AWS Big Data

SEPTEMBER 5, 2024

It comes in two modes: document-only and bi-encoder. For more details about these two terms, see Improving document retrieval with sparse semantic encoders. Simply put, in document-only mode, term expansion is performed only during document ingestion. We care more about the recall metric.

Metrics 111

Metrics Testing Experimentation Modeling 111

CIO Business Intelligence

MAY 1, 2024

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times. Now nearly half of code suggestions are accepted.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

CIO Business Intelligence

AUGUST 15, 2024

A virtual assistant may save employees time when searching for old documents or composing emails, but most organizations have no idea how much time those tasks have taken historically, having never tracked such metrics before, she says.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

DataRobot Blog

JANUARY 10, 2023

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. This flexibility allows you to import your local code into the DataRobot platform and continue further experimentation using the combination of DataRobot Notebooks with: Deep integrations with DataRobot comprehensive APIs.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

AWS Big Data

JUNE 11, 2024

Each index shard may occupy different sizes based on its number of documents. In addition to the number of documents, one of the important factors that determine the size of the index shard is the compression strategy used for an index. As part of an indexing operation, the ingested documents are stored as immutable segments.

Optimization 94

Optimization Experimentation Cost-Benefit Software 94

AWS Big Data

AUGUST 21, 2023

Lexical search looks for words in the documents that appear in the queries. Background A search engine is a special kind of database, allowing you to store documents and data and then run queries to retrieve the most relevant ones. OpenSearch Service supports a variety of search and relevance ranking techniques.

Data Processing 98

Data Processing Visualization Experimentation Metrics 98

DataRobot Blog

MARCH 16, 2023

This means they need the tools that can help with testing and documenting the model, automation across the entire pipeline and they need to be able to seamlessly integrate the model into business critical applications or workflows. Assured Compliance and Governance – DataRobot has always been strong on ensuring governance.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

CIO Business Intelligence

NOVEMBER 21, 2023

Equally important is communicating with stakeholders how to onboard technology requests, sharing how departmental technology needs are prioritized, documenting stakeholder responsibilities when seeking new technologies, and providing the status of active programs.

IT 137

IT Risk Cost-Benefit Data Science 137

CIO Business Intelligence

APRIL 2, 2024

Joanne Friedman, PhD, CEO, and principal of smart manufacturing at Connektedminds, says orchestrating success in digital transformation requires a symphony of integration across disciplines : “CIOs face the challenge of harmonizing diverse disciplines like design thinking, product management, agile methodologies, and data science experimentation.

Management 140

Management Digital Transformation Testing Experimentation 140

AWS Big Data

JANUARY 9, 2024

Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

Visualization 119

Visualization Cost-Benefit Modeling Machine Learning 119

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. Today, top AI-assistant capabilities delivering results include generating code, test cases, and documentation.

Advertising 124

Advertising Cost-Benefit Experimentation Reporting 124

CIO Business Intelligence

AUGUST 21, 2024

Our goal is to analyze logs and metrics, connecting them with the source code to gain insights into code fixes, vulnerabilities, performance issues, and security concerns,” he says. Then there’s the risk of malicious code injections, where the code is hidden inside documents read by an AI agent, and the AI then executes the code.

Risk 136

Risk Insurance Cost-Benefit Software 136

AWS Big Data

MAY 2, 2023

If your updates to a dataset triggers multiple subsequent DAGs, then you can use the Airflow metric max_active_tasks_per_dag to control the parallelism of the consumer DAG and reduce the chance of overloading the system. Removal of experimental Smart Sensors. Let’s demonstrate this with a code example. Apache Airflow v2.4.3

Testing 130

Testing Experimentation Management Metadata 130

Cloudera

OCTOBER 8, 2024

By 2023, the focus shifted towards experimentation. Detailed Data and Model Lineage Tracking*: Ensures comprehensive tracking and documentation of data transformations and model lifecycle events, enhancing reproducibility and auditability. These innovations pushed the boundaries of what generative AI could achieve.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

Domino Data Lab

AUGUST 22, 2019

Common natural language preprocessing options include: Tokenization: This is the splitting of a document (e.g., Execute gutenberg.fileids() to print the names of all 18 documents.) As we wrap up the section later on, we’ll apply the steps across the entire 18-document corpus. words), which we call tokens. 0.85 = 0.15.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

DataRobot Blog

MARCH 7, 2023

DataRobot on Azure accelerates the machine learning lifecycle with advanced capabilities for rapid experimentation across new data sources and multiple problem types. With built-in guardrails and automated model documentation for compliance, have the confidence you need to make business decisions quickly.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

Occam's Razor

DECEMBER 9, 2009

They also tend to generate inefficiencies (everyone's doing their own thing after all) be it with tools or work or metrics definitions or testing platforms or… Decentralized organizations optimize for a local maxima and it happens all the time that while individual divisions in a company win, that the company as a whole loses.

Analytics 95

Analytics Data-driven Marketing Sales 95

DataRobot

JUNE 23, 2021

After adding the preferred code, teams can take advantage of the existing DataRobot capabilities, such as metrics, explainability, visualizations, deployment, monitoring, collaboration, and governance. In data science , the best results come through experimentation. So let’s dig in!

