Peter James Thomas

SEPTEMBER 19, 2018

Here are 20 new definitions, including the first from other contributors (thanks Tenny!): Testing Data (Training Data). People are now also welcome to contribute their own definitions. The peterjamesthomas.com Data and Analytics Dictionary is an active document and I will continue to issue revised versions of it periodically.

Analytics 45

Analytics Testing Data Strategy Data Integration 45

IBM Big Data Hub

APRIL 13, 2023

SELECT count (*) FROM FLIGHT.FLIGHTS_DATA — — — 99879 Look into the scheme definition of the table. Creating train/test partitions of the dataset Before collecting deeper insights into the data, I’ll divide this dataset into train and test partitions using Db2’s RANDOM_SAMPLING SP.

Modeling 82

Modeling Statistics Machine Learning Testing 82

O'Reilly on Data

MARCH 26, 2024

But perhaps it should infringe something: even when the collection of data is legal (which, statistically, it won’t entirely be for any web-scale corpus), it doesn’t mean it’s legitimate, and it definitely doesn’t mean there was informed consent. To see this, let’s consider another example, that of MegaFace. joined Flickr.

Modeling 274

Modeling Machine Learning Risk Advertising 274

MLWhiz

NOVEMBER 10, 2019

P-Values are always a headache to explain even to someone who knows about them let alone someone who doesn’t understand statistics.

Statistics 74

Statistics Testing Modeling IT 74

datapine

JANUARY 6, 2022

First of all, let’s find a definition to understand what lies behind data interpretation meaning. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

JULY 24, 2023

We started by giving this data to the technical staff of the clubs, but we decided it was the moment to offer these advanced statistics to the fans and the media,” Bruno says. “We We had some tests in the laboratory first, and then we tested with the fans. We followed the design thinking process,” says Bruno. “We

Broadcasting 89

Broadcasting Recreation/Entertainment Testing Machine Learning 89

Cloudera

MAY 22, 2023

Report Standardization Take these steps: Inventory reports, including ownership, usage statistics, and report frequency. DB Standardization As before, inventory database assets, ownership, refresh frequency, and associated usage statistics. Target temporary/testing databases and user databases owned by former FTE.

Statistics 76

Statistics Data-driven Reporting Dashboards 76

Smart Data Collective

MARCH 28, 2022

It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. They can be again classified as random testing and optimization. This includes studying factors like test scores, teacher performances, and graduation rates. How to make the best use of data analytics.

Data Analytics 84

Data Analytics Software Analytics Statistics 84

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. Commonly used models include: Statistical models. They emphasize access to and manipulation of a model.

Data mining 134

Data mining Data-driven Statistics OLAP 134

IBM Big Data Hub

DECEMBER 18, 2023

Synthetic data is a statistical representation of reality. By definition, anomalous network performance is unpredictable. When an end user visits the web property, that JavaScript tag performs a series of tests which collect data on performance and availability. Those test results are then sent to NS1 Connect for analysis.

IT 64

IT Metrics Optimization Testing 64

datapine

JANUARY 24, 2021

You’ll want to be mindful of the level of measurement for your different variables, as this will affect the statistical techniques you will be able to apply in your analysis. There are basically 4 types of scales: *Statistics Level Measurement Table*. 5) Which statistical analysis techniques do you want to apply?

IT 317

IT Statistics KPI Data-driven 317

DataRobot Blog

APRIL 29, 2022

The regulators have provided a universal definition that has been adopted across the financial industry. They define a model to be “ a quantitative method, system, or approach that applies statistical, economic, financial, or mathematical theories, techniques, and assumptions to process input data into quantitative estimates. ”.

Risk 111

Risk Modeling IT Risk Management 111

Jen Stirrup

SEPTEMBER 30, 2021

Data Science – Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. This involves a number of sub tasks, including: Selecting the modelling technique Generate Test Design Building the model Assessing the Model.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

O'Reilly on Data

JULY 28, 2020

PULSE could be used for applications like upsampling video for 8K ultra high-definition, but I’m less interested in the algorithm and its applications than in the discussion about ethics that it provoked. When looked at this way, it’s largely a problem of mathematics and statistics. It’s an issue of harms and of power.

Testing 135

Testing Recreation/Entertainment Statistics Software 135

datapine

SEPTEMBER 29, 2022

What is the definition of data quality? It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. This way, you make sure there is a common understanding of data definitions that are being used across the organization. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

JULY 11, 2023

To make one, starting with the predetermined answer and working backward from there, employing such questionable practices as cherry-picked data, one-sided analyses, inappropriate statistical tests, and selective anecdotes to name a few, defining and justifying a strategic program whose success depends on … surprise! …

Consulting 71

Consulting IT Statistics Testing 71

Occam's Razor

MARCH 8, 2010

A very simple test can allow you to figure out if the metric you are dutifully reporting (or absolutely in love with) is gold or mud. It is called the Three Layers of So What test. What's this lovely test? Let's check out how you would conduct the "so what" test with a couple of examples. So what? "We

Metrics 117

Metrics Testing Key Performance Indicator KPI 117

CIO Business Intelligence

APRIL 11, 2022

We’re already seeing a range of activities, such as AI-driven services and development tools with AI bots being used in software testing. You already can find bug prediction tools such as Google’s w3C that make use of Machine Learning algorithms and deeper statistical analysis to find bad code.

