Occam's Razor

FEBRUARY 7, 2022

Since you're reading a blog on advanced analytics, I'm going to assume that you have been exposed to the magical and amazing awesomeness of experimentation and testing. And yet, chances are you really don’t know anyone directly who uses experimentation as a part of their regular business practice. Wah wah wah waaah.

Experimentation 101

Experimentation Testing Optimization Marketing 101

Occam's Razor

MAY 22, 2006

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.

Experimentation 103

Experimentation Testing Optimization Measurement 103

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. Continuous pipeline monitoring with SPC (statistical process control). Just-in-Time” manufacturing increases production while optimizing resources. Let’s take a look.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

CIO Business Intelligence

JUNE 28, 2023

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs. This allowed us to derive insights more easily.”

Digital Transformation 101

Digital Transformation Cost-Benefit Informatics Data mining 101

O'Reilly on Data

MARCH 31, 2020

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

Management 332

Management Machine Learning Experimentation Metrics 332

DataRobot Blog

JULY 28, 2022

Of course, finding a compromise is necessary to a certain degree, but rather than simply compromising, finding the optimal solution within that trade-off is the key to creating maximum business value. The first baseline model we created used spectrograms of speech waveform data, statistical features, and spectrogram images.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

FineReport

DECEMBER 11, 2019

. – Head First Data Analysis: A learner’s guide to big numbers, statistics, and good decisions. The big news is that we no longer need to be proficient in math or statistics, or even rely on expensive modeling software to analyze customers. By Michael Milton. – Data Divination: Big Data Strategies.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

CIO Business Intelligence

MARCH 21, 2022

As such, a data scientist must have enough business domain expertise to translate company or departmental goals into data-based deliverables such as prediction engines, pattern detection analysis, optimization algorithms, and the like. Learn from data scientists about their responsibilities and find out how to launch a data science career. |

Unstructured Data 135

Unstructured Data Data Analytics Analytics Structured Data 135

DataRobot

JANUARY 13, 2022

Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. Determining demand, optimal price, and how much of each kind of product to have available when new products enter the market.

ROI 52

ROI Machine Learning Experimentation Data Science 52

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. ” AGI analyzes relevant code, generates a draft function with comments explaining its logic and allows the programmer to review, optimize and integrate it.

Cost-Benefit 89

Cost-Benefit Modeling Manufacturing Interactive 89

Occam's Razor

MARCH 23, 2021

This is very hard to do, we now have a proven seven-step experimentation process, with one of the coolest algorithms to pick matched-markets (normally the kiss of death of any large-scale geo experiment). You have the start of a fabulous in-flight optimization engine. More shouting is not really better – and it is expensive!

Analytics 131

Analytics Scorecard Strategy Testing 131

Octopai

MAY 2, 2022

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. Just-in-Time” manufacturing increases production while optimizing resources. Issue detected?

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google. Data Analysis Libraries.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

DataRobot

JUNE 8, 2021

Because cluster analysis is an unsupervised algorithm, it does not attempt to select groups that optimize business goals. Small changes in the data or parameters can result in the creation of significantly different groups. The authors of “ Resistance to Medical Artificial Intelligence ” explore consumers’ receptivity to medical AI.

Data-driven 98

Data-driven Testing Marketing Experimentation 98

Domino Data Lab

JANUARY 24, 2019

This group of solutions targets code-first data scientists who use statistical programming languages and spend their days in computational notebooks (e.g., These data scientists require the flexibility to use a constantly-evolving software and hardware stack to optimize each step of their model lifecycle. Jupyter) or IDEs (e.g.,

Data Science 65

Data Science Marketing Data-driven Statistics 65

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. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Occam's Razor

SEPTEMBER 19, 2011

We have to do Search Engine Optimization. You need people with deep skills in Scientific Method , Design of Experiments , and Statistical Analysis. The team did the normal modeling to ensure that the results were statistically significant (large enough sample set, sufficient number of conversions in each variation). *

Measurement 119

Measurement Advertising Testing Marketing 119

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. You're choosing only one metric because you want to optimize it. Remember that the raw number is not the only important part, we would also measure statistical significance. But it is not routine.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Occam's Razor

AUGUST 22, 2011

Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer. Tip #9: Leverage Statistical Control Limits. Tip#1: Statistical Significance. Search Engine Optimization (SEO) Metrics & Analytics. Web Analytics Career Advice: Statistics, Business, IT & Mushrooms.

