Rocket-Powered Data Science

MARCH 19, 2021

Focus on specific data types: e.g., time series, video, audio, images, streaming text (such as social media or online chat channels), network logs, supply chain tracking (e.g., Dynamic sense-making, insights discovery, next-best-action response, and value creation is essential when data is being acquired at an enormous rate.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

Occam's Razor

AUGUST 13, 2012

Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. What's possible to measure. What's not possible to measure. Let's do this!

Modeling 125

Modeling Metrics Data Quality Data-driven 125

O'Reilly on Data

JANUARY 28, 2019

The problems with consent to data collection are much deeper. It comes from medicine and the social sciences, in which consenting to data collection and to being a research subject has a substantial history. We really don't know how that data is used, or might be used, or could be used in the future.

Insurance 242

Insurance Metadata Data Collection Marketing 242

datapine

JANUARY 6, 2022

Yet, before any serious data interpretation inquiry can begin, it should be understood that visual presentations of data findings are irrelevant unless a sound decision is made regarding scales of measurement. For a more in-depth review of scales of measurement, read our article on data analysis questions.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

AUGUST 9, 2024

Privacy protection The first step in AI and gen AI projects is always to get the right data. “In In cases where privacy is essential, we try to anonymize as much as possible and then move on to training the model,” says University of Florence technologist Vincenzo Laveglia. “A A balance between privacy and utility is needed.

Risk 138

Risk Measurement Data Lake Data Collection 138

IBM Big Data Hub

SEPTEMBER 7, 2023

Today we are announcing our latest addition: a new family of IBM-built foundation models which will be available in watsonx.ai , our studio for generative AI, foundation models and machine learning. Collectively named “Granite,” these multi-size foundation models apply generative AI to both language and code.

Modeling 101

Modeling Risk Unstructured Data Enterprise 101

Smart Data Collective

SEPTEMBER 14, 2022

To get the range data from this technology, you will start by projecting a laser beam at a surface or an object. Then, measure the time it takes for the reflected beam of light to reach the receiver. Due to the high accuracy that Lidar data are known for, many people adopt them for various applications.

Data-driven 141

Data-driven Big Data Cost-Benefit Data Collection 141

Smart Data Collective

MARCH 24, 2020

In the article, you will find a number of areas where Big Data in education can be applied. The relationship between performance parameters and factors for predicting performance is involved in complex nonlinear relationships, so the areas of data collection should be comprehensive. Data collection. To Begin with….

Big Data 120

Big Data Internet Publishing and Broadcasting Broadcasting Data Collection 120

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167

Analytics Machine Learning Data Science Data Collection 167

CIO Business Intelligence

MARCH 19, 2025

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

IT 59

IT Data Governance Data-driven Metrics 59

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

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. See [link]. Industry 4.0 2) Connected cars. (3)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

DataRobot

AUGUST 25, 2021

In a recent blog, we talked about how, at DataRobot , we organize trust in an AI system into three main categories: trust in the performance in your AI/machine learning model , trust in the operations of your AI system, and trust in the ethics of your modelling workflow, both to design the AI system and to integrate it with your business process.

Metrics 98

Metrics Measurement Machine Learning Data Collection 98

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

Occam's Razor

JULY 18, 2011

The only requirement is that your mental model (and indeed, company culture) should be solidly rooted in permission marketing. You just have to have the right mental model (see Seth Godin above) and you have to… wait for it… wait for it… measure everything you do! Just to ensure you are executing against your right mental model.

Metrics 138

Metrics Marketing Measurement Cost-Benefit 138

Data Science and Beyond

NOVEMBER 22, 2015

Contrary to common belief, the hardest part of data science isn’t building an accurate model or obtaining good, clean data. It is much harder to define feasible problems and come up with reasonable ways of measuring solutions. This post discusses some examples of these issues and how they can be addressed.

Data Science 92

Data Science Data Collection Measurement Modeling 92

datapine

MAY 2, 2023

The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries. According to studies, 92% of data leaders say their businesses saw measurable value from their data and analytics investments.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

Smart Data Collective

MAY 29, 2023

Overcoming representation bias necessitates comprehensive data collection efforts that cover a wide range of languages and dialects, ensuring equal representation and inclusivity. Labeling Bias: Impact on Model Performance The presence of labeling bias in AI translation systems will significantly impact the model’s performance.

Metrics 96

Metrics Measurement Data Collection Strategy 96

Smart Data Collective

DECEMBER 17, 2021

The process of Marketing Analytics consists of data collection, data analysis, and action plan development. Understanding your marketing data to make more informed and successful marketing strategy decisions is a systematic process. Types of Data Used in Marketing Analytics. Preparing the Data for Analysis.

Marketing Analytics 122

Marketing Analytics Marketing Data-driven Analytics 122

O'Reilly on Data

JULY 20, 2021

When we’re building shared devices with a user model, that model quickly runs into limitations. That model doesn’t fit reality: the identity of a communal device isn’t a single person, but everyone who can interact with it. This measurement of trust and risk is benefited by understanding who could be in front of the device.

Risk 331

Risk Software Interactive Modeling 331

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

DataKitchen

JUNE 24, 2021

Chapin also mentioned that measuring cycle time and benchmarking metrics upfront was absolutely critical. “It It struck me that DataOps has the potential to be a transformative capability, and not just from a technology perspective, but from the lens it brings to how we approach these complex data environments.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

CIO Business Intelligence

AUGUST 19, 2024

The company’s mission is to provide farmers with real-time insights derived from plant data, enabling them to optimize water usage, improve crop yields, and adapt to changing climatic conditions. This system uses large language models (LLMs) to combine a vast library of agricultural data with expert knowledge.

IoT 126

IoT Data-driven Data Enablement Optimization 126

datapine

SEPTEMBER 1, 2020

An effective modern means of extracting real value from your research results