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

Jet Global

APRIL 27, 2023

These changes create an ever-increasing demand on manufacturing tax departments to report on cross-border situations and transactions. Manufacturing organizations will succeed if they can adapt quickly to shifting supply chains and maintaining agility in reporting.

Manufacturing 52

Manufacturing Marketing Experimentation Reporting 52

DataRobot Blog

JANUARY 17, 2023

TRACE, Asian bond market reporting, ECNs’ trade history) as well as a clear set of more liquid assets which can be used as predictors (e.g., Not actually being a machine learning problem: Value-at-Risk modeling is the classic example here—VaR isn’t a prediction of anything, it’s a statistical summation of simulation results.

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

Business Over Broadway

FEBRUARY 21, 2021

As such, data science requires three broad skill sets , including subject matter expertise, statistics/math and technology/programming. Experimentation and iteration to improve existing ML models (25%). Data professionals who reported two activities included Machine Learning Engineer, Data Engineer and Research Scientist.

Machine Learning 60

Machine Learning Statistics Data Science Experimentation 60

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). They cannot process language inputs generally. Examples: (1) Automated manufacturing assembly line. (2) 4) Prosthetics.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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

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). If you’ve created a useful reporting process or dashboard segment, no one need ever waste time reinventing it.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

Ontotext

FEBRUARY 14, 2024

Data integration If your organization’s idea of data integration is printing out multiple reports and manually cross-referencing them, you might not be ready for a knowledge graph. As a statistical model, LLM inherently is random. Experimentation is important, but be explicit when you do. Start with “why?”

Recreation/Entertainment 105

Recreation/Entertainment Data Integration Modeling Data Quality 105

CIO Business Intelligence

DECEMBER 6, 2023

And in addition to having generative AI cite the sources of key information, consider ways to highlight elements that are important to double check, like dates, statistics, policies, or precedents that are being relied on. Human reviewers should be trained to critically assess AI output, not just accept it at face value.”

IT 130

IT Risk Management Interactive Modeling 130

O'Reilly on Data

APRIL 19, 2021

The percentage of respondents reporting “mature” practices has been roughly the same for the last few years. This is almost exactly in line with the results from 2020, where 25% of the respondents reported that they had products in production (“Mature” wasn’t a possible response in the 2020 survey.). Bottlenecks to AI adoption.

Enterprise 353

Enterprise Modeling Risk Manufacturing 353

CIO Business Intelligence

MARCH 21, 2022

Data scientists are often engaged in long-term research and prediction, while data analysts seek to support business leaders in making tactical decisions through reporting and ad hoc queries aimed at describing the current state of reality for their organizations based on present and historical data.

Unstructured Data 133

Unstructured Data Data Analytics Analytics Structured Data 133

FineReport

DECEMBER 19, 2019

Taking FineReport as an example, it is a BI reporting tool that can connect to various data sources, quickly analyze the data, and make various reports and cool dashboards. You can complete real-time report through simple drag and drop operations. It can produce a variety of complex reports. Reporting of FineReport.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Paul DeBeasi

JANUARY 30, 2019

Machine learning projects are inherently different from traditional IT projects in that they are significantly more heuristic and experimental, requiring skills spanning multiple domains, including statistical analysis, data analysis and application development. New Gartner Research.

Machine Learning 56

Machine Learning IoT Experimentation Statistics 56

DataRobot Blog

JULY 28, 2022

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 The first baseline model we created used spectrograms of speech waveform data, statistical features, and spectrogram images. Industry Analyst Report. Download Now.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Smarten

MAY 11, 2017

Advanced Data Discovery ensures data democratization by enabling users to drastically reduce the time and cost of analysis and experimentation. Plug n’ Play Predictive Analysis enables business users to explore power of predictive analytics without indepth understanding of statistics and data science.

Experimentation 49

Experimentation Visualization Business Intelligence Predictive Analytics 49

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

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. Nearly all respondents reported promising early results from gen AI experiments and planned to increase their spending in 2024 to support production workloads.

Cost-Benefit 92

Cost-Benefit Modeling Manufacturing Interactive 92

DataRobot

JUNE 8, 2021

Although modern medicine is founded on rigorous experimental design and statistical analysis, and many research studies have shown the superiority of objective analysis over human intuition, medical AI adoption will depend on consumer receptivity and trust in this new technology. But beware of selling or buying consumer data.