KPI 124

KPI Metrics Measurement ROI 124

Insight

APRIL 28, 2020

You’ll often see the name “data challenge” used when the take-home assignment involves machine learning or statistics or “coding challenge” when the focus is on evaluating a candidate’s software engineering skills. Length: Highly Variable. Teams new to hiring often make this mistake of creating long multi-stage screening processes.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

Business Over Broadway

MAY 22, 2019

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Using Customer Journey Orchestration and AI to Optimize Customer Experience: [link]. So, become data literate.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Occam's Razor

JULY 24, 2018

The ability to optimize landing pages. Ignore the metrics produced as an experimental exercise nine months ago. For example, there is no need for any human to review Viewability because advanced display platforms optimize campaigns automatically against this metric. Is the distribution optimal? What do you see?

Analytics 93

Analytics Metrics Strategy Measurement 93

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Jet Global

APRIL 27, 2023

For your tax team to be agile, you’ll need to optimize tax technology and processes so you can both spot data insights and mitigate risk. Manufacturing organizations will succeed if they can adapt quickly to shifting supply chains and maintaining agility in reporting.

Manufacturing 52

Manufacturing Marketing Experimentation Risk 52

The Unofficial Google Data Science Blog

APRIL 16, 2019

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime. But these are not usually amenable to A/B experimentation.

Experimentation 68

Experimentation Sales Metrics Measurement 68

Occam's Razor

JUNE 6, 2007

Experimentation & Testing (A/B, Multivariate, you name it). What's the optimal organization structure (and who should own web analytics!)? The book takes a stand on issues, makes choices and cuts through the fog/FUD, in an attempt to make your life a tiny bit easier. It is a book about Web Analytics 2.0. Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

O'Reilly on Data

MARCH 23, 2023

Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. It was not optimized to provide correct responses. It has helped to write a book.

IT 260

IT Modeling Testing Risk 260

Corinium

APRIL 25, 2019

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

JULY 3, 2023

This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance. Buy Experimentation findings The following table shows Sharpe Ratios for various holding periods and two different trade entry points: announcement and effective dates.

Snapshot 82

Snapshot Data Lake Testing Strategy 82

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. So you don't have to worry about integrations with analytics tools, you don't have to worry about rushing to get a PhD in Statistics to interpret results and what not.

Testing 112

Testing Experimentation Risk Optimization 112

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. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

MAY 8, 2019

They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Perhaps if machine learning were solely being used to optimize advertising or ecommerce, then Agile-ish notions could serve well enough. PSL models are easy to use and fast.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

JUNE 6, 2011

1: Figure out the optimal career path for you. So in addition to becoming good at Omniture, Google Analytics, Baidu Analytics , pick one other tool from the Experimentation, Voice of Customer, Competitive Intelligence buckets of Web Analytics 2.0. This might seem odd. Analytics or start pimping your resume left and right.

Analytics 125

Analytics Consulting Statistics Marketing 125

Occam's Razor

FEBRUARY 8, 2021

From observing behavior closely, and from my own experimentation and failure, I've noticed consistent patterns in what great employees do and great bosses do. They find the external author of the statistical algorithm I want them to use, and ask them for guidance. They are there to nudge your career in an optimal direction.

Strategy 132

Strategy Statistics Cost-Benefit Marketing 132

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? Innovate on serviceability and optimize utilization. It would enable faster experimentation with easy, protected, and governed access to a variety of data.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

Occam's Razor

SEPTEMBER 13, 2016

Hypothesis development and design of experimentation. Take this as an example… How do you know that this is a profoundly sub-optimal collection of choices to provide? Ok, maybe statistical modeling smells like an analytical skill. . + Pattern recognition and understanding trends. Argumentation and logical thinking.

Modeling 127

Modeling Reporting Strategy Consulting 127