- How Pancake transforms complex JSON into relational data🔍
- Unraveling Nested JSON with dbt and BigQuery🔍
- How to Compare and Evaluate Data Pipeline Tools🔍
- What Is a Data Pipeline?🔍
- Use Transformations to fix bad data🔍
- Working with nested data🔍
- Transforming and Validating Data in Data & Insights Before Publishing🔍
- How To Flatten Data🔍
Big Data Transformations with Complex and Nested Data Types
How Pancake transforms complex JSON into relational data - LinkedIn
Wow! Transforming complex nested JSON into relational Dynamic Tables in minutes inside your Snowflake environment! Check out this demo[1] of ...
Unraveling Nested JSON with dbt and BigQuery: A Hands-On Guide
If you're like me, you might find that working with JSON data can often feel like trying to untangle a ball of wool. Nested structures are ...
How to Compare and Evaluate Data Pipeline Tools | Upsolver
Why data transformation matters: Data transformation has become more important because big and streaming data in its raw form is often unusable, ...
What Is a Data Pipeline? - IBM
This is inclusive of data transformations, such as filtering, masking, and aggregations, which ensure appropriate data integration and ...
Use Transformations to fix bad data | Segment Documentation
Depending on the transformation type you selected, relevant drop-down selectors and fields are presented to define how you want to transform the ...
Working with nested data - Splunk Documentation
The exact data transformations that you need to include in your pipeline vary depending on the specific data that you are working with and the ...
Transforming and Validating Data in Data & Insights Before Publishing
When editing complex transformations - particularly adding new conditions to Case transformations - be sure to update your data. This will ...
One of the most common transformations in an ETL pipeline pulling JSON data is to flatten nested JSON objects into a flat format to load into databases and data ...
Working with Nested and Repeated Fields in BigQuery - Datadice
quantity” column without having to look at other columns. The ability to have lots of data in one place and be able to easily analyze it without ...
Nested and Repeated Data - Kaggle
In this tutorial, you'll learn how to query nested and repeated data. These are the most complex data types that you can find in BigQuery datasets! Nested data¶.
Nested field type | Elasticsearch Guide [8.16] | Elastic
When ingesting key-value pairs with a large, arbitrary set of keys, you might consider modeling each key-value pair as its own nested document with key and ...
How to Read Nested JSON Files Using Spark SQL? - ProjectPro
... data from complex structured data. This powerful approach ... In this AWS Big Data Project, you will learn to perform Spark Transformations ...
And, as much of the data used in big data is unstructured, big data architecture must be able to accommodate the ingestion of varying data types with varying ...
Data Transformation: A Total Beginner's Guide - CareerFoundry
To help illustrate data transformation in the ETL/ELT processes, we're going to work through an example. Imagine you're an analyst at a company ...
Data Types and Declarations - Stan
These constraints are not part of the underlying data type for a variable, but determine error checking in the transformed data, transformed parameter, and ...
Data modeling techniques for more modularity - dbt Labs
If your marts models are overly nested + complex to read ... Now let's build the intermediate layer, where I'll conduct some major data transformations.
Hierarchical data structures - JSON | CloverDX Tech Blog
It is most frequently used to read complex JSON documents or large files. As an example, let's take a look at the following JSON document that ...
When to use a Nested Data Layer vs Flat Data Layer with GTM and ...
Scalability: This type of data storage is scalable, which means it can handle large amounts of data without any significant slowdown in ...
Data Transformation Explained - Ascend.io
This type of data transformation involves analytical-style operations, such as “count how many users during a particular time did x, y, or z.” ...
Advanced Data Transformation Techniques For Enhanced Analytics
Within these four wider categories, multiple more specific types of data transformations can be pursued to enhance the quality and accessibility ...