DataKitchen

DECEMBER 29, 2022

The Terms and Conditions of a Data Contract are Automated Production Data Tests. The best data contract is an automated production data test. Data testing plays a critical role in the process of implementing data contracts. Data testing ensures that the data is transmitted and received accurately and consistently.

Testing 130

Testing Statistics Data Quality Data Integration 130

IBM Big Data Hub

SEPTEMBER 12, 2023

The UK government’s Ecosystem of Trust is a potential future border model for frictionless trade, which the UK government committed to pilot testing from October 2022 to March 2023. The models also reduce private sector customs data collection costs by 40%.

Testing 94

Testing Modeling Cost-Benefit Consulting 94

Analytics Vidhya

SEPTEMBER 27, 2022

Introduction My last blog discussed the “Training of a convolutional neural network from scratch using the custom dataset.” ” In that blog, I have explained: how to create a dataset directory, train, test and validation dataset splitting, and training from scratch. This blog is […].

Testing 358

Testing Data Science Publishing Analytics 358

Analytics Vidhya

JANUARY 2, 2024

Introduction In this technologically advanced era, programming languages come and go, but Python has stood the test of time, emerging as a titan in coding. Its simplicity, versatility, and robust community support have made it the go-to language for beginners and experts alike.

Testing 253

Testing Technology Analytics IT 253

Paul Blogs on BI

FEBRUARY 5, 2024

But watching that Roller Derby mashup game, it occurred to me that there may be a better way to determine if the service pack is ready for prime time in your environment and that is to install it on a test server and try things out – just like the mashup game with the “Minor Assaults”. You will find a lot of useful information about BI 4.3

Testing 52

Testing Reporting Business Objectives IT 52

Analytics Vidhya

OCTOBER 17, 2022

Introduction This article is part of blog series on Machine Learning Operations(MLOps). In the previous articles, we have gone through the introduction, MLOps pipeline, model training, model testing, model packaging, and model registering. We have seen how to train, test, package, and register […].

Modeling 330

Modeling Machine Learning Testing Data Science 330

Analytics Vidhya

APRIL 8, 2023

My latest blog post is jam-packed with fun and innovative experiments that I conducted with ChatGPT over the weekend. In this experiment, I put ChatGPT to the test and challenged it to […] The post How to Use ChatGPT as a Data Scientist? Introduction Are you a data scientist looking for an exciting and informative read?

Testing 348

Testing Analytics IT Data Science 348

Analytics Vidhya

DECEMBER 22, 2021

This article was published as a part of the Data Science Blogathon Dear readers, In this blog, let’s build our own custom CNN(Convolutional Neural Network) model all from scratch by training and testing it with our custom image dataset.

Modeling 370

Modeling Data Science Testing Publishing 370

Analytics Vidhya

JANUARY 2, 2024

Introduction In this technologically advanced era, programming languages come and go, but Python has stood the test of time, emerging as a titan in coding. Its simplicity, versatility, and robust community support have made it the go-to language for beginners and experts alike.

Testing 143

Testing Technology Analytics IT 143

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

FEBRUARY 23, 2024

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

Testing 120

Testing Data-driven Metrics Data Quality 120

DataRobot

MARCH 5, 2019

In a previous blog post , we introduced you to Zach Deane-Mayer, a data scientist who runs our core modeling team. One of the most important tools in his team’s arsenal is a data science performance evaluation system created and maintained by our QA team.

Testing 72

Testing Machine Learning Data Science Modeling 72

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

CDW Research Hub

APRIL 9, 2020

A healthcare system needed to respond rapidly to the COVID-19 pandemic with pop-up drive-through testing sites. But first they needed a way to secure network connections between testing sites and their data center. Field testing took place immediately, and equipment orders were placed later that day by Sirius.

Testing 94

Testing Technology IT 94

CDW Research Hub

JUNE 23, 2020

As virtual desktop infrastructure (VDI) gains popularity among enterprises across multiple industries, and with many desktops migrating to the cloud, testing your virtual desktop environment has never been so important. Here are three reasons why testing is so important before setting up a virtual desktop environment.

Testing 92

Testing Strategy Data Processing Optimization 92

Sisense

NOVEMBER 5, 2019

Informational sessions, user acceptance training, and performance load testing are all vital parts of making sure that your new software suits everyone’s needs and can handle the strains that your organization will throw at them. Load testing might be one of the most important parts of this process. What Is Load Testing?

Testing 75

Testing Analytics Dashboards Software 75

DataKitchen

DECEMBER 13, 2021

Without further ado, here are DataKitchen’s top ten blog posts, top five white papers, and top five webinars from 2021. Top 10 Blog Posts. Add DataOps Tests to Deploy with Confidence. We hope you and your family have happy holidays and we look forward to continuing your DataOps journey with you in the new year.

Data Architecture 246

Data Architecture Data Governance Testing Modeling 246

Domino Data Lab

JANUARY 20, 2019

These are the kind of questions Been Kim , Senior Research Scientist at Google Brain, poised in the MLConf 2018 talk , “Interpretability Beyond Feature Attribution: Testing with Concept Activation Vectors (TCAV)”. Testing with Concept Activation Vectors (TCAV): The Zebra. Would industry people be interested?

Testing 63

Testing Modeling Machine Learning Data Science 63

DataKitchen

AUGUST 9, 2021

The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., …. It can orchestrate a hierarchy of directed acyclic graphs ( DAGS ) that span domains and integrates testing at each step of processing.

