oceanprotocol/docs
1
0
Fork 0
mirror of https://github.com/oceanprotocol/docs.git synced 2024-11-01 15:55:34 +01:00
Code Releases Activity

GITBOOK-380: change request with no subject merged in GitBook

Browse Source
This commit is contained in:
Christian Casazza 2023-05-31 13:58:19 +00:00 committed by gitbook-bot
parent d52d213bac
commit 63b3542e5c
No known key found for this signature in database
GPG Key ID: 07D2180C7B12D0FF
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
data-science/how-to-contribute/data-engineers.md
View File

@ -1,10 +1,10 @@
# Data Engineers
Data engineers play a pivotal role in driving data value creation. If you're a developer looking to build useful dashboards or cutting-edge machine-learning models, you understand the importance of having access to well-curated data. That's where our team of friendly and skilled data engineers comes in!
Data engineers play a pivotal role in driving data value creation. If you're a data scientist looking to build useful dashboards or cutting-edge machine-learning models, you understand the importance of having access to well-curated data. That's where friendly and skilled data engineers come in!
Data engineers specialize in creating robust data pipelines that enable seamless data ingestion from diverse source systems. The expertise lies in conducting essential transformations to ensure data cleanliness and aggregation, ultimately making the data readily available for downstream use cases. With data engineer support, data scientists can focus on unleashing their creativity and innovation, knowing that the data they need is reliably curated and accessible.
There are numerous types of data that data engineers can contribute to the Ocean Protocol ecosystem.
Data engineers can contribute numerous types of data to the Ocean Protocol ecosystem. Some examples are below.
* Government Open Data: Governments serve as a rich and reliable source of data. However, this data often lacks proper documentation or poses challenges for data scientists to work with effectively. Establishing robust Extract, Transform, Load (ETL) pipelines enhance accessibility to government open data. This way, others can tap into this wealth of information without unnecessary hurdles. For example, in one of our [data challenges](https://desights.ai/shared/challenge/8) we leveraged public real estate data from Dubai to build use cases for understanding and predicting valuations and rents. Local, state, and federal governments around the world provide access to valuable data. Build pipelines to make consuming that data easier and help others build useful products to help your local community.