Yahoo Canada Web Search

Search results

1. www.firebolt.io › glossary-items › data-flatteningData Flattening and Data Unflattening | Firebolt Gloassary

   www.firebolt.io › glossary-items › data-flattening

   • Cached

   Data flattening usually refers to the act of flattening semi-structured data, such as name-value pairs in JSON, into separate columns where the name becomes the column name that holds the values in the rows. Data unflattening is the opposite; adding nested structure to relational data. If flattening does not sound great, you have good intuition.

   • Documentation

     Firebolt documentation . Firebolt is a cloud data warehouse...

2. stackoverflow.com › questions › 52004368What is meant by Flattening and Unflattening of Json? Also ...

   stackoverflow.com › questions › 52004368

   Aug 24, 2018 · Why flattening is required? If you don't internal structure of JSON Object, it will be quite cumbersome to access all the elements inside hence simple solution is to put everything on the same level and deepness of Objects is depicted by dot operator. So flattening makes it easier to access the internal elements.

3. www.geeksforgeeks.org › flattening-json-objects-inFlattening JSON objects in Python - GeeksforGeeks

   www.geeksforgeeks.org › flattening-json-objects-in

   • Cached

   Aug 1, 2022 · The json-flatten library provides functions for flattening a JSON object to a single key-value pairs, and unflattening that dictionary back to a JSON object. Installing library In order to use the flatten_json library, we need to install this library. flatten_json can be installed by running the following command in the terminal.

4. www.pecan.ai › blog › data-flatten-analytics-101Data Flattening 101: Preparing Your Data for Predictive ...

   www.pecan.ai › blog › data-flatten-analytics-101

   • Cached

   Jun 5, 2024 · Data flattening is crucial for preparing data for predictive analytics modeling. It transforms nested data into a flat, tabular format. Challenges of nested data structures include complexity, data manipulation skills required, and potential impact on model accuracy. Techniques for flattening data include using tools like the Pandas library and ...

5. apricot-articles.socialsolutions.com › en › articlesApricot Results | Flattened Versus Unflattened Data

   apricot-articles.socialsolutions.com › en › articles

   • Cached

   Unflattened data is all data in an enterprise stored in "Question/Answer" pair format. Unflattened data should be used when aggregating (totaling) data. Unflattened demographic data is available in real time. Unflattened tier 2 record responses are not available in real time. They are populated by a queue system that feeds updated tier 2 record ...

6. satoricyber.com › glossary › data-flatteningData Flattening - Satori

   satoricyber.com › glossary › data-flattening

   • Cached

   Data Flattening. Data flattening is associated with transforming data into plain text files stored in file systems rather than in databases or data warehouses. Flat files are records that generally consist of single portions of data, which can be, for example, tabular spreadsheet files. Other kinds of flat files can be header records containing ...

7. People also ask

   What is the difference between data flattening and data Unflattening?

   • Data flattening usually refers to the act of flattening semi-structured data, such as name-value pairs in JSON, into separate columns where the name becomes the column name that holds the values in the rows. Data unflattening is the opposite; adding nested structure to relational data. If flattening does not sound great, you have good intuition.

   Data Flattening and Data Unflattening | Firebolt Gloassary

   www.firebolt.io/glossary-items/data-flattening-and-data-unflattening

   See all results for this question

   What is data Unflattening?

   • Data unflattening is the opposite; adding nested structure to relational data. If flattening does not sound great, you have good intuition. Flattening is mostly done to put data in a format that a relational data warehouse can use natively, and make sure queries perform well.

   Data Flattening and Data Unflattening | Firebolt Gloassary

   www.firebolt.io/glossary-items/data-flattening-and-data-unflattening

   See all results for this question

   Does flattening data affect analytics?

   • Flattening data also limits your analytics. Often you want to be able to walk the actual JSON structure. When you flatten JSON, those analytics become nested queries, which is a horribly slow query to run on any relational database. If you have mostly relational data, then flattening some data may make good sense.

   Data Flattening and Data Unflattening | Firebolt Gloassary

   www.firebolt.io/glossary-items/data-flattening-and-data-unflattening

   See all results for this question

   Why is data flattening important?

   • Data flattening is an essential process for preparing data for predictive analytics. It allows you to transform complex nested data into a flat, tabular format more suitable for machine learning algorithms. This process can significantly improve the performance and accuracy of your predictive models and streamline the overall analytics process.

   Data Flattening 101: Preparing Your Data for Predictive Analytics

   www.pecan.ai/blog/data-flatten-analytics-101/

   See all results for this question

   What happens if you flatten data in a data lake?

   • When you flatten you lose information. This is one reason why a data lake should store the full, raw structure. You cannot unflatten data unless you have this extra information somewhere else. Flattening data also limits your analytics. Often you want to be able to walk the actual JSON structure.

   Data Flattening and Data Unflattening | Firebolt Gloassary

   www.firebolt.io/glossary-items/data-flattening-and-data-unflattening

   See all results for this question

   How do you flatten data?

   • Techniques for flattening data include using tools like the Pandas library and SQL queries. Best practices for data flattening involve data cleaning, handling missing values, and leveraging automated platforms like Pecan AI.

   Data Flattening 101: Preparing Your Data for Predictive Analytics

   www.pecan.ai/blog/data-flatten-analytics-101/

   See all results for this question

8. infogoal.com › datawarehousing › flat_files_tutorialWhat are Flat Files and Flattened Data and Why Are They ...

   infogoal.com › datawarehousing › flat_files_tutorial

   • Cached

   The fixed-format approach was commonly used in COBOL applications. Flattened / Denormalized Data is data where data from related database tables or flat file records are gathered into a single or reduced number of tables or records. This reverses the process of normalization where data is organized so that each fact is stored once - avoiding ...