Hi there 👋

I have divided this Use Case into 4 chapters:

1. Starting the adventure 🚀 We will start this journey by using Objectives and Key Results (OKR) and the selection of appropriate Key Performance Indicators (KPI). Next we create an Instrumentation Plan, so that we are able to gather the right information to make good data-driven decisions. As a result we build our Data Pipeline with AWS.

#aws #design_thinking #okr #data_strategy #business_dev

2. Analytics for the win 📊 It is hard to make decisions without looking into data. Fortunately we have taxi ride data available. Furthermore, we have had interviews with users to understand how they think about our business idea. We already had a look into it while we discussed our OKR and the data strategy in the first chapter, because data is the basis for our decisions. This chapter is divided in an initial EDA part including data cleaning 2.1 and an analytics 2.2 part.

TechStack: Python, Pandas, PandasProfiler, Numpy, Matplotlib, Seaborn, Tableau

3. Impact of Privacy Rights 📙 As a Product Manager we think interdisciplinary. That means we also have to deal with legal implications on our product. We will find out if privacy rights apply to our planned actions. If so, what exactly do we need to consider? Is there anything extra special we need to keep in mind? I will use this part of the use case as well to show areas of overlap with my previous job as an IT consultant. Please be aware that this is no legal advice. This is just for the purpose of showcasing my skillset.

#iso2700x #itil #gdpr #dpo #itgc

4. Applying iterative design principles to the live product 🔄 The data gave us some good insights that enables us to shape our operations. We also considered the requirements to use personal data in line with data privacy rights. The market introduction of our product went well and now we would like improve our product continously.

TechStack: Tableau

#design_thinking #funnel_analysis #ab_testing #hypothesis_testing