The FAIR Wizard is a tool that helps researchers and data stewards create data management plans (DMPs) easily, efficiently, and in a FAIR manner.
Data stewards can easily capture the knowledge, including required project data and decisions in knowledge models that are then turned into per-project questionnaires to be filled by researchers. The questionnaires guide researchers through the process using recommendations, FAIR metrics indications, and only showing relevant questions based on previous answers.
Once the questionnaire is completed, a DMP can be easily generated using a selected template and output format. The document is then stored in FAIR Wizard for easy access and future reference. This is especially helpful because many funding agencies now require a DMP for their application process.
But the benefits of using FAIR Wizard go beyond just creating a DMP. Researchers also learn how to handle data correctly, make it FAIR, maintain it throughout the project, and curate it long-term. This intelligent, guided, and efficient approach to composing DMPs is useful for ELIXIR nodes, research institutions, and individual researchers alike.
Based on our record, Google BigQuery seems to be more popular. It has been mentiond 35 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 9 months ago
Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 9 months ago
Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 10 months ago
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 11 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 11 months ago