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 96

Experimentation Statistics Testing Knowledge Discovery 96

CIO Business Intelligence

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

JULY 31, 2024

This is where marketing teams will probably spend much of their time, as finding the right prompt to generate the optimal messaging to customers is very much a combination of art and science. Salesforce is pushing the idea that Einstein 1 is a vehicle for experimentation and iteration. AI is still a new and quickly evolving field.

Data Lake 119

Data Lake IT Sales Experimentation 119

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 120

Measurement Advertising Testing Marketing 120

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 157

Metrics KPI Analytics Key Performance Indicator 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

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 Data Science 137

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 346

IT Modeling Testing Risk 346

IBM Big Data Hub

MAY 17, 2024

” Given the statistics—82% of surveyed respondents in a 2023 Statista study cited managing cloud spend as a significant challenge—it’s a legitimate concern. Optimized: Cloud environments are now working efficiently and every new use case follows the same foundation set forth by the organdization.

Modeling 96

Modeling Cost-Benefit Optimization Digital Transformation 96

CIO Business Intelligence

AUGUST 21, 2024

The flashpoint moment is that rather than being based on rules, statistics, and thresholds, now these systems are being imbued with the power of deep learning and deep reinforcement learning brought about by neural networks,” Mattmann says. These projects include those that simplify customer service and optimize employee workflows.

Risk 136

Risk Insurance Cost-Benefit Software 136

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 105

Digital Transformation Cost-Benefit Informatics Data mining 105

AWS Big Data

JULY 8, 2024

In every Apache Flink release, there are exciting new experimental features. This flexibility optimizes job performance by reducing checkpoint frequency during backlog phases, enhancing overall throughput. You can find valuable statistics you can’t normally find elsewhere, including the Apache Flink Dashboard.

Management 115

Management Consulting Dashboards Snapshot 115

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 98

Manufacturing Testing Data Quality Dashboards 98

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 Data mining Reporting 98

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

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 126

Analytics Consulting Statistics Marketing 126

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 86

OLAP Data Lake Data-driven Online Analytical Processing 86

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

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

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

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

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 134

Strategy Statistics Cost-Benefit Marketing 134

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 Reporting Risk 52

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 45

Statistics Optimization Modeling Experimentation 45

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 95

Analytics Metrics Strategy Measurement 95

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 Manufacturing Modeling Interactive 89

AWS Big Data

SEPTEMBER 13, 2024

We expect statistically equal distribution of jobs between the two clusters. contains(GroupName, 'eks-cluster-sg-bpg-cluster-')].GroupId" spark-cluster-a-v and spark-cluster-b-v are configured with a queue named dev and weight=50. For more information, refer to Weight Based Cluster Selection. contexts[] | select(.name

Management 111

Management Snapshot Cost-Benefit Testing 111

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 105

Snapshot Data Lake Testing Strategy 105

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

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

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

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 59

Data Warehouse Unstructured Data Analytics Visualization 59

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

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. If we were using CBOW, then a window size of 5 (for a total of 10 context words) could be near the optimal value. Example 11.6

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 364

Marketing Experimentation Metrics Testing 364

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 103

Experimentation Testing Optimization Marketing 103

CIO Business Intelligence

APRIL 9, 2025

One of the most fundamental tenets of statistical methods in the last century has focused on correlation to determine causation. The quantitative models that make ML-enhanced analytics possible analyze business issues through statistical, mathematical and computational techniques.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102