FineReport

DECEMBER 11, 2019

Effective use of big data helps companies analyze critical information more accurately, ultimately improving operational efficiency, reducing costs, reducing risk, accelerating innovation, and increasing revenue. By Michael Milton. – Data Divination: Big Data Strategies. by Dimitri Maex and Paul B.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

O'Reilly on Data

SEPTEMBER 15, 2020

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk.

Cost-Benefit 294

Cost-Benefit Advertising ROI Machine Learning 294

CIO Business Intelligence

MAY 1, 2024

Ready to roll It’s shorter to make a list of organizations that haven’t announced their gen AI investments, pilots, and plans, but relatively few are talking about the specifics of any productivity gains or ROI. Pilots can offer value beyond just experimentation, of course. But where am I going to make money as an organization?”

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. The ability to measure results (risk-reducing evidence). Ensure a culture that supports a steady process of learning and experimentation.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. And then you’ll do a lot of work to get it out and then there’ll be no ROI at the end.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

MAY 8, 2019

That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Given how so much of IT gets driven by concerns about risks and costs, in practice auditability tops the list for many business stakeholders. How fast can the model be trained?

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

MARCH 23, 2010

My problem with these mistruths and FUD is that they result in a ton of practitioners and companies making profoundly sub optimal choices, which in turn results in not just much longer slogs but also spectacular career implosions and the entire web analytics industry suffering. There is such little risk to actually trying. This is sad.

Analytics 118

Analytics Consulting Metrics Experimentation 118

CIO Business Intelligence

AUGUST 1, 2023

As many CIOs prepare their 2024 budgets and digital transformation priorities, developing a strategy that seeks opportunities to evolve business models, targets near-term operational impacts, prioritizes where employees should experiment, and defines AI-related risk-mitigating plans is imperative.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Experimentation 98