O'Reilly on Data

OCTOBER 13, 2020

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

Management 314

Management Machine Learning Metrics Modeling 314

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. A complete DataOps program will have a unified, system-wide view of process metrics using a common data store. Download the 2021 DataOps Vendor Landscape here. DataOps is a hot topic in 2021.

Testing 300

Testing Machine Learning Consulting Data Science 300

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., This blog post discusses such a comprehensive approach that is used at Youtube. the fraction of video recommendations resulted in positive user experiences).

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

SEPTEMBER 30, 2013

We'll start with digital at the highest strategic level, which leads us into content marketing, from there it is a quick hop over to the challenge of metrics and silos, followed by a recommendation to optimize for the global maxima, and we end with the last two visuals that cover social investment and social content strategy.

Marketing Analytics 156

Marketing Analytics Marketing Visualization Analytics 156

DataRobot Blog

JANUARY 10, 2023

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. This flexibility allows you to import your local code into the DataRobot platform and continue further experimentation using the combination of DataRobot Notebooks with: Deep integrations with DataRobot comprehensive APIs.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

datapine

JANUARY 31, 2022

They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process. BI dashboards like the one presented below provide a centralized view of the most important metrics businesses need to stay ahead of their competitors. What Are The Benefits of Business Intelligence?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataKitchen

OCTOBER 5, 2021

DataOps enables: Rapid experimentation and innovation for the fastest delivery of new insights to customers. In this blog, we’ll explore the role of the DataOps Engineer in driving the data organization to higher levels of productivity. A more technical discussion will follow in the next edition of this blog series.

Testing 152

Testing Dashboards Measurement Experimentation 152

DataRobot Blog

MARCH 16, 2023

Collaborative Experimentation Experience – the new experience, called the Workbench, comes packed with new capabilities such as new integrated data prep for modeling and notebooks providing a full code-first experience. New Snowflake integrations and the SAP joint solution have tightened the data to experimentation to deployment loop.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

IBM Big Data Hub

JUNE 10, 2024

In this blog, we’ll explore how businesses can use both on-premises and cloud XaaS to control budgets in the age of AI, driving financial sustainability without compromising on technological advancement. Embracing a culture of experimentation helps businesses drive innovation while minimizing financial risk.

Experimentation 62

Experimentation Optimization Risk Management Machine Learning 62

Occam's Razor

AUGUST 13, 2012

Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. That means: All of these metrics are off. This is exactly why the Page Value metric (in the past called $index value) was created. Hopefully soon! Edward Cowell. "Was

Modeling 125

Modeling Metrics Data Quality Data-driven 125

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines. Here are the key stages: .

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Occam's Razor

NOVEMBER 2, 2015

Success Metrics. In my Oct 2011 post, Best Social Media Metrics , I'd created four metrics to quantify this value. I believe the best way to measure success is to measure the above four metrics (actual interaction/action/outcome). It can be a brand metric, say Likelihood to Recommend. It is not that hard.

B2B 167

B2B Metrics Recreation/Entertainment Testing 167

Occam's Razor

NOVEMBER 13, 2009

I now have several full time jobs, plus this blog, plus speaking around the world, plus a family, plus… so much more. " This blog post is in three parts: The pitch. Chapter 3 The Awesome World of Clickstream Analysis: Metrics. Chapter 7 Failing Faster: Unleashing the Power of Testing and Experimentation.

Analytics 71

Analytics Metrics Measurement Testing 71

CIO Business Intelligence

JULY 11, 2023

In this blog post, we will delve deeper into each of these principles and provide concrete examples to illustrate their importance. For example, a good result in a single clinical trial may be enough to consider an experimental treatment or follow-on trial but not enough to change the standard of care for all patients with a specific disease.

Modeling 95

Modeling Testing Experimentation Risk Management 95

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning. accounting for effects "orthogonal" to the randomization used in experimentation. accounting for effects "orthogonal" to the randomization used in experimentation.

Modeling 63

Modeling Experimentation Knowledge Discovery Testing 63

DataRobot Blog

OCTOBER 18, 2022

Model Observability – the ability to track key health and service metrics for models in production – remains a top priority for AI-enabled organizations. Learn more about the DataRobot AI Cloud and the ability to accelerate your experimentation and production timelines. DataRobot Booth at Big Data & AI Toronto 2022.

Big Data 96

Big Data Forecasting Experimentation Machine Learning 96

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 95

Analytics Metrics Strategy Measurement 95

Occam's Razor

JANUARY 7, 2014

They are generic mash-ups that tailor to almost no one's needs, and more often than not contain awful things like nine not-really-thought out metrics for one dimension in a report. the instinctive response of the Squirrels is to go grab the most obvious metrics and start partying. My second blog post covered what and why !

Data-driven 142

Data-driven Consulting Reporting Marketing 142

Sisense

JANUARY 21, 2020

One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. Another study showed using experimental studies that the paradox might occur, and that people are often poor at recognizing it. See “ How likely is Simpson’s paradox?

