erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance. Data Governance 2.0

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Smart Data Collective

SEPTEMBER 22, 2021

One bad breach and you are potentially risking your business in the hands of hackers. In this blog post, we discuss the key statistics and prevention measures that can help you better protect your business in 2021. Cyber fraud statistics and preventions that every internet business needs to know to prevent data breaches in 2021.

Statistics 106

Statistics Risk Measurement Software 106

Smart Data Collective

JULY 25, 2019

The Global Data Protection Regulation (GDPR) was enacted in May 2018. Consumers need to be aware of the risks and take appropriate measures. Data privacy risks remain a concern after the passage of the GDPR. Many experts are still trying to determine how effective the law has been.

Risk 80

Risk Cost-Benefit Data Processing Measurement 80

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). More Policies Emerged” (2010-2018). Data is on the move.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

FEBRUARY 22, 2024

But it’s equally important that they have a deep understanding of the risks and limitations of AI and how to implement the appropriate security measures and ethics guardrails. Note: These measures of responsibility must be interpretable by AI non-experts (without “mathsplaining”).

Metadata 96

Metadata Measurement Risk Modeling 96

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? The ability to measure results (risk-reducing evidence).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66