Testing 246

Testing Data Lake Metadata Publishing 246

IBM Big Data Hub

SEPTEMBER 7, 2023

In the “Managing your cloud ecosystems” blog series, we cover different strategies for ensuring that your setup functions smoothly with minimal downtime. In the third blog of the series, we’re discussing migrating your worker nodes to a new Ubuntu operating system.

Management 88

Management Testing Optimization Strategy 88

DataKitchen

JANUARY 2, 2021

Blog: Deliver AI and ML Models at Scale with ModelOps. Blog: Improving Teamwork in Data Analytics with DataOps. These practices include CI/CD automation and automated testing. Blog: Add DataOps Tests for Error-Free Analytics. Blog: Add DataOps Tests to Deploy with Confidence.

Testing 130

Testing Machine Learning Reporting Modeling 130

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

DataKitchen

OCTOBER 5, 2021

In this blog, we’ll explore the role of the DataOps Engineer in driving the data organization to higher levels of productivity. A more technical discussion will follow in the next edition of this blog series. Instead of focusing on a narrowly defined task with minimal testing and feedback, DataOps focuses on adding value.

Testing 157

Testing Dashboards Measurement Experimentation 157

DataKitchen

JUNE 7, 2021

Test Coverage and Inventory Reports show the degree of test coverage of the data analytics pipeline. Maybe the test coverage report mentioned above helped you understand that your data operations pipeline needs more tests. Tests apply to code (analytics) and streaming data. Lower Error Rates.

Testing 130

Testing IT Measurement Data-driven 130

Insight

AUGUST 16, 2019

see below for the top 10 blog posts/resources! Getting Started with Data Engineering This blog post by Richard Taylor starts with a discussion of what big data and data engineering really mean before delving into an overview of the current landscape. What is Data Engineering and what is the role of a Data Engineer?

Big Data 51

Big Data Data Science Data Processing Machine Learning 51

Rocket-Powered Data Science

FEBRUARY 15, 2023

These rules are not necessarily “Rocket Science” (despite the name of this blog site), but they are common business sense for most business-disruptive technology implementations in enterprises. Keep it agile, with short design, develop, test, release, and feedback cycles: keep it lean, and build on incremental changes.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

DataKitchen

MARCH 5, 2024

ngx-toolkit, a new open-source project from DataKitchen At DataKitchen, we use Angular and strive for well-tested and maintainable code. See ngx-toolkit’s readme # rxjs-marbles In our app, we heavily use reactive programming, and we know how complicated it is to properly test observables chains.

Testing 146

Testing Software IT 146

O'Reilly on Data

FEBRUARY 16, 2023

There are excellent summaries of these failures in Ben Thompson’s newsletter Stratechery and Simon Willison’s blog. That’s what beta tests are for. Will it take weeks, months, or years to iron out the problems with Microsoft’s and Google’s beta tests? The important question is where we go from here.

Testing 210

Testing Statistics Modeling Optimization 210

Dataiku

MAY 26, 2023

We’ve previously explored what large language models (LLMs) are , how they can be used in an enterprise setting , and how the technology’s usefulness can be tested inside your organization. In this blog article, we’re taking a closer look at our OpenAI GPT integration and how it makes GPT technology even more accessible with Dataiku.

Testing 98

Testing Enterprise Technology Modeling 98

DataKitchen

DECEMBER 6, 2022

T est Automation : Business rules validation, test scripts management, test data management. Still, our job at DataKitchen is to make our customers successful so that in 2025, we can write another self-congratulatory blog post touting our position as the Magic Quadrant ‘leader’ in DataOps software!

Software 130

Software Marketing Data Lake Testing 130

Domino Data Lab

JULY 20, 2022

We've blogged before about the importance of model validation, a process that ensures that the model is performing the way it was intended and that it solves the problem it was designed to solve. Validations and tests are key elements to building machine learning pipelines you can trust.

Machine Learning 98

Machine Learning Testing Modeling Data Integration 98

IBM Big Data Hub

SEPTEMBER 5, 2023

In the “Managing your cloud ecosystems” blog series, we cover different strategies for ensuring that your setup functions smoothly with minimal downtime. In the second blog of the series, we’re discussing best practices for upgrading your clusters to newer versions.

Management 71

Management Testing Strategy IT 71

IBM Big Data Hub

NOVEMBER 10, 2023

Once loaded into the new system and formatted correctly, your first ERP test can be performed. Define what data transfer method you want to use and test it to be sure it is the right migration process. Test the ERP system All the preemptive steps have been taken and now it’s time to do some system testing before you go-live.

Enterprise 122

Enterprise Consulting Testing Cost-Benefit 122

DataKitchen

FEBRUARY 21, 2023

Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” Still, there is little testing and no consistent deployment processes, and everyone is very busy with ‘keeping the lights on’ by constantly chasing down errors in production systems.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

IBM Big Data Hub

FEBRUARY 16, 2024

Similar to other forms of security validation such as red teaming and penetration testing , BAS complements more traditional security tools by simulating cyberattacks to test security controls and provide actionable insights. BAS can also be used to run on-demand tests, as well as provide feedback in real time.

Testing 82

Testing IoT Reporting Data-driven 82

IBM Big Data Hub

FEBRUARY 1, 2024

To help prepare, many organizations are testing their incident response (IR) plans and teams with cyber range simulations. million in data breach costs compared to organizations without an IR team or IR plan testing. Organizations with an incident response team can save USD 1.5

Testing 94

Testing Data Processing Risk Consulting 94

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. Stratified sampling by component is in between.

Testing 58

Testing Experimentation Measurement Modeling 58