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., They have a forthcoming report on automation-focused platforms this year. Code-first data science platforms. Jupyter) or IDEs (e.g.,

Data Science 65

Data Science Marketing Data-driven Statistics 65

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. 5 Tags, CMS, Reports & Regressions: All Included! they contain all reporting built in and the data is not that hard to understand. So as my tiny gift for you here are five experimentation and testing ideas for you. And I meant every word of it.

Testing 112

Testing Experimentation Risk Optimization 112

Occam's Razor

AUGUST 22, 2011

Delibrate Your Data, Dig Into Your Data, Reimagine Content Reporting. The Difference Between Web Reporting And Web Analysis. Refuse Report Requests. Consultants, Analysts: Present Impactful Analysis, Insightful Reports. Produce Actionable Insights: Mate Custom Reports With Adv Segments! Web Analytics Demystified.

KPI 124

KPI Metrics Measurement ROI 124

Domino Data Lab

DECEMBER 4, 2020

Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). The drug under investigation is an anti-inflammatory agent, and the study looks at self-reported pain relief and plasma concentration over time. In this tutorial we will use JupyterLab.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Smarten

JULY 3, 2017

So, if a business users wants to find and analyze data, that user must depend on others to understand the user’s needs, gather the data and create the report. By the time the user receives the report, the data may be outdated or it may be presented in a way that makes it difficult to interpret and use.

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40

Occam's Razor

SEPTEMBER 13, 2016

If you are open to being challenged… then here are the short-stories inside this post… The World Needs Reporting Squirrels. The World Needs Reporting Squirrels. If you are curious, here is a April 2011 post: The Difference Between Web Reporting And Web Analysis. Hypothesis development and design of experimentation.

Modeling 127

Modeling Reporting Strategy Consulting 127

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? Traditional systems are siloed, hard to access and often structured to serve traditional reports. Before now, this was really hard to do. Legacy systems do not scale with the new data needs.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

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. In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

SEPTEMBER 28, 2022

Monitoring and reporting of processes. This includes everything from data storage and warehousing solutions to artificial intelligence and analytics reporting tools. Technical environments and IDEs must be disposable so that experimental costs can be kept to a minimum. Easy-to-experiment data development environment. Simplicity.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

O'Reilly on Data

MARCH 23, 2023

There are more that I haven’t listed, and there will be even more by the time you read this report. That statement would certainly horrify the researchers who are working on them, but at the level we can discuss in a nontechnical report, they are very similar. Why are we starting by naming all the names?

IT 258

IT Modeling Testing Risk 258

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. LogMeIn’s Forrester Survey Reports AI Widens Gap Between Customer Experience and Marketing Teams: [link].

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

The Unofficial Google Data Science Blog

JULY 31, 2016

To figure this out, let's consider an appropriate experimental design. In other words, the teacher is our second kind of unit, the unit of experimentation. This type of experimental design is known as a group-randomized or cluster-randomized trial. When analyzing the outcome measure (e.g.,

Experimentation 42

Experimentation Testing Measurement Metrics 42

Occam's Razor

SEPTEMBER 19, 2011

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). * ask for a raise. It is that simple. Okay, it is not simple.

Measurement 119

Measurement Advertising Testing Marketing 119

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. You can report Gross Profit in real-time, of course, but doing so is almost entirely useless. Ignore the metrics produced as an experimental exercise nine months ago.

Analytics 93

Analytics Metrics Strategy Measurement 93

The Unofficial Google Data Science Blog

MAY 31, 2016

A geo experiment is an experiment where the experimental units are defined by geographic regions. Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. They are non-overlapping geo-targetable regions.

Advertising 42

Advertising Testing Sales Statistics 42

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. When it comes to proving which campaigns are better and which numbers to report to the management what will you do? Part of it fueled by some Consultants.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Go to the Multi-Channel Funnels folder in Google analytics and look at two other yummy reports: Time Lag and Path Length. I don’t mean: BUY IT NOW OR ELSE! Sizing the Opportunity.

Strategy 124

Strategy Cost-Benefit Testing Sales 124

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. As the O’Reilly surveys and other recent reports have demonstrated, the state of “Product Management for AI” is still barely even evolved to a primordial soup stage.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Remember that the raw number is not the only important part, we would also measure statistical significance. Online, offline or nonline. The result?

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156