Software 79

Software Data-driven Machine Learning Testing 79

datapine

MARCH 16, 2023

Here, you’ll learn the definition, its advantages in a business context, common types and their use cases as well as an insightful list of examples for different functions and industries. Let’s dive in with the definition. Your Chance: Want to test modern data visualization software for free? What Are Bar Charts & Graphs?

Visualization 196

Visualization KPI Cost-Benefit Dashboards 196

CIO Business Intelligence

MARCH 31, 2023

And the Bureau of Labor Statistics predicts that business analyst jobs will grow 11% from 2021 to 2031. The exam will test your knowledge in seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management.

Business Analysis 91

Business Analysis Testing Business Analytics Statistics 91

Alation

APRIL 18, 2023

In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today. Definition and purpose of data profiling Data profiling is the process of analyzing and assessing the quality, structure, and content of data. What is data profiling?

IT 52

IT Metadata Data Quality Data Governance 52

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Among these, only statistical uncertainty has formal recognition.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

CIO Business Intelligence

AUGUST 24, 2023

Retraining, deployment, operations, testing—a lot of these features just aren’t available yet.” Testing will only show the presence of errors, not the absence,” says Martin Fix, technology director at Star, a technology consulting company. “AI And it definitely foreshadows what’s to come if there’s federal regulation.”

Uncertainty 98

Uncertainty Risk Testing Enterprise 98

Cloudera

JUNE 28, 2022

A dashboard feeds from the Kudu database to show fraud summary statistics. NiFi is integrated with Schema Registry and it will automatically connect to it to retrieve the schema definition whenever needed throughout the flow. You can simply connect to the CDF console, upload the flow definition, and execute it.

Dashboards 88

Dashboards Machine Learning Statistics KPI 88

DataRobot

JUNE 8, 2021

Because it quantitatively identifies the common attributes of members of a group, it can inspire new persona definitions. The researchers set out to test whether consumers are more resistant to healthcare delivered by AI providers because of concerns that the AI will neglect the unique characteristics of their case. It can be unstable.

Data-driven 98

Data-driven Testing Marketing Experimentation 98

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

FineReport

MAY 18, 2024

Definition and Importance Visualizing data involves representing information through graphical elements like charts and graphs. In scientific research, histograms are commonly used to illustrate the distribution of test scores among students, providing insights into performance patterns and areas for improvement.

Visualization 52

Visualization Interactive Cost-Benefit Dashboards 52

Decision Management Solutions

JUNE 24, 2021

Leaning on this definition, we can define a Chain of Responsibility as a process for maintaining and documenting decision-making, showing who defined, modeled, trained, tested, and validated the decision-making approach that resulted in a specific decision. There are established protocols and procedures for this process.

Machine Learning 52

Machine Learning Testing Data-driven Modeling 52

AWS Big Data

DECEMBER 12, 2023

EMR Serverless application is only a definition and once created, can be re-used as long as needed. For our testing, we use the following files: The green/ folder has the file green_tripdata_2022-06.parquet Unlike EMR on EC2, you do not need to delete or terminate EMR Serverless applications.

Data Processing 90

Data Processing Management Statistics Interactive 90

Domino Data Lab

JULY 10, 2019

The model definition via a YAML file. Beginning their analytical strategy with a data type abstraction allowed the Uber engineering team to better integrate deep learning best practices for model training, validation, testing and deployment. Training a model in Ludwig only requires a CSV dataset and a model definition YAML file.

Deep Learning 110

Deep Learning Visualization Recreation/Entertainment Data Processing 110

AWS Big Data

JUNE 6, 2023

Set up and deploy the Lambda pipeline To test the solution, we can use the following AWS CloudFormation template. When the crawler is complete, you can see the AWS Glue Data Catalog table definition. After you create the table definition on the AWS Glue Data Catalog, you can use Athena to query the Data Catalog table.

Data Quality 72

Data Quality Metrics Visualization Dashboards 72

Data Science and Beyond

AUGUST 23, 2020

Previously, I encouraged readers to test different approaches to bootstrapped confidence interval (CI) estimation. The idea of using simulations to test bootstrapped CIs came from Tim Hesterberg’s What Teachers Should Know about the Bootstrap. The decision to use num_simulations =1,000 was informed by practical concerns (i.e.,

Testing 83

Testing IT Statistics Data Science 83

Domino Data Lab

OCTOBER 2, 2019

The case that might be familiar to you is an AB test. You can make a change to a product and test it against the original version of the product. The control group experiences the original algorithm, and the test group experiences the new version. Each person can be assigned to the test group or the control group, but not both.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

bridgei2i

JANUARY 25, 2022

I think as I mentioned earlier before the podcast that I’m introvert in general, but definitely not shy away when talking about topics of my interests in particular. The only thing is, you know, I understand what we do understand that, you know, using statistics using coding and everything, we will do amazing stuff.

Data Science 52

Data Science Machine Learning Data-driven Statistics 52

Occam's Razor

AUGUST 22, 2011

Five Reasons And Awesome Testing Ideas. Lab Usability Testing: What, Why, How Much. Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer. " The Definitive Guide To (8) Competitive Intelligence Data Sources! Tip #9: Leverage Statistical Control Limits.

KPI 124

KPI Metrics Measurement ROI 124

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. Because individual observations have so little information, statistical significance remains important to assess.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Data science is an interdisciplinary field within STEM that combines math and statistics, computer science, and business acumen to find patterns in complex datasets that can be used to improve decision making. What are Data Scientists?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45