O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 363

Management Machine Learning Experimentation Metrics 363

DataKitchen

NOVEMBER 5, 2024

Data is typically organized into project-specific schemas optimized for business intelligence (BI) applications, advanced analytics, and machine learning. Similarly, downstream business metrics in the Gold layer may appear skewed due to missing segments, which can impact high-stakes decisions.

Data Quality 195

Data Quality Testing Metrics Reporting 195

O'Reilly on Data

MARCH 25, 2025

People have been building data products and machine learning products for the past couple of decades. Business value : Once we have a rubric for evaluating our systems, how do we tie our macro-level business value metrics to our micro-level LLM evaluations? How will you measure success? This isnt anything new.

Testing 174

Testing Data-driven Software Measurement 174

CIO Business Intelligence

JANUARY 23, 2024

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). He suggests, “Choose what you measure carefully to achieve the desired results.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

O'Reilly on Data

MAY 14, 2020

This role includes everything a traditional PM does, but also requires an operational understanding of machine learning software development, along with a realistic view of its capabilities and limitations. In addition, the Research PM defines and measures the lifecycle of each research product that they support.

Management 364

Management Experimentation B2B Machine Learning 364

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Why aren’t traditional software tools sufficient?

Modeling 249

Modeling Machine Learning Testing Metrics 249

KDnuggets

SEPTEMBER 20, 2022

When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results.

Metrics 160

Metrics Measurement Optimization Modeling 160

Smart Data Collective

NOVEMBER 7, 2023

If you’re eager to monetize the web hosting services you offer to third party site owners, or you have a selection of self-hosted sites which you are eager to wring more cash out of, then machine learning could be the answer. This is where machine learning from top developers comes into play.

Data Processing 124

Data Processing Machine Learning Measurement Optimization 124

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. While useful, these constructs are not beyond criticism. Monitoring.

Management 314

Management Machine Learning Metrics Modeling 314

DataRobot Blog

JULY 21, 2022

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Cloudera

NOVEMBER 17, 2021

We are very excited to announce the release of five, yes FIVE new AMPs, now available in Cloudera Machine Learning (CML). In addition to the UI interface, Cloudera Machine Learning exposes a REST API that can be used to programmatically perform operations related to Projects, Jobs, Models, and Applications.

Machine Learning 124

Machine Learning Visualization Data Science Dashboards 124

DataKitchen

APRIL 26, 2021

Workiva also prioritized improving the data lifecycle of machine learning models, which otherwise can be very time consuming for the team to monitor and deploy. Multiple Metrics for Success. Workiva uses a broad range of metrics to measure success. Measure, measure, measure is really a critical piece.

Measurement 246

Measurement Metrics Data-driven Dashboards 246

Smart Data Collective

APRIL 1, 2020

Tracking the right metrics is an important part of running a successful business. When your company is offering software as a service, the need for tracking certain metrics becomes dire, and in this post, we are talking about those metrics. Here you will read about four metrics that are super crucial for your SaaS business.

Big Data 121

Big Data Metrics Machine Learning Optimization 121

DataKitchen

APRIL 13, 2021

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. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Collaboration and Sharing.

Testing 300

Testing Machine Learning Consulting Data Science 300

O'Reilly on Data

NOVEMBER 19, 2024

While RAG leverages nearest neighbor metrics based on the relative similarity of texts, graphs allow for better recall of less intuitive connections. presented the TRACE framework for measuring results, which showed how GraphRAG achieves an average performance improvement of up to 14.03%.

Unstructured Data 318

Unstructured Data Structured Data Modeling Statistics 318

David Menninger's Analyst Perspectives

OCTOBER 9, 2024

Unfortunately, we expect that through 2026, model governance will remain a significant concern for more than one-half of enterprises, limiting the deployment, and therefore the realized value of AI and machine learning (ML) models. One of the most important steps is to establish and track metrics that measure bias.

Metrics 147

Metrics Measurement Machine Learning Modeling 147

Smart Data Collective

DECEMBER 14, 2020

Customer satisfaction (CSAT) metrics are a powerful tool for businesses, but despite the way we talk about it, satisfaction isn’t something you can easily measure. Just as NPS asks people about a specific action or scenario, other useful KPIs for measuring CSAT ask customers to make comparisons based on their own personal metrics.

Measurement 99

Measurement Metrics Machine Learning Data Collection 99

DataRobot Blog

APRIL 21, 2022

Machine learning, and especially deep learning, has become increasingly more accurate in the past few years. Here, model size is measured by the amount of floating-point operations. Measure efficiency, not only accuracy. Machine learning has been obsessed with accuracy — and for good reason.

Deep Learning 145

Deep Learning Machine Learning Metrics Measurement 145

Rocket-Powered Data Science

DECEMBER 15, 2018

This wisdom applies not only to life but to machine learning also. Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning. A related problem also arises in unsupervised machine learning.

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

AWS Big Data

JANUARY 15, 2025

Improve accuracy and resiliency of analytics and machine learning by fostering data standards and high-quality data products. In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications.

