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Identifying and Understanding Business Problems for Data Scientists

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Duration

26m

level

Intermediate

Course Creator

Pinal Dave

Last Updated

16-Jan-24

Identifying and defining business challenges is crucial for developing data science solutions and aligning stakeholders. This course teaches you to recognize key problems that data science can address.

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Diagnosing business challenges involves defining the problem, pinpointing its origins, assessing data science as a solution, shaping it into data objectives, and creating a focused, clear problem statement for stakeholder consensus. In this course, Identifying and Understanding Business Problems for Data Scientists, you’ll gain the ability to effectively recognize, understand, and define business problems that can be addressed with data science. First, you’ll explore how to uncover hidden business challenges through data trends and stakeholder engagement. Next, you’ll discover the methods to apply data science to create impactful business solutions. Finally, you’ll learn how to assess the readiness of a business problem for a data science approach and articulate it into clear, data-centric objectives. When you’re finished with this course, you’ll have the skills and knowledge of business problem identification and analysis needed to confidently translate business issues into data science projects that deliver tangible results.
Author Name: Pinal Dave
Author Description:
Pinal Dave is an SQL Server Performance Tuning Expert and independent consultant with over 22 years of hands-on experience. He holds a Master of Science degree and numerous database certifications. Pinal has authored 14 SQL Server database books and 81 Pluralsight courses. To freely share his knowledge and help others build their expertise, Pinal has also written more than 5,800 database tech articles on his blog at https://blog.sqlauthority.com.

Table of Contents

  • Course Overview
    1min
  • Diagnosing Business Challenges
    11mins
  • Strategizing Project Execution
    13mins

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Identifying and Understanding Business Problems for Data Scientists
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