From 42dc41f566270586826f121390747eefe5bc69d1 Mon Sep 17 00:00:00 2001 From: Wanderclyffex <138209826+Wanderclyffex@users.noreply.github.com> Date: Mon, 10 Mar 2025 15:43:10 +0530 Subject: [PATCH] Update data-engineers (updated links).md some links are outdated that are related to data challenges --- data-scientists/data-engineers.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/data-scientists/data-engineers.md b/data-scientists/data-engineers.md index e95523247..8ded98387 100644 --- a/data-scientists/data-engineers.md +++ b/data-scientists/data-engineers.md @@ -14,13 +14,13 @@ To figure out which market segments are paying for data, then it may help you to But even then, it's not enough to just publish useful data on Ocean. **You need to market your data** **assets** to close sales. -If you're still encountering challenges in generating income, don't worry! You can enter one of the [data challenges](https://oceanprotocol.com/challenges) to make sweet OCEAN rewards and build your data science skills. +If you're still encountering challenges in generating income, don't worry! You can enter one of the [data challenges](https://oceanprotocol.com/earn/data-challenges/) to earn sweet rewards and build your data science skills. But what if you're a well-heeled company looking to create dApps or source data predictions? You can kickstart the value creation loop by working with Ocean Protocol to [sponsor a data challenge](sponsor-a-data-challenge.md). ### What data could be useful for dApp builders? -* **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. One idea is to clean and organize this data in a way that others can tap into this wealth of information with ease. For example, in one of the [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. So make consuming that data easier to help consumers build useful products and help your local community. +* **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. One idea is to clean and organize this data in a way that others can tap into this wealth of information with ease. For example, in one of the [data challenges](https://oceanprotocol.com/earn/data-challenges/) 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. So make consuming that data easier to help consumers build useful products and help your local community. * **Public APIs:** Data scientists can use free, public APIs to tokenize data in such a way that consumers can easily access it. [This ](https://github.com/public-apis/public-apis)is a repository of some public APIs for a wide range of topics, from weather to gaming to finance. * **On-Chain Data:** There is consistent demand for good decentralized finance (DeFi) data and an emerging need for decentralized social data. Thus, data scientists can query blockchain data to build and sell valuable datasets for consumers. * **Datasets for training AI and foundation models:** Much of the uniqueness and value in your data consists of aggregating and cleaning data from different sources. You can scrape the web or source data from other sources to present to AI/ML engineers looking for data to train their models.