Data Processing Data Transformation Risk 
O'Reilly on Data
JANUARY 17, 2023
Especially when you consider how Certain Big Cloud Providers treat autoML as an on-ramp to model hosting. Is autoML the bait for long-term model hosting? Related to the previous point, a company could go from “raw data” to “it’s serving predictions on live data” in a single work day.
AWS Big Data
DECEMBER 4, 2024
Globally, financial institutions have been experiencing similar issues, prompting a widespread reassessment of traditional data management approaches. With this approach, each node in ANZ maintains its divisional alignment and adherence to data risk and governance standards and policies to manage local data products and data assets.
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datapine
MAY 2, 2023
However, if you underestimate how many vehicles a particular route or delivery will require, then you run the risk of giving customers a late shipment, which negatively affects your client relationships and brand image. After examining their data, UPS found that trucks turning left were costing them a lot of money.
datapine
SEPTEMBER 29, 2022
Data processes that depended upon the previously defective data will likely need to be re-initiated, especially if their functioning was at risk or compromised by the defected data. This is also the point where data quality rules should be reviewed again. This is due to the technical nature of a data system itself.
IBM Big Data Hub
JANUARY 9, 2024
Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. Data ingestion must be done properly from the start, as mishandling it can lead to a host of new issues.
Sisense
AUGUST 28, 2020
Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. Data integrity risks.
Cloudera
OCTOBER 8, 2024
A major risk is data exposure — AI systems must be designed to align with company ethics and meet strict regulatory standards without compromising functionality. Ensuring that AI systems prevent breaches of client confidentiality, personally identifiable information (PII), and data security is crucial for mitigating these risks.
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