AWS Big Data

JULY 20, 2023

Orca Security is an industry-leading Cloud Security Platform that identifies, prioritizes, and remediates security risks and compliance issues across your AWS Cloud estate. Therefore, optimizing the EMR clusters for this type of load while maintaining high throughput and low costs has been an ongoing challenge.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

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

DataRobot Blog

JANUARY 10, 2023

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Clinics and hospitals like Phoenix Children’s use AI to predict which patients are at risk of contracting an illness so that they can then prescribe medication and treatment accordingly. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Cloudera

JUNE 6, 2019

This strategy works well for managing internal chargebacks, limiting the impact of less sophisticated users on more experienced users, and overall encouraging individuals to think about and optimize their jobs and queries now that they have a smaller (but dedicated) cluster. 2) By workload type. 3) By workload priority.

Metadata 88

Metadata Data Lake Optimization Strategy 88

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. Another pattern that I’ve seen in good PMs is that they’re very metric-driven.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

JUNE 27, 2022

Tyson: You’re coming up to two years since you added Sentry’s ability to monitor for performance which has some pretty fine-grained metrics in terms of identifying where bottlenecks are located in code. A lot of the current approaches feel very experimental and are tough to see as maintainable, so there’s certainly still room for growth here.

Software 100

Software Experimentation Testing Marketing 100

CIO Business Intelligence

MAY 1, 2024

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times. Now nearly half of code suggestions are accepted.

Cost-Benefit 141

Cost-Benefit Metrics Insurance Measurement 141

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

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. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

AUGUST 26, 2019

When hyperparameters are also used for optimization and tuned for a specific dataset, they also impact predictive accuracy. Searching is a very general approach to solving or optimizing problems. I will continue using parameters (which are optimized during training) and hyperparameters (which are tuned via cross-validation).

Testing 79

Testing Modeling Machine Learning Metrics 79

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. As copilot technology capabilities are changing rapidly, leaders should frequently identify metrics and evaluate strategies.

Cost-Benefit 115

Cost-Benefit Advertising Experimentation Software 115

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. It should be noted that inverse probability weighting is not generally optimal (i.e., This is often referred to as the positivity assumption. the curse of dimensionality).

Statistics 44

Statistics Optimization Modeling Experimentation 44

DataRobot Blog

SEPTEMBER 30, 2022

By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Adoption of AI/ML is maturing from experimentation to deployment. How do you track the integrity of a machine learning model in production? Model Observability can help.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. You can start for free with a superb tool: Google's Website Optimizer. 4 Big Bets, Low Risks, Happy Customers. You have just launched something risky, yet you have controlled the risk by reducing exposure of the risky idea. Think about it this way.

Testing 112

Testing Experimentation Risk Optimization 112

Occam's Razor

JANUARY 9, 2012

If you are doing lame stuff, why try harder in an analytics context by asking for Economic Value or Visitor Loyalty or Conversation Rate or a thousand other super powerful and insightful metrics ? All while constantly optimizing your portfolio via controlled experiments. AND you can control for risk! Bank of America everything.

Marketing 140

Marketing B2B Measurement Risk 140

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

Occam's Razor

OCTOBER 23, 2006

Start with measuring these Outcomes metrics (revenue, leads, profit margins, improved product mix, number of new customers etc). Get competitive data (we are at x% of zz metric and our competition is at x+9% of zz metric). Great for a couple months and then you lose the audience. 6 Reporting is not Analysis. Your Choice? .

Data-driven 117

Data-driven Metrics KPI Reporting 117

IBM Big Data Hub

SEPTEMBER 25, 2023

With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. This allowed them to focus on SQL-based query optimization to the nth degree. Large, untested workloads run the risk of hogging all the resources.

OLAP 87

OLAP Data Lake Data-driven Snapshot 87

Sisense

NOVEMBER 23, 2020

Marketing needs quantitative metrics to justify every dollar they’re spending, the return they’re getting, and the revenue generated, so it’s one of the best examples of why you need a data-driven, evidence-based decision making culture within an organization,” he explains. Scott explains this is both a challenge and an opportunity.

Analytics 98

Analytics Data-driven Marketing Reporting 98