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

FineReport

DECEMBER 11, 2019

Although this book may have been somewhat outdated in the present, many of the ideas in it are still very useful. Pay attention to the profound influence of social media on consumer behavior; present new consumer behavior characteristics in the new network environment; analyze new hotspot marketing and consumption events.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

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

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 137

Unstructured Data Data Analytics Analytics Structured Data 137

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

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 97

Cost-Benefit Modeling Manufacturing Interactive 97

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

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. Data was expensive to gather, and therefore decisions to collect data were generally well-considered.

Experimentation 61

Experimentation Testing Statistics Metrics 61

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

Occam's Razor

FEBRUARY 8, 2021

At different points of the day, sometimes from one minute to the next, I have to switch gears so that I can be fully present as both a good employee and a good people leader. 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.

Strategy 132

Strategy Statistics Cost-Benefit Marketing 132

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. Similarly, if the existing dataset has stocks that are not present in the new dataset, those records will remain expired with a status code of ‘expired’.

Snapshot 82

Snapshot Data Lake Testing Strategy 82

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

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. ML: social systems and context.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

AUGUST 22, 2011

Consultants, Analysts: Present Impactful Analysis, Insightful Reports. 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.

KPI 124

KPI Metrics Measurement ROI 124

Occam's Razor

JANUARY 9, 2012

It is a lot easier to predict the present. Rather, I'm going to share a clump of realities/rules garnered from the present to help ready you for the predictable near future. All while constantly optimizing your portfolio via controlled experiments. So I'm not going to do that. So I'm not going to do that either.

Marketing 140

Marketing B2B Measurement Risk 140

Occam's Razor

SEPTEMBER 13, 2016

Here is my slide the first time I presented the concept in a keynote… Cute, right? :). 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.

Modeling 127

Modeling Reporting Strategy Consulting 127

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

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. If you don't have a robust experimentation program in your company you are going to die. Part of it fueled by some Consultants. This is sad. Likely not.

Analytics 118

Analytics Consulting Metrics Experimentation 118

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. And you’ll be able to complete provisioning faster because data is presented in real-time, without needing to wait on data consolidation or processing.

Manufacturing 52

Manufacturing Marketing Experimentation Reporting 52

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). What's the optimal organization structure (and who should own web analytics!)? Qualitative and quantitative.

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 262

IT Modeling Testing Risk 262

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. Although it’s not perfect, [Note: These are statistical approximations, of course!] s lead may not be the optimal choice. Example 11.6

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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. But the simplicity ends there. Every transaction, every cent matters.

OLAP 94

OLAP Data Lake Data-driven Snapshot 94