CIO Business Intelligence

NOVEMBER 13, 2023

Transformational leaders must ensure their organizations have the expertise to integrate new technologies effectively and the follow-through to test and troubleshoot thoroughly before going live. Ensuring data quality, privacy, and security is essential.

Digital Transformation 137

Digital Transformation Cost-Benefit Experimentation Measurement 137

Octopai

MAY 2, 2022

A successful data analytics team is one that can increase the quantity of data analytics products they develop in a given time while ensuring (and ideally, improving) the level of data quality. Through jidoka, quality problems are stopped in their tracks and prevented from reaching the consumer. . Enter DataOps.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

Alation

SEPTEMBER 28, 2022

DataOps strategies share these common elements: Collaboration among data professionals and business stakeholders. Easy-to-experiment data development environment. Automated testing to ensure data quality. There are many inefficiencies that riddle a data pipeline and DataOps aims to deal with that.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

O'Reilly on Data

MARCH 31, 2020

The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

Smarten

NOVEMBER 3, 2017

These tools should include: Self-Serve Data Preparation – Allows business users to perform Advanced Data Discovery and auto-suggests relationships, reveals the impact and importance of key factors, recommends data type casts, data quality improvements and more!

Analytics 40

Analytics Visualization Experimentation Cost-Benefit 40

Occam's Razor

AUGUST 22, 2011

Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. Data Quality Sucks, Let's Just Get Over It. Five Reasons And Awesome Testing Ideas. Lab Usability Testing: What, Why, How Much. Who Owns Web Analytics?

KPI 124

KPI Metrics Measurement ROI 124

DataKitchen

APRIL 13, 2021

Testing and Data Observability. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Genie — Distributed big data orchestration service by Netflix.

Testing 307

Testing Machine Learning Consulting Data Quality 307

O'Reilly on Data

OCTOBER 13, 2020

In Bringing an AI Product to Market , we distinguished the debugging phase of product development from pre-deployment evaluation and testing. During testing and evaluation, application performance is important, but not critical to success. require not only disclosure, but also monitored testing. Debugging AI Products.

Management 244

Management Metrics Machine Learning Modeling 244

Occam's Razor

NOVEMBER 13, 2009

I am a Mechanical Engineer with a MBA, a late covert to the power of understanding the super sexy "why" by leveraging lab usability studies, surveys, card sorts, online remote testing and more. Chapter 7 Failing Faster: Unleashing the Power of Testing and Experimentation. You get a jump start. It was hard.

Analytics 71

Analytics Metrics Measurement Testing 71

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. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Alation

DECEMBER 14, 2021

These systems offer numerous web-centric features that bolster customer service and engagement, provide server scalability during periods of fluctuating traffic, and allow easy experimentation with new technologies and promotional strategies. Cloud testing. Optimized business continuity. Let’s start with some simple definitions.

Cost-Benefit 52

Cost-Benefit Data Processing Optimization Consulting 52

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Dealing with data quality doubt is every day and, sadly, very complex challenge for many, if not most, of us. They also reveal things that starting to become scary (Privacy!

Modeling 124

Modeling Metrics Data Quality Data-driven 124

CIO Business Intelligence

APRIL 15, 2024

Given the speed required, Lowden established a specialized team for the project to encourage a culture of experimentation and “moving fast to learn fast.” “You Three layers of content integrity Another big part of ensuring the integrity of the content was testing, which consisted of three layers. We don’t write all the code.

Testing 76

Testing Experimentation Data Quality Machine Learning 76

datapine

JANUARY 31, 2022

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214