DataCamp

MAY 5, 2020

This tutorial will define statistical bias in a machine learning model and demonstrate how to perform the test on synthetic data.

Machine Learning 96

Machine Learning Statistics Testing Measurement 96

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. Insights worth testing. The entire online experimentation canon is filled with landing page optimization type testing. You can test landing pages.

Experimentation 101

Experimentation Testing Optimization Marketing 101

The Unofficial Google Data Science Blog

JULY 18, 2023

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Researchers and practitioners have been using human-labeled data for many years, trying to understand all sorts of abstract concepts that we could not measure otherwise. That’s the focus of this blog post.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

KDnuggets

JANUARY 24, 2023

Leading expert Ronny Kohavi, drawing from his 20+ years of experience, will walk you through the ins and outs of experimentation, identifying key insights and working through live demos in his live course, Accelerating Innovation with A/B Testing, starting January 30th.

Experimentation 73

Experimentation Testing Measurement 73

O'Reilly on Data

OCTOBER 30, 2023

adversarial testing to determine a model’s flaws and weak points), and not a wider range of information that would help to address many of the other concerns outlined in the EO. The EO seems to be requiring only data on the procedures and results of “Red Teaming” (i.e. Policy on use of user data for further training.

Measurement 296

Measurement Risk Modeling Metrics 296

Analytics Vidhya

AUGUST 5, 2022

Hypothesis testing is used to look if there is any significant relationship, and we report it using a p-value. Measuring the strength of that relationship […]. Introduction One of the most important applications of Statistics is looking into how two or more variables relate.

Statistics 318

Statistics Measurement Testing Data Science 318

datapine

FEBRUARY 9, 2024

The process helps businesses and decision-makers measure the success of their strategies toward achieving company goals. How does Company A measure the success of each individual effort so that it can isolate strengths and weaknesses? Key performance indicators enable businesses to measure their own ability to set and achieve goals.

KPI 221

KPI Management Key Performance Indicator Measurement 221

O'Reilly on Data

OCTOBER 12, 2021

We know how to test whether or not code is correct (at least up to a certain limit). Given enough unit tests and acceptance tests, we can imagine a system for automatically generating code that is correct. But we don’t have methods to test for code that’s “good.” There are lots of ways to sort.

Testing 300

Testing Measurement Consulting Modeling 300

DataKitchen

SEPTEMBER 20, 2021

The best way to ensure error-free execution of data production is through automated testing and monitoring. The DataKitchen Platform enables data teams to integrate testing and observability into data pipeline orchestrations. Automated tests work 24×7 to ensure that the results of each processing stage are accurate and correct.

Testing 246

Testing Metrics Measurement Dashboards 246

DataRobot

MAY 27, 2021

In particular, Mina believes that our failure to test effectively has allowed COVID-19 to spread. True, there are tests—and they are good ones—but they are relatively expensive, require an outside laboratory, and take two days or more for results. This is testing where people test themselves multiple times a week.

Testing 98

Testing Machine Learning Measurement Publishing 98

DataKitchen

APRIL 18, 2024

The most effortless way to institute comprehensive, agile data quality testing is to derive actionable information, start testing and measuring immediately, and then iterate, using tests and results to refine. But our open-source tools are not hobbled in testing and observing. And a way to configure more tests.

Testing 120

Testing Data Quality Enterprise Data Analytics 120

datapine

OCTOBER 11, 2023

A Warehouse KPI is a measurement that helps warehousing managers to track the performance of their inventory management, order fulfillment, picking and packing, transportation, and overall operations. These powerful measurements will allow you to track all activities in real-time to ensure everything runs smoothly and safely.

Metrics 217

Metrics KPI Management Cost-Benefit 217

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Cloudera

DECEMBER 18, 2020

When running any performance benchmarking tool on your cluster, a critical decision is always what data set size should be used for a performance test, and here we demonstrate why it is important to select a “good fit” data set size when running a HBase performance test on your cluster. Test Methodology.

Testing 58

Testing Measurement IT Management 58

DataKitchen

MARCH 5, 2024

Implementing rigorous DataOps Observability practices, including automated testing, observability tools, and a culture of continuous improvement, can transform how your team addresses data reliability and accuracy. Not hearing about errors is not a sign to rest easy but a call to action for deeper investigation and proactive measures.

Data Quality 150

Data Quality Measurement Testing Data-driven 150

O'Reilly on Data

JUNE 15, 2023

If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. And they are stress testing and “ red teaming ” them to uncover vulnerabilities. That is a crucial first step, and we should take it immediately.

Metrics 283

Metrics Reporting Measurement Finance 283

DataKitchen

MARCH 12, 2024

We kept adding tests over time; it has been several years since we’ve had any major glitches. DataKitchen helped us completely transform our operations by broadening our testing definition. Tests assess important questions, such as “Is the data correct?”

Metrics 120

Metrics Software Cost-Benefit Testing 120

bridgei2i

MAY 15, 2020

While citizens are taking extreme caution with preventive measures, as of today, a sustainable solution, along the lines of a vaccine, is nowhere in sight. Instead, our energies are focused on arresting the spread of the pandemic by testing as many people as possible. Curious about the details? To read the whitepaper fill the form.

Optimization 52

Optimization Testing Strategy Measurement 52

DataKitchen

NOVEMBER 18, 2022

It is the measure of data sets at any point in time. Data Observability is dynamic — it is the testing of data, integrated data, and tools acting upon data — as it is processed — that checks for flow rates and data errors. Data Observability tools test data in the database. Data Quality is static.

