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Not all dataset comes structure. Or better put, there are more unstructured or semi-structured datasets that they are structured. And as a data engineer, we should at least give a good amount of structure or schema to data before it becomes useful for any downstream operation.
In this Hackerday session, we will evaluate and demonstrate how to handle rather unstructured data sets from the ginniemae.gov data disclosure history site. This dataset is a free text data that comes with a codebook describing the data. A lot does actually happen between the codebook and the data and we will see all in this sessions.
Ginnie Mae is a federally-owned corporation that helps to create and guarantee mortgage-backed securities in the US housing market. It is a lot more than that. See https://www.investopedia.com/terms/g/ginniemae.asp from more.
The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture.
In this hive project, you will design a data warehouse for e-commerce environments.
In this spark project, we will measure by how much NFP has triggered moves in past markets.