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1. • Adding nested structure to relational data

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

     Data Flattening and Data Unflattening | Firebolt Gloassary

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

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

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   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.

   • Firebolt documentation | User and developer documentation for the ...

     Firebolt is a cloud data warehouse engineered ground up for...

   • Data Nesting and Data Unnesting - Definition | Firebolt Glossary

     Data nesting and data unnesting is the opposite of data...

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

   stackoverflow.com › questions › 52004368

   Aug 24, 2018 · What is meant by Flattening and Unflattening of Json? Also can we use ObjectMapper class to deserialize a flattened json attribute?

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

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

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   Jun 5, 2024 · The three best practices for data flattening include data cleaning and preprocessing, handling missing or null values, and leveraging automated platforms like Pecan AI that streamline the data flattening process.

5. community.visualdatatools.com › datagraphHow to ‘Flatten’ Data – DataGraph Community

   community.visualdatatools.com › datagraph

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   Mar 8, 2023 · In DataGraph, you can reverse pivot, or flatten a data set quickly using the menu option Data/Flatten Columns. Why Flatten? Data tables can be configured in two general formats: (1) a wide format with lots of columns or (2) a long format with less columns and more rows.

6. www.firebolt.io › glossary-items › data-nesting-andData Nesting and Data Unnesting - Definition | Firebolt Glossary

   www.firebolt.io › glossary-items › data-nesting-and

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   Data nesting and data unnesting is the opposite of data flattening and data unflattening. In order to nest data from a “flattened” form such as a relational model, you need extra information about how to nest.

7. www.researchgate.net › publication › 327946311Nick Sousanis, Unflattening, Cambridge, MA: Harvard ...

   www.researchgate.net › publication › 327946311

   Unflattening is constructed as an experience. Its argument lies in its very form. Unflattening asks how humans construct knowledge: How do fixed viewpoints limit us, flattening experience and...

8. 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

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   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

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   Can You unflatten JSON data?

   • 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. When you flatten JSON, those analytics become nested queries, which is a horribly slow query to run on any relational database.

   Data Flattening and Data Unflattening | Firebolt Gloassary

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

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   Why do we flatten data?

   • Flattening increases the performance and scalability. The flattened format is also more general. Data can be added without changing the data structure (i.e., adding more columns). Drawing commands that use that data also do not need to change when we add more data. Here is an example of data spanning multiple columns, a ‘wide’ format.

   How to ‘Flatten’ Data – DataGraph Community - Visual Data Tools

   community.visualdatatools.com/datagraph/knowledge-base/how-to-flatten-data/

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   What are the challenges in data flattening?

   • One of the primary challenges in data flattening is the complexity and size of the nested data structures. Deeply nested data means more transformations and processing to flatten the data, which can be time-consuming and computationally intensive.

   Data Flattening 101: Preparing Your Data for Predictive Analytics

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

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   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

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9. towardsdatascience.com › the-perfect-way-to-smoothThe Perfect Way to Smooth Your Noisy Data

   towardsdatascience.com › the-perfect-way-to-smooth

   Oct 25, 2023 · Whether you’re carrying out a survey, measuring rainfall or receiving GPS signals from space, noisy data is ever present. Dealing with such data is the main part of a data scientist’s job. It’s not all glamorous machine learning models and AI — it’s cleaning data in an attempt to extract as much meaningful information as possible.