Data Quality 130

Data Quality Testing Measurement Data Integration 130

Occam's Razor

SEPTEMBER 15, 2011

Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. This article guides you in understanding the value of the Digital Marketing & Measurement Model (notice the repeated emphasis on Marketing, not just Measurement), and how to create one for yourself. Acquisition.

Measurement 166

Measurement Marketing Modeling Key Performance Indicator 166

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. Data and tool tests. Observability users are then able to see and measure the variance between expectations and reality during and after each run.

Testing 130

Testing Statistics Measurement Metrics 130

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Below we will explain how to virtually eliminate data errors using DataOps automation and the simple building blocks of data and analytics testing and monitoring. . Tie tests to alerts.

Testing 214

Testing Manufacturing Data Quality Statistics 214

DataKitchen

OCTOBER 27, 2022

The first step in solving that pain is to observe what’s happening with your data and analytics ‘estate’ and stick little thermometers at various points in the process and measure. You can’t improve what you can’t measure. Is it late? Is the raw data correct? Why Observability first DataOps?

Dashboards 130

Dashboards Measurement Testing Modeling 130

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? Under Velocity, the Mean Time to Deliver Data metric measures the time it takes to deliver data. The Data Change Request Ratio metric measures the rate of business demand for data. The Mean Time to Recovery metric measures how quickly defects can be resolved. Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

DataKitchen

APRIL 13, 2021

Testing and Data Observability. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Testing and Data Observability. Production Monitoring and Development Testing.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

OCTOBER 28, 2021

As the industry’s understanding of AI bias matures, model developers are getting better at defining and measuring bias. When you buy a car, you can be sure that the factory has tested every component and subsystem. The car is tested before it is sold and then monitored while in operation.

Testing 130

Testing IT Manufacturing Metrics 130

DataKitchen

JUNE 7, 2021

Hopefully, with metrics in place, you can show measured improvements in productivity and quality that will win converts. DataOps includes four key objectives: Measure Your Process – As data professionals, we advocate for the benefits of data-driven decision making. Measure Your Process. DataOps Objectives. Lower Error Rates.

Testing 130

Testing IT Measurement Data-driven 130

Analytics Vidhya

DECEMBER 11, 2023

In this guide, we’ll explore the vital role of algorithm efficiency and its measurement using notations. Algorithm efficiency isn’t just for computer scientists; it’s for anyone who writes code.

Measurement 240

Measurement Optimization Technology Analytics 240

CIO Business Intelligence

FEBRUARY 13, 2024

IT leaders are drowning in metrics, with many finding themselves up to their KPIs in a seemingly bottomless pool of measurement tools. Still, when all is said and done, some key metrics stand out above the rest for accurately measuring IT success. There are a number of ways to measure value. Here they are.

Metrics 138

Metrics IT ROI Measurement 138

datapine

FEBRUARY 3, 2022

Your Chance: Want to test a professional KPI and metrics software? Essentially, Key Performance Indicators or KPIs measure performance or progress based on specific business goals and objectives. Companies usually visualize these measurements together with the help of interactive KPI reports. What Are KPIs? What Are Metrics?

Metrics 189

Metrics KPI Key Performance Indicator Sales 189

Domino Data Lab

JANUARY 20, 2019

What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? Testing with Concept Activation Vectors (TCAV): The Zebra. Introduction. with post-training explanations? on a global level instead of a local level ?

Testing 63

Testing Modeling Machine Learning Data Science 63

CIO Business Intelligence

MARCH 3, 2024

One component of corporate IT that has long been ‘in range’ for cyber criminals that is often overlooked when protection measures are being put in place are multifunction printers – widely used in almost every organisation. Doing penetration testing. uniFLOW is one such tool offered by Canon.

IT 100

IT Measurement Risk Testing 100

DataKitchen

NOVEMBER 20, 2021

A DataOps Engineer can make test data available on demand. We have automated testing and a system for exception reporting, where tests identify issues that need to be addressed. It then autogenerates QC tests based on those rules. You can track, measure and create graphs and reporting in an automated way.

Testing 246

Testing Machine Learning Data Warehouse Reporting 246

DataKitchen

APRIL 26, 2021

GSK had been pursuing DataOps capabilities such as automation, containerization, automated testing and monitoring, and reusability, for several years. DataOps provides the “continuous delivery equivalent for Machine Learning and enables teams to manage the complexities around continuous training, A/B testing, and deploying without downtime.

Measurement 246

Measurement Metrics Data-driven Testing 246

CIO Business Intelligence

APRIL 23, 2024

To stay out of harm’s way, charter a few harmless initiatives — ones that aren’t likely to succeed, will pass the cool test if, in the off chance, they do happen to succeed, but won’t do much damage if they fail. Which is to say if your preventive measures work, you’ll be found guilty of having cried wolf — of inflating the risk.

Risk 91

Risk IT Insurance Risk Management 91

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). The Core Responsibilities of the AI Product Manager.

Marketing 362

Marketing Experimentation Metrics Testing 362

DataKitchen

NOVEMBER 29, 2021

Model developers will test for AI bias as part of their pre-deployment testing. Quality test suites will enforce “equity,” like any other performance metric. Continuous testing, monitoring and observability will prevent biased models from deploying or continuing to operate. Companies Commit to Remote.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245