Machine Learning 52

Machine Learning Visualization Experimentation Modeling 52

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). In 480 pages the book goes from from beginner's basics to a advanced analytics concepts. Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

DataRobot Blog

SEPTEMBER 30, 2022

By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Adoption of AI/ML is maturing from experimentation to deployment. How do you track the integrity of a machine learning model in production? Model Observability can help.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

Domino Data Lab

DECEMBER 4, 2020

Having calculated AUC/AUMC, we can further derive a number of useful metrics like: Total clearance of the drug from plasma. Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). 2] Pumas AI Documentation, [link]. [3] Mean residence time.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Domino Data Lab

AUGUST 6, 2021

Develop: includes accessing and preparing data and algorithms, researching and development of models and experimentation. Monitor: includes monitoring the performance of the model, tracking metrics, as well as driving adoption of the model by those it was intended to serve.

Data Science 75

Data Science Testing Modeling Publishing 75

AWS Big Data

JULY 26, 2023

The vector engine supports the popular distance metrics such as Euclidean, cosine similarity, and dot product, and can accommodate 16,000 dimensions, making it well-suited to support a wide range of foundational and other AI/ML models. To create the vector index, you must define the vector field name, dimensions, and the distance metric.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 364

Marketing Experimentation Metrics Testing 364

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. We use performance metrics such as bias and mean squared error for the estimation of $delta$, our causal estimand of interest, defined as the average effect of treatment on the treated.

Statistics 45

Statistics Optimization Modeling Experimentation 45

CIO Business Intelligence

AUGUST 5, 2024

Some important steps that need to be taken to monitor and address these issues include specific communication and documentation regarding GenAI usage parameters, real-time input and output logging, and consistent evaluation against performance metrics and benchmarks. To learn more, visit us here.

Experimentation 124

Experimentation Risk Metadata Data-driven 124

Occam's Razor

AUGUST 22, 2011

" ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. "Engagement" Is Not A Metric, It's An Excuse. Convert Data Skeptics: Document, Educate & Pick Your Poison. Defining a "Master Metric", + a Framework to Gain a Competitive Advantage in Web Analytics.

KPI 125

KPI Metrics Measurement ROI 125

CIO Business Intelligence

MAY 20, 2024

The study documents “substantial returns to face-to-face meetings … (and) returns to serendipity.” Nonetheless, ample anecdotal evidence documents that serendipity plays a major role in creating new knowledge, novel products, and unexpected combinations. Instead, companies should use metrics other than budget targets for rewards.

Management 122

Management Interactive Measurement Marketing 122

Corinium

APRIL 25, 2019

Life insurance needs accurate data on consumer health, age and other metrics of risk. Whether eventual legislation will exactly mirror GDPR remains to be seen, I think there will be some experimentation at the State level as well as for specific verticals whose successes would point the way.

Insurance 150

Insurance Risk IoT Data-driven 150

Domino Data Lab

AUGUST 26, 2019

To support the iterative and experimental nature of industry work, Domino reached out to Addison-Wesley Professional (AWP) for appropriate permissions to excerpt the “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. algorithm leaf_size metric metric_params n_jobs n_neighbors p weights.

Testing 79

Testing Modeling Machine Learning Metrics 79

Insight

MARCH 12, 2020

To collect these genre tags and other metadata, I took advantage of the well-documented Goodreads API. After some experimentation, I landed on a strategy I’ll call ‘warm encoding’: if greater than 1% of tags were in a particular class, I encoded the book as belonging to that class, non-exclusively. In other words, if 0.1%

Modeling 59

Modeling Metadata Publishing Sales 59

CIO Business Intelligence

OCTOBER 10, 2024

For example, a retrieval-augmented generation (RAG) AI document search project can cost up to $1 million to deploy, with recurring per-user costs of up to $11,000 a year, according to Gartner. Still, a 30% failure rate represents a huge amount of time and money, given how widespread AI experimentation is today.

ROI 135

ROI Experimentation Cost-Benefit Metrics 135

CIO Business Intelligence

FEBRUARY 5, 2025

By focusing on domains where data quality is sufficient and success metrics are clear such as increased conversion rates, reduced downtime, or improved operational efficiency companies can more easily quantify the value AI brings. Break the project into manageable, experimental phases to learn and adapt quickly.

Cost-Benefit 117

Cost-Benefit ROI Metrics Measurement 117

CIO Business Intelligence

FEBRUARY 27, 2025

Traditional PMOs must move beyond rigid timelines and delivery metrics to enable continuous value delivery, where contextual intelligence flows across the stack to inform real-time decision-making. PMOs should abandon traditional approaches emphasizing lengthy planning and documentation, says Ori Yudilevich, CPO of MaterialsZone.

IT 126

IT Digital Transformation Metrics Data-driven 126

CIO Business Intelligence

FEBRUARY 17, 2025

Research from IBM indicates that only 15% of global businesses have established themselves as leaders in AI implementation, while the majority remain in early experimental phases. For instance, using AI to automate document preparation can cut processing time from hours to minutes. First, set clear objectives and success metrics.

Experimentation 78

Experimentation Metrics Strategy Manufacturing 78

O'Reilly on Data

APRIL 15, 2025

One client proudly showed me this evaluation dashboard: The kind of dashboard that foreshadows failure This is the tools trapthe belief that adopting the right tools or frameworks (in this case, generic metrics) will solve your AI problems. Second, too many metrics fragment your attention. When everything is important, nothing is.

Experimentation 328

Experimentation Testing Metrics Measurement 328

CIO Business Intelligence

MAY 6, 2025

Governance challenges I commonly see: No consistent data definitions between departments No agreed-upon owner for key metrics like revenue or customer lifetime value Shadow IT spinning up their datasets and dashboards These gaps create delays, misalignment and risk. These capabilities are no longer theoretical or experimental.

Prescriptive Analytics 69

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 69