IoT 101

IoT Machine Learning Metadata Data-driven 101

DataRobot Blog

APRIL 22, 2022

In our previous post , we talked about how red AI means adding computational power to “buy” more accurate models in machine learning , and especially in deep learning. We also talked about the increased interest in green AI, in which we not only measure the quality of a model based on accuracy but also how big and complex it is.

Machine Learning 98

Machine Learning Measurement Deep Learning Manufacturing 98

Corinium

JUNE 6, 2019

A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment. It is also important to have a strong test and learn culture to encourage rapid experimentation. Build multiple MVPs to test conceptually and learn from early user feedback.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Rocket-Powered Data Science

JULY 21, 2023

Here are four specific metrics from the report, highlighting the potentially huge enterprise system benefits coming from implementing Splunk’s observability and monitoring products and services: Four times as many leaders who implement observability strategies resolve unplanned downtime in just minutes, not hours or days.

Machine Learning 190

Machine Learning Metrics Internet of Things Reporting 190

CIO Business Intelligence

NOVEMBER 18, 2024

Although measuring Unit Economics across organisations is challenging due to various limitations and assumptions, we can further explore its role in both digital-native and traditional businesses. Building the model is an iterative process that needs to involve the business.

Measurement 111

Measurement Modeling Forecasting Metrics 111

CIO Business Intelligence

FEBRUARY 20, 2025

In addition, they can use statistical methods, algorithms and machine learning to more easily establish correlations and patterns, and thus make predictions about future developments and scenarios. Companies should then monitor the measures and adjust them as necessary.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

CIO Business Intelligence

APRIL 8, 2025

Data quality must be embedded into how data is structured, governed, measured and operationalized. Implementing Service Level Agreements (SLAs) for data quality and availability sets measurable standards, promoting responsibility and trust in data assets. Continuous measurement of data quality. Accountability and embedded SLAs.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

DECEMBER 5, 2024

This type of structure is foundational at REA for building microservices and timely data processing for real-time and batch use cases like time-sensitive outbound messaging, personalization, and machine learning (ML). These metrics help us determine the attributes of the cluster usage effectively.

Metrics 79

Metrics Dashboards Testing Optimization 79

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. blueberry spacing) is a measure of the model’s interpretability. Machine Learning Model Lineage. Machine Learning Model Visibility . Figure 04: Applied Machine Learning Prototypes (AMPs).

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 1 for data analytics trends in 2020.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

AWS Big Data

DECEMBER 7, 2023

In this post, we outline planning a POC to measure media effectiveness in a paid advertising campaign. We chose to start this series with media measurement because “Results & Measurement” was the top ranked use case for data collaboration by customers in a recent survey the AWS Clean Rooms team conducted. and CTV.Co

Measurement 106

Measurement Advertising Testing Data-driven 106

datapine

SEPTEMBER 6, 2022

That said, measuring the success of your those efforts is another great part of the job, and on many occasions, it can prove to be overwhelming as you need to use multiple tools to gather the data. A content dashboard is an analytical tool that contains critical performance metrics to assess the success of all content-related initiatives.

Dashboards 179

Dashboards Reporting ROI Metrics 179

AWS Big Data

DECEMBER 18, 2024

The service also provides multiple query languages, including SQL and Piped Processing Language (PPL) , along with customizable relevance tuning and machine learning (ML) integration for improved result ranking. The similarity between query and documents is measured by their relative distances, despite being encoded separately.

Metrics 76

Metrics Modeling Data Processing Machine Learning 76

CIO Business Intelligence

OCTOBER 19, 2023

With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. You can also use Power BI to prepare and manage high-quality data to use across the business in other tools, from low-code apps to machine learning.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

datapine

DECEMBER 11, 2019

Within business scenarios, artificial intelligence (as well as machine learning, in many cases) provides an advanced degree of responsiveness and interaction between businesses, customers, and technology, driving AI-based SaaS trends 2020 onto a new level. How will AI improve SaaS in 2020? 2) Vertical SaaS.

Software 314

Software Cost-Benefit Data-driven Data Processing 314

datapine

JANUARY 21, 2020

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Artificial intelligence and machine-learning algorithms used in those kinds of tools can foresee future values, identify patterns and trends, and automate data alerts. It doesn’t stop here.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

DataKitchen

OCTOBER 28, 2021

Machine learning (ML) models are computer programs that draw inferences from data — usually lots of data. As the industry’s understanding of AI bias matures, model developers are getting better at defining and measuring bias. Data teams should formulate equity metrics in partnership with stakeholders. What Is AI Bias?

Testing 130

Testing IT Manufacturing Machine Learning 130

IBM Big Data Hub

JUNE 10, 2024

SLAs describe the level of performance to be expected, how performance will be measured and repercussions if levels are not met. Crucially, they define how performance will be measured. SLAs should precisely define the key metrics—service-level agreement metrics—that will be used to measure service performance.

Metrics 58

Metrics Key Performance Indicator Measurement Cost-Benefit 58