The Unofficial Google Data Science Blog

OCTOBER 31, 2016

By PATRICK RILEY For a number of years, I led the data science team for Google Search logs. We were often asked to make sense of confusing results, measure new phenomena from logged behavior, validate analyses done by others, and interpret metrics of user behavior. Why has this document resonated with so many people over time?

Metrics 107

Metrics Measurement Statistics Data Collection 107

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book? Unfortunately, that API does not permit collection of synopses.

Modeling 59

Modeling Metadata Publishing Sales 59

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. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Alation

OCTOBER 12, 2022

Companies collect and analyze vast amounts of data to make informed business decisions. From product development to customer satisfaction, nearly every aspect of a business uses data and analytics to measure success and define strategies. Some examples of quantitative data include: Counts or units, stored as raw numbers.

Statistics 52

Statistics Sales Testing Marketing 52

erwin

APRIL 21, 2020

By combining physical system catalogs, critical data elements, and key performance measures with clearly defined product and sales goals, you can manage the effectiveness of your business and ensure you understand what critical systems are for business continuity and measuring corporate performance.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

One example is the European Union (EU) Open Data Portal , which is used to document, catalog and govern EU data related to the pandemic. So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance. Clearly Document Data Policies and Rules.

Measurement 96

Measurement Sales Data Governance Metadata 96

Domino Data Lab

AUGUST 12, 2021

Taking a closer look at the data you will notice that some columns have questions marks ? For this dataset that is the way the data collection denotes missing data. Let’s look at some examples of the data in the dataset: masses.iloc[[20, 456, 512],:]. Severity is made out of integers. Pandas Profiler.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

FineReport

JUNE 26, 2023

These reports commonly incorporate graphical elements such as charts, graphs, tables, and statistics, which complement the text-based information and offer visual representation. Serving as foundational documents : Performance reports serve as the groundwork for other reports and documentation.

Reporting 52

Reporting Key Performance Indicator Sales Visualization 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. The book contains a cd with six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. [If Bonus: Interactive CD.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. In other words, D&A plays a key role in the foundational measuring angle. This was not statistic and we have not really explored this in any greater detail since. I suspect we should. – Yes and no.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. In the real world, things are never this easy, and it is a battle to get the data into the correct shape as we will see later in this chapter. shows the output in Jupyter Notebook of the describe command.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Jet Global

MAY 15, 2020

A financial Key Performance Indicator (KPI) or metric is a quantifiable measure that a company uses to gauge its financial performance over time. Under modern day reporting standards, companies are formally obligated to present their financial data in the following statements: balance sheet, income statement, and cash flow statement.

Metrics 98

Metrics Finance Reporting KPI 98

O'Reilly on Data

OCTOBER 18, 2022

If you’re thinking of a less formal internal assessment, the influential Closing the AI Accountability Gap puts forward a solid framework with worked documentation examples. We also tend to use standards from US nondiscrimination law and the NIST SP1270 guidance to fill in any gaps around bias measurement or specific LLM concerns.

Risk Management 297

Risk Management Risk Testing Measurement 297

datapine

AUGUST 29, 2022

Most people are aware that companies collect our GPS locale, text messages, credit card purchases, social media posts, Google search history, etc., and this book will give you an insight into their data collecting procedures and the reasons behind them.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

AUGUST 20, 2019

Real-world datasets can be missing values due to the difficulty of collecting complete datasets and because of errors in the data collection process. Drop a column from a table—either based on a principled argument (we know the two columns are measuring the same thing) or based on a randomness. Filling missing values.

Testing 68

Testing Modeling Interactive Measurement 68

datapine

APRIL 16, 2019

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. What Is Data Driven Decision Making? Quantitative data analysis focuses on numbers and statistics.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

DataKitchen

JANUARY 23, 2023

Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements. Data testing can be done through various methods, such as data profiling, Statistical Process Control, and quality checks.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

NOVEMBER 2, 2021

University KPIs are the tools that many universities use to measure their success and progress towards their goals. Those without KPIs are left without any valuable statistics, while those with established performance tracking dashboards are able to make data driven decisions. Effective Data Collection.

Metrics 52

Metrics Reporting KPI Key Performance Indicator 52

Jet Global

MAY 1, 2023

Manage compliance through up-to-the-minute performance measures, workflow automation, and essential regulatory reports. Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. Use the experts in analytics to add value to your product.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52