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Data Science

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Data Analysis

Before CRM, PA, MMP Tool Implementation, Must-Know Data Taxonomy Design Know-How (with 5 Industry Examples)

This lecture is structured to be easily understood even by those new to data taxonomy. Data taxonomy design is essential when implementing CRM marketing tools like Braze, analytics tools such as Mixpanel and Amplitude, and MMP tools including Airbridge and AppsFlyer, and establishing their environments. By taking this lecture, you will learn industry-specific practical standards and application methods, enabling you to directly build data-driven marketing automation and accurate analysis systems. This is a practical guide that organizations working with data must take.

3 learners are taking this course

  • kdaejung
데이터텍소노미
디지털마케팅
amplitude
데이터분석
Braze
Digital Marketing
Amplitude

What you will learn!

  • Essential task for our service data analysis. Hands-on Learning of Data Taxonomy Design

  • Easy-to-follow Data Classification: From Principles to Practice!

  • Universal Data Language Unification: Imparted!

  • Learn how to build a systematic analysis environment without data confusion.

If you miss out on designing your data taxonomy now, you’ll fall behind your competitors 🤔

Are you using the vast amounts of data being accumulated in your organization properly?

Companies without data taxonomy tend to only collect data and interpret it incorrectly, analysis time increases, collaboration is misaligned, and eventually automation, personalization, and AI end up being just a pie in the sky. Leading companies at home and abroad are already ahead of their competitors through consistent data language and systems.

We provide everything from real-life cases of 'data chaos' in each business department, such as marketing, CRM, and development, to templates and practical application checklists for each industry, such as e-commerce/travel/platform. If you want to take your organization's data quality and automation competitiveness to the next level through systematic data taxonomy design, now is the time to start.

Features of this course

📌 A complete disclosure of the taxonomy design process used in the field to utilize Braze, Mixpanel, Amplitude, etc.! You can acquire design methods that can be applied immediately to the field with just one listen.

📌 Includes cases from various industries such as e-commerce, travel, and content! It doesn't just contain vague explanations of concepts, but also contains actual cases.

📌 From data naming rules to management systems, a complete A~Z guide! One lecture will take away your fear of taxonomy design.

I recommend this to these people

Marketers and data analysts who have experienced confusion due to constant differences in data interpretation across departments.

Anyone who has ever wondered, “Why are the interpretations of our team and the development team different?”

Service/platform operators who are already collecting a lot of data, but analysis and reporting always take a lot of time and money.

“Can’t we manage our company’s data more efficiently?” are the concerns of practitioners.

Have you ever felt the need to organize your data but were at a loss as to how to implement it?

PMs, POs, and data managers always feel that the data definitions, event mapping, and data guide documents required for practical work are insufficient.

After class

  • You can build a consistent data system without data duplication, omission, or confusion.


  • It can fundamentally solve the problem of data interpretation inconsistency within an organization.

  • You can actually apply the method of designing a customized data taxonomy for each service and industry.

  • You will gain the ability to create data definitions and guide documents that anyone can use out of the box.

  • It can dramatically increase the efficiency of all data-based practices, including analysis, automation, and marketing.

Recommended for
these people

Who is this course right for?

  • Need a unified business performance analysis system across Marketing, Development, and Data teams?

  • Practitioners interested in data-driven marketing automation

  • Planner facing internal data inconsistency.

  • Seeking to improve data analysis accuracy and reliability.

  • Manager needing integrated multi-channel data management

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Reviews

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Answers

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3 lectures

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