Product Management
❮ ❮ ❮ back forward ❯ ❯ ❯ A look at the business model from the product manager's point of view CANVAS 13 - Great guide on the business model, from the product manager's point of view 1 – Customer Problem 2 – Customer Segments 3 – Value Propositions Value Proposition Formulation Map 4 – Customer
Product Management
❮ ❮ ❮ back forward ❯ ❯ ❯ A look at the business model from the product manager's point of view CANVAS 13 - Great guide on the business model, from the product manager's point of view 1 – Customer Problem 2 – Customer Segments 3 – Value Propositions Value Proposition Formulation Map 4 – Customer
Product Management
❮ ❮ ❮ back forward ❯ ❯ ❯ A look at the business model from the product manager's point of view CANVAS 13 - Great guide on the business model, from the product manager's point of view 1 – Customer Problem 2 – Customer Segments 3 – Value Propositions Value Proposition Formulation Map 4 – Customer
Product Management
❮ ❮ ❮ back forward ❯ ❯ ❯ A look at the business model from the product manager's point of view CANVAS 13 - Great guide on the business model, from the product manager's point of view 1 – Customer Problem 2 – Customer Segments 3 – Value Propositions Value Proposition Formulation Map 4 – Customer
Product Management
❮ ❮ ❮ back A look at the business model from the product manager's point of view CANVAS 13 - Great guide on the business model, from the product manager's point of view 1 – Customer Problem 2 – Customer Segments 3 – Value Propositions Value Proposition Formulation Map 4 – Customer Relationships
Data Analitics Study Notes
Guidelines and pro tips Refer to the table below for recommended guidelines and style checks for headlines, subtitles, labels, and annotations in your data visualizations. Think of these guidelines as guardrails to prevent your visualizations from becoming too crowded or busy. This can confuse or distract the audience with unnecessary
Data Analitics Study Notes
Introduction to Data Visualization and Design Principles
Data Analitics Study Notes
© Google This text outlines the purpose, examples, and limitations of six data validation types. The first five are linked to the data itself: type, range, constraint, consistency, and structure. The sixth type pertains to application code validation that accepts user input. As a junior data analyst, you may not conduct
Data Analitics Study Notes
* As a data analyst, familiar tools and processes are frequently used, but learning new ones is essential for growth. * SQL can significantly improve efficiency when pulling data and conducting analysis. * Spreadsheets, conditional formulas, the SUMPRODUCT function, and pivot tables are useful tools for performing calculations in data analysis. * Pivot tables
Data Analitics Study Notes
WarehouseWarehouse.csv484 Bytesdownload-circleOrdersOrders.csv352 KBdownload-circle HAVING function Allows you to add a filter to your query instead of the underlying table that can only be used with aggregate functions CASE function Returns records with your conditions by allowing you to include if/then statements in your query Aliasing When you
Data Analitics Study Notes
Open BigQuery and create a free account there, upload bigquery-public-data and select new_york_citibike. Scenario Review the following scenario. Then complete the step-by-step instructions. You work for an organization that is responsible for the safety, efficiency, and maintenance of transportation systems in your city. You have been asked to
Data Analitics Study Notes
Common JOINs * INNER JOIN: a function that returns records with matching values in both tables * LEFT JOIN: a function that returns all the records from the left table (first mentioned) and only the matching records from the right table (second mentioned) * RIGHT JOIN: a function that returns all records from