Cookies: Our site uses cookies in order to deliver better content. By continuing you accept these cookies.
See all devices compared
Expand your fleet with Mini
Upgrade your fleet's IQ with CM4
Increase fleet visibility and secure all your operations in real-time
Optimize your operations or projects by obtaining insightful telematics data
Secure your operations with precise localization and secure key management
Manage your code in a secure and standardized method
Strengthen your data flow with an All-in-one gateway
Explore some of our exiting topics
Explore our extensive Cloud API
Get answers to your questions in our documentation
Get inspired by the potential
Reach out to our support for extended help
Our shop offer a wide selection accesories to your project
Get an introduction to our cloud for businesses. Schedule your demo for FREE
Do you have any questions? We have compiled a list of very useful faqs
Learn more about what it means to be a part of AutoPi
Contact us about solutions for your business or projects
Check out our open positions
Login to your AutoPi cloud account here
At its core, data redundancy meaning encapsulates the idea of duplicating identical data within a database or across systems. This replication can either be intentional (for data protection and faster access) or unintentional (causing inconsistencies). This concept is pivotal in realms like database management, data processing, and networking.
Data redundancy, despite occasionally leading to storage inefficiencies, plays an essential role in preserving data. By duplicating data, we ensure its survival if the original dataset faces corruption, deletion, or any other kind of damage. Furthermore, having duplicate data across different systems allows quicker data access, as the data can be fetched from the closest or most available source.
The phrase 'data error cyclic redundancy check' might sound a bit intimidating, but it's a key mechanism in ensuring data integrity during transmission. Essentially, it's an error-detection code used by computers to check for accidental changes to raw data. For example, if you're downloading a file and a bit is altered during the process, a cyclic redundancy check (CRC) can detect this anomaly.
In this process, the sender computes a check (or a "remainder") by dividing the data by a certain divisor. The check is sent along with the data to the receiver, who performs the same division. If the receiver's result matches the check sent by the sender, the data is deemed intact. However, if there's a discrepancy, it indicates a 'data error cyclic redundancy check', alerting the receiver to the corrupted data.
To illustrate, imagine you're sending a parcel (the data) with a specific weight (the check). If the receiver finds the parcel's weight different from what's stated, they know something's off, just like a CRC mismatch.
In the digital world, where data is the new oil, understanding data redundancy and related concepts is non-negotiable. While it sometimes leads to storage inefficiencies, the value it provides in preserving data integrity, preventing data loss, and ensuring faster access outweighs the drawbacks. Moreover, tools like data error cyclic redundancy check further fortify data accuracy and reliability during transmission.
What is data redundancy?: The duplication of data in a database or across systems.
Data redundancy meaning: Ensuring data preservation and faster access by duplicating data.
Data error cyclic redundancy check: An error-detection code for ensuring data integrity during transmission.
Get in touch with us – We're ready to answer any and all questions.
* Mandatory fields
Email our engineers
We are here to help!
E-mail us at sales@autopi.io or use the form below. We will get back to you ASAP.