training to learn more about using Analytics Canvas. nModal Solutions Inc. All Rights Reserved .

View Full Text

Details

  • File Type
    pdf
  • Upload Time
    -
  • Content Languages
    English
  • Upload User
    Anonymous/Not logged-in
  • File Pages
    3 Page
  • File Size
    -

Download

Channel Download Status
Express Download Enable

Copyright

We respect the copyrights and intellectual property rights of all users. All uploaded documents are either original works of the uploader or authorized works of the rightful owners.

  • Not to be reproduced or distributed without explicit permission.
  • Not used for commercial purposes outside of approved use cases.
  • Not used to infringe on the rights of the original creators.
  • If you believe any content infringes your copyright, please contact us immediately.

Support

For help with questions, suggestions, or problems, please contact us