Data Hashing | Dagster Glossary

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Data Hashing

Convert data into a fixed-length code to improve data security and integrity.

Hashing definition:

Hashing is the process of transforming data of arbitrary size into a fixed-size output called a hash value. The hash value is a unique and consistent identifier for the input data, which makes it useful for a variety of purposes such as data security, indexing, and comparison.

One of the most common uses of hashing is in password storage. When a user creates a password, it is hashed and stored in a database. When the user enters their password during login, it is hashed again and compared to the stored hash value. If the hash values match, the user is granted access.

Data hashing example using Python and hashlib:

Please note that you need to have the hashlib library installed in your Python environment to run the following code examples.

In Python, the hashlib module provides a way to generate hash values. Here is an example of how to use the sha256 algorithm to hash a string:

import hashlib

input_data = "Hello World"
hash_object = hashlib.sha256(input_data.encode())
hash_value = hash_object.hexdigest()

This code will output the hash value b94d27b9934d3e08a52e52d7da7dabfac484efe37a5380ee9088f7ace2efcde9 (string hyphenated for layout), which is a fixed-length string of 64 characters representing the hash of the input string "Hello World".

Hashing is also commonly used in data processing pipelines for indexing and comparison purposes. For example, if you have a large dataset and want to quickly find all the records that match a specific value, you can hash the value and use it as an index to quickly retrieve the matching records.

Other data engineering terms related to
Data Security and Privacy: