CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 115

Modeling Cost-Benefit IT ROI 115

DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. These errors might seem small, but the effects can be disastrous when the model is used to make decisions in the real world.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 198

Machine Learning Modeling Testing Risk Management 198

O'Reilly on Data

APRIL 2, 2019

A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects. We are still in the early days for tools supporting teams developing machine learning models. Model governance.

Machine Learning 207

Machine Learning Modeling Data Science Software 207

O'Reilly on Data

OCTOBER 13, 2020

Our previous articles in this series introduce our own take on AI product management , discuss the skills that AI product managers need , and detail how to bring an AI product to market. In Bringing an AI Product to Market , we distinguished the debugging phase of product development from pre-deployment evaluation and testing.

Management 253

Management Metrics Machine Learning Modeling 253

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MAY 14, 2020

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products.

Management 363

Management Experimentation B2B Machine Learning 363

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Jet Global

NOVEMBER 2, 2021

KPIs are a select few metrics that provide insight on the operation of all entities contributing to the supply chain. Metrics help supply chain management track its progress in achieving its goals and respond quickly if needed. Measurable: Is your metric quantifiable? That’s where KPI monitoring comes into play.

Metrics 52

Metrics Reporting KPI Key Performance Indicator 52

Domino Data Lab

JULY 1, 2021

In this blog post we present the Named Entity Recognition problem and show how a BiLSTM-CRF model can be fitted using a freely available annotated corpus and Keras. The model achieves relatively high accuracy and all data and code is freely available in the article. The CRF model. What is Named Entity Recognition?

Modeling 111

Modeling Statistics Testing Metrics 111

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration.

Modeling 122

Modeling IT Metrics Testing 122

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 Reporting Internet of Things 190

CIO Business Intelligence

APRIL 25, 2024

During the summer of 2023, at the height of the first wave of interest in generative AI, LinkedIn began to wonder whether matching candidates with employers and making feeds more useful would be better served with the help of large language models (LLMs).

IT 133

IT Experimentation Cost-Benefit Metrics 133

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Juice Analytics

APRIL 7, 2023

It can compress a long article down to the CliffsNotes version in an instant. I found ChatGPT was exceptional at identifying the meaning of the individual rows in my tests. For each data field, identify if it is a metric, dimension, boolean, or date. Finding similar concepts is another Large Language Model strength.

Metrics 97

Metrics Testing Modeling IT 97

DataKitchen

OCTOBER 2, 2023

This comprehensive article delves into the complexities encountered by various types of data teams—Data Ingestion Teams, End-to-End Data Product Teams, and Enterprise Data Enablement Teams—to name a few. Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

CIO Business Intelligence

JUNE 11, 2024

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications. What comes first: A new brand or operating model?

IT 108

IT Digital Transformation Broadcasting Business Objectives 108

datapine

OCTOBER 21, 2020

In this article, we’re going to address the need for big data in healthcare and hospital big data: why and how can it help? Now that we live longer, treatment models have changed and many of these changes are namely driven by data. and could provide a model for the EU to follow. What are the obstacles to its adoption?

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

datapine

FEBRUARY 4, 2020

Below, in the article, we’ve gathered some of the marketing reports templates that can easily be used to perfect the efficiency of generating data and reduce the time needed to create it. Structure your metrics. That way you can choose the best possible metrics for your case. Use professional software. 1) Marketing CMO report.

Reporting 280

Reporting Marketing Advertising Metrics 280

Cloudera

AUGUST 17, 2020

One of the primary sources of that knowledge comes from our Knowledge Articles. These Knowledge Articles have proven to be invaluable to our Support Staff over the years. To that end, we have been working on improving the way our customers discover the collection of knowledge available in our Knowledge Articles. Set Pieces.

Testing 88

Testing Machine Learning Interactive Metrics 88

The Unofficial Google Data Science Blog

JANUARY 16, 2018

by SANGHO YOON In this article, we discuss an approach to the design of experiments in a network. We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. At Google, A/B testing plays a key role in better understanding our users and products. Assume we have $K$ users.

Testing 58

Testing Experimentation Measurement Modeling 58

Occam's Razor

FEBRUARY 9, 2015

. + Traffic Trends Key Metrics Analysis. Onsite Behavior Key Metrics Analysis. I tend to use Hitwise a lot less, or not at all, because it is a very hard to use, it is slow, the UX/UI, metrics and reports have not really evolved over the years. Traffic Trends Key Metrics Analysis. Visitor/Audience Type Profile Analysis.

Metrics 155

Metrics Reporting IT Advertising 155

datapine

MAY 17, 2021

Without a doubt, the best way to drive maximum value from the metrics, insights, and information is through something called data discovery. What is a discovery model, and how do you use it in a real-world business context? Your Chance: Want to test a professional data discovery tool for free? What is a data discovery platform?

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

datapine

APRIL 15, 2020

That said, in this article, we will go through both agile analytics and BI starting from basic definitions, and continuing with methodologies, tips, and tricks to help you implement these processes and give you a clear overview of how to use them. Your Chance: Want to test an agile business intelligence solution? Finalize testing.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage. GPT – Is based on a Large Language Model (LLM).

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Cloudera

DECEMBER 3, 2021

For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Even something as simple as choosing a loss function can change the bias of a trained model. Model Drift. Regulation.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

datapine

JUNE 18, 2019

We will explore even more examples of monthly reports later in the article. We live in a data-driven age, and the ability to use financial insights and metrics to your advantage will set you apart from the pack. Work Quality: These metrics help companies determine the quality level of their employees’ work performance.

Reporting 251

Reporting Metrics KPI Finance 251

Cloudera

MARCH 22, 2023

While in the old world where questions around data quality or system performance were answered by monitoring a few logs and metrics, in a distributed landscape (like a hybrid data platform) it’s not that straightforward. There are many logs and metrics, and they are all over the place.

Metrics 88

Metrics Data Governance Cost-Benefit Dashboards 88

Ontotext

MARCH 7, 2024

Wikidata entities are connected to Wikipedia articles, where such exist (Wikipedia has about 7 million articles). We have experimented with different models that enable linking to Wikidata. The required MEL model for this task should be capable of performing end-to-end entity linking. IXA+MGENRE 0.79 English (en) BELA 0.72

Modeling 59

Modeling Metrics Business Intelligence Testing 59

Juice Analytics

JANUARY 18, 2022

Like a news article, it provides an update that focuses on highlights and insights. This commonly-used structure for new articles prioritizes the overall message first, then provides additional content details to back it up. We’ve outlined five areas to focus on and where to go for inspiration. (1) Otherwise, what’s the point?

Reporting 88

Reporting Metrics Dashboards Testing 88

Smarten

JUNE 29, 2018

This article discusses the Paired Sample T Test method of hypothesis testing and analysis. What is the Paired Sample T Test? The Paired Sample T Test is used to determine whether the mean of a dependent variable e.g., weight, anxiety level, salary, reaction time, etc., is the same in two related groups.

Business Analysis 40

Business Analysis Testing Statistics Advertising 40

DataRobot

NOVEMBER 29, 2021

This article will discuss the technologies DataRobot uses to help ensure trust in the AI systems built on our platform. We’ll focus on evaluating a model for biased behavior, which can occur during the training process or after it has been deployed in a production environment. .

Technology 52

Technology Metrics Predictive Modeling Modeling 52

Cloudera

NOVEMBER 17, 2021

Every AMP includes all the dependencies, industry best practices, prebuilt models, and a business-ready AI application — All deployable with a couple clicks, allowing Data Science teams to start a new project with a working example that they can then customize to their own needs in a fraction of the time.

Machine Learning 124

Machine Learning Visualization Data Science Metrics 124

Smarten

DECEMBER 3, 2023

This article will help you gather information about the topic of augmented analytics. It also augments the expert and citizen data scientists by automating many aspects of data science, machine learning, and AI model development, management and deployment.’ ‘You Maybe you just want to understand the analytics solution market better.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

CIO Business Intelligence

FEBRUARY 29, 2024

You’d be forgiven if you’re wondering whether you’ve stumbled on an article from 2016 , but, in fact, the practice of launching an offshore IT center wholly owned and operated by the enterprise it serves is back in vogue with notable twists. Captive centers are on the rise. Not all BOTs transfer in the end, notes Martorelli.

Cost-Benefit 105

Cost-Benefit Risk Modeling Strategy 105

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. Your Chance: Want to try a professional BI analytics software? Let’s look at our first use case.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. The most powerful approach for the first task is to use a ‘language model’ (LM), i.e. a statistical model of natural language.

Modeling 59

Modeling Metadata Publishing Sales 59