Testing 104

Testing Data-driven Risk Statistics 104

Cloudera

OCTOBER 8, 2024

By 2023, the focus shifted towards experimentation. Performance Monitoring and Logging: Provides comprehensive monitoring and logging capabilities, tracking performance metrics such as latency, throughput, resource utilization, and model health, supporting troubleshooting and optimization.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

IBM Big Data Hub

MAY 17, 2024

Organizations face increased pressure to move to the cloud in a world of real-time metrics, microservices and APIs, all of which benefit from the flexibility and scalability of cloud computing. Teams are comfortable with experimentation and skilled in using data to inform business decisions. Why move to cloud?

Modeling 96

Modeling Cost-Benefit Optimization Digital Transformation 96

Occam's Razor

FEBRUARY 26, 2008

1: Implement a Experimentation & Testing Program. # 1: Implement a Experimentation & Testing Program. Experimentation and Testing: A Primer. Build A Great Web Experimentation & Testing Program. # Be it for in vogue metrics like Conversion Rates or for metrics that should be in vogue like Abandonment Rates.

Management 68

Management Experimentation Testing Metrics 68

Occam's Razor

JUNE 6, 2007

It has been such an amazing journey to write the book, and for it to come up almost exactly a year after I started this blog. Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. There I said it. Damini, Chirag and now the book! :).

Analytics 60

Analytics Metrics Marketing Dashboards 60

IBM Big Data Hub

DECEMBER 4, 2023

And the abundance of data available for training models has opened up vast possibilities for experimentation and learning. Explore IBM watsonx Orchestrate™ Try the watsonX Orchestrate interactive demo The post Top 5 criteria for developers when adopting generative AI appeared first on IBM Blog.

Experimentation 63

Experimentation Machine Learning Metrics Modeling 63

The Unofficial Google Data Science Blog

JANUARY 16, 2018

Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. However, the downside of using a larger unit of randomization is that we lose experimental power. Consider the case where experiment metrics are evaluated at the per-user level.

Testing 59

Testing Experimentation Measurement Modeling 59

Sisense

JULY 1, 2021

We know in marketing that one of the most powerful ideas is experimentation,” Scott told Sisense. What has held that back is that the gap between idea and implementation has been a real bottleneck for how much experimentation can happen.”. In a world of rapid technological change, digital tools for marketers are having a moment.

Marketing 52

Marketing Experimentation Marketing Analytics ROI 52

DataRobot Blog

FEBRUARY 28, 2023

They can enjoy a hosted experience with code snippets, versioning, and simple environment management for rapid AI experimentation. When the training process is complete, DataRobot will recommend the best-performing model for production based on the selected metric and provide an explanation. Learn more about DataRobot hosted notebooks.

Data Processing 72

Data Processing Experimentation Machine Learning Data Warehouse 72

Occam's Razor

DECEMBER 9, 2009

In this blog post I'll share a unique "case study", more like one person's problem, and my advice to them about how to think about the organization problem. If your overall web business is misaligned from an org perspective then honestly there is no hope for you, regardless of where analytics sits.]. You are out man!

Analytics 95

Analytics Data-driven Marketing Sales 95

AWS Big Data

JULY 20, 2023

Additionally, partition evolution enables experimentation with various partitioning strategies to optimize cost and performance without requiring a rewrite of the table’s data every time. Orca monitored the cluster status and resource usage of Amazon EMR by utilizing the available metrics through Amazon CloudWatch.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

DataRobot Blog

JULY 28, 2022

In addition to the accuracy of the models we built, we had to consider business metrics, cost, interpretability, and suitability for ongoing operations. Initially, the customer tried modeling using statistical methods to create typical features, such as moving averages, but the model metrics (R-square) was only 0.5

Data Science 72

Data Science Machine Learning Statistics Modeling 72

DataRobot Blog

MARCH 7, 2023

DataRobot on Azure accelerates the machine learning lifecycle with advanced capabilities for rapid experimentation across new data sources and multiple problem types. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

IBM Big Data Hub

MARCH 4, 2024

This culture encourages experimentation and expertise growth. Visit the IBM Hybrid Cloud Architecture Center The post How to become an AI+ enterprise appeared first on IBM Blog. For example, by using compliance control scanning of terraform templates to fail provisioning if controls are not met.

Enterprise 96

Enterprise ROI Risk Strategy 96

Cloudera

JUNE 6, 2019

At the other end of the spectrum, the admin may instantiate a number of low-priority dev clusters – these clusters may often run at capacity, not require performance guarantees, but also provide more agility and flexibility for experimentation. Designing a proper network for VPCs extends beyond the scope of this blog post.

Metadata 86

Metadata Data Lake Optimization Strategy 86

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. Right tools/open source.

Analytics 98

Analytics Data-driven Marketing Reporting 98

IBM Big Data Hub

SEPTEMBER 25, 2023

This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. Data Exploration and Innovation: The flexibility of Presto has encouraged data exploration and experimentation at Uber. Enterprise Management Associates (EMA).

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

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

Sisense

MAY 18, 2021

When you discover data that means something, you need to be agile enough to make experimental changes.”. Mistake #3: Making vanity metrics your main event. When the primary focus becomes likes, retweets, follows, and comments — also known as vanity metrics — marketing efforts become less meaningful for your long-term goals.

Marketing 52

Marketing Data Analytics Analytics Metrics 52