Enrollments for individual courses are no longer available for this program. Visit our Data Product Manager page to learn more about enrolling in the complete Nanodegree program.
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Prior Data Analysis & Product Management Experience Recommended
Begin by understanding the importance and need of data pipelines and the various components of data pipelines, and learn how to organize data pipeline components to automate end-to-end data flow. Then, create conceptual data pipelines and conceptualize classic data problems that can be addressed by data pipelines.
Learn about primary data consumers, their data needs, and how to identify data consumers in an organization and their relevant data use cases. Develop an understanding of the components of a relational data model and apply relational data models to business scenarios.
Learn how to create event data models and implement them to get business insights, and use data collected from event models to calculate product KPIs. Identify primary data producers in an organization and distinguish between backend data producers (SaaS, ERPs, and data stores) while also differentiating between types of data (structured vs. semi-structured vs. unstructured).
Understand the difference between ETL and ELT processes, distinguish between batch processing and stream processing, and learn to select the appropriate data processing components for a product based on data needs. Differentiate between a data warehouse and data lake, and between SQL and NoSQL databases, and determine the appropriate data storage components for a particular data infrastructure of a product based on data needs. Assess capabilities of various data warehousing options (build vs buy, cloud vs on-prem, open source vs proprietary, and insource vs outsource) to make strategic decisions for data infrastructure, and evaluate data security and compliance product use cases (PII, PCI, HIPAA, GDPR, and CCPA).
In this project, you will act as a data product manager for Flyber, a fictional flying-taxi service, and create a data strategy to not only handle the massive amount of incoming data, but also process it to gain business insights. First, you will define the data needs of primary business stakeholders within the organization and create a data model to ensure the data collected supports those needs. Then, you will perform the necessary extraction and transformation of the data to make the data relevant to answer business questions. Finally, you will interpret data visualizations to understand the scale of Flyber’s data growth and choose an appropriate data warehouse to enable that growth.
PRODUCT MANAGER AT EXPEDIA
Vaishali has spent 12+ years in the tech eco-system with roles spanning product management and product development to content writing to coding. She is experienced in building platforms, high performance start-up divisions, streamlined operations, and managing customer expectations.