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Apache Airflow is an open-source workflow management platform for data engineering pipelines. It started at Airbnb in October 2014 [2] as a solution to manage the company's increasingly complex workflows. Creating Airflow allowed Airbnb to programmatically author and schedule their workflows and monitor them via the built-in Airflow user interface.
Apache Superset is an open-source software application for data exploration and data visualization able to handle data at petabyte scale ().The application started as a hack-a-thon project by Maxime Beauchemin (creator of Apache Airflow) while working at Airbnb and entered the Apache Incubator program in 2017. [1]
Supported data models (conceptual, logical, physical) Supported notations Forward engineering Reverse engineering Model/database comparison and synchronization Teamwork/repository Database Workbench: Conceptual, logical, physical IE (Crow’s foot) Yes Yes Update database and/or update model No Enterprise Architect
These platforms — such as Amazon, Airbnb, Uber, Microsoft and Google — serve as intermediaries between various groups of users, enabling interactions, transactions, collaboration, and innovation. The platform economy has experienced rapid growth, disrupting traditional business models and contributing significantly to the global economy. [2]
Airbnb, Inc. (/ ˌ ɛər ˌ b iː ɛ n ˈ b iː / AIR-BEE-en-BEE, an abbreviation of its original name, "Air Bed and Breakfast" [5]) is an American company operating an online marketplace for short-and-long-term homestays and experiences in various countries and regions.
Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g., using data modeling:
Statistical inference makes propositions about a population, using data drawn from the population with some form of sampling.Given a hypothesis about a population, for which we wish to draw inferences, statistical inference consists of (first) selecting a statistical model of the process that generates the data and (second) deducing propositions from the model.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.