“Data Ethics describe a code of behaviour, specifically what is right and wrong, encompassing the following: Data Handling: generation, recording, curation, processing, dissemination, sharing, and use."
“Data Quality (DQ) as stated in the DAMA International, Data Management Book of Knowledge "Refers to both the characteristics associated with and to the processes used to measure or improve the quality of data.” Data is considered high quality to the degree it is fit for the purposes data consumers want to apply it."
“Data ingestion is the process of obtaining and importing data for immediate use or storage in a database. To ingest something is to "take something in or absorb something." Data can be streamed in real time or ingested in batches.”
“Data ingestion tools provide a framework that allows companies to collect, import, load, transfer, integrate, and process data from a wide range of data sources.”
The survey question had 267 votes.
In additions to the results above I received a few additional comments.
- The biggest thing in my opinion is just ethics. How is the data collected?
- Also, what is it being used for. What are the impacts of high or low accuracy models.
- Improving quality and ethics seem to me, to be related tasks
- All of the above?
The results are quite interesting with AI Data Ethics and Improving Data Quality being the trends that the respondents thought were the most important.