Corinium

JUNE 6, 2019

present a significant barrier to adoption of the latest and greatest approaches. It is also important to have a strong test and learn culture to encourage rapid experimentation. Newer methods can work with large amounts of data and are able to unearth latent interactions. In addition, the traditional challenges remain.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

IBM Big Data Hub

MARCH 4, 2024

It’s also crucial to modernize existing applications that interact with AI. An AI+ enterprise excels in delivering innovative AI applications to its customers and modernizing existing applications to meet the new demands AI presents. This culture encourages experimentation and expertise growth.

Enterprise 108

Enterprise ROI Risk Strategy 108

datapine

JANUARY 31, 2022

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process. What Are The Benefits of Business Intelligence?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Occam's Razor

MAY 15, 2006

Add to this the fact that now there is a massive proliferation of tools that will instantly create reports presenting data in every conceivable slice, graph, table, pivot or dump that you can imagine the challenge. Visitor interaction can lead to actionable insights faster while having a richer impact on your decision making.

Metrics 100

Metrics Experimentation Testing Interactive 100

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Sisense

MAY 18, 2021

When you discover data that means something, you need to be agile enough to make experimental changes.”. Mistake #2: Choosing the wrong data visualization to present your data. Mistake #3: Making vanity metrics your main event. Vanity metrics ebb and flow like a tidal wave, meaning they can easily consume your marketing efforts.

Marketing 52

Marketing Data Analytics Analytics Metrics 52

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 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch presented “ Product Management for AI ” at Rev. 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. Session Summary.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

DECEMBER 4, 2020

Having calculated AUC/AUMC, we can further derive a number of useful metrics like: Total clearance of the drug from plasma. Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). The area under the first moment curve would respectively be.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

AWS Big Data

NOVEMBER 14, 2023

With a combination of low-latency data streaming and analytics, they are able to understand and personalize the user experience via a seamlessly integrated, self-reliant system for experimentation and automated feedback. Real-time streaming data technologies are essential for digital transformation.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

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

Occam's Razor

MARCH 23, 2021

The other dimension to consider is most Analtyics teams kick into gear after the campaign is concluded, after the customer interaction has taken place in the call center, and after the funds budgeted have already been spent. The benchmark for the beautiful metric AVOC is 15.3%. More shouting is not really better – and it is expensive!

Analytics 131

Analytics Scorecard Strategy Testing 131

CIO Business Intelligence

JUNE 27, 2022

David Cramer: I love the open source community so I would build a lot of things in open source to interact with my peers. 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.

Software 113

Software Experimentation Testing Marketing 113

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. This simulation is based on the actual user network of GCP.

Testing 58

Testing Experimentation Measurement Modeling 58

Occam's Razor

AUGUST 12, 2013

Last Interaction/Last Click Attribution model. First Interaction/First Click Attribution Model. If you see a value greater than one, that channel has a propensity to be present earlier in the conversion cycle. Last Interaction/Last Click Attribution model. First Interaction/First Click Attribution Model.

Modeling 161

Modeling Optimization Marketing Interactive 161

Occam's Razor

JULY 26, 2010

PALM: People Against Lonely Metrics]. So why not your metrics? This is the problem with lonely metrics. Why not find a BFF for your lonely metric and present something like this. I found a "you complete me" for my Visits metric, Bounce Rate. Or an actual outcome metric. I need someone.

Metrics 96

Metrics Measurement Dashboards Reporting 96

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. when an admin uses the cluster creation wizard, CM presents two options: (1) create a traditional cluster, or (2) create a compute cluster. Beginning with CM 6.2, Cloudera Manager 6.2

Metadata 85

Metadata Data Lake Optimization Strategy 85

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. "So what if no one interacted with your Twitter feed, at least they saw it!" I believe the best way to measure success is to measure the above four metrics (actual interaction/action/outcome).

B2B 167

B2B Metrics Testing Recreation/Entertainment 167

Occam's Razor

DECEMBER 12, 2016

In a world when your work will never be done, how do you assess that the core things necessary are present? What guarantees that agility and innovation are present in your analytics practice? My answer was: " Look for these two elements, if they are present then it is worth helping the company with free consulting and analysis.

Analytics 141

Analytics Data-driven Strategy Consulting 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. In other words, your talk didn’t quite stand out enough to put onstage, but you still get “publish or perish” credits for presenting.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

MARCH 23, 2010

Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more. Post my keynote the feedback I got was: "Your presentation was powerful, you made a compelling case for how we can do the things you have outlined to take advantage of the opportunity. Likely not.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Domino Data Lab

AUGUST 22, 2019

In the present chapter [excerpt], we cover code that will enable you to create your own word vectors as well as to provide them as an input into a deep learning model. Instead, we recommend using the bokeh library to create a highly interactive—and actionable—plot, as with the code provided in Example 11.11. Example 11.11 y=subset_df.y,

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Occam's Razor

MAY 27, 2015

Because, I'm sure like you, I'm humbled by the immense opportunity digital presents. Apps are the past, present, future. It is being hyper-conservative when it comes to creativity and experimentation because of quant-issues. Apps are the past, present, future. My hope is that 1. The web is dead. Go, subscribe!

Marketing Analytics 153

Marketing Analytics Marketing Analytics Advertising 153

Domino Data Lab

MAY 8, 2019

If your “performance” metrics are focused on predictive power, then you’ll probably end up with more complex models, and consequently less interpretable ones. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. ML: social systems and context.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

To that end, we present a vignette that is lighthearted but sufficiently realistic as to allow for the requisite reasoning. It was now a business decision to decide whether to pursue this radical strategy given the projected hit to metrics. There is an interaction between the selection of measures, and the selection of counterfactuals.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Domino Data Lab

AUGUST 26, 2019

To support the iterative and experimental nature of industry work, Domino reached out to Addison-Wesley Professional (AWP) for appropriate permissions to excerpt the “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. algorithm leaf_size metric metric_params n_jobs n_neighbors p weights.

Testing 79

Testing Modeling Machine Learning Metrics 79

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). Bonus: Interactive CD. Immediately actionable web analytics (your biggest worries covered).

Analytics 60

Analytics Metrics Marketing Dashboards 60

Occam's Razor

AUGUST 23, 2010

Why comes from lab usability studies , website surveys , "follow me home" exercises, experimentation & testing , and other such delightful endeavors. In as much, heuristic evaluations follow a set of well established rules (best practices) in web design and how website visitors experience websites and interact with them.

Analytics 116

Analytics Cost-Benefit Testing Optimization 116

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. Data Exploration and Innovation: The flexibility of Presto has encouraged data exploration and experimentation at Uber.

OLAP 94

OLAP Data Lake Data-driven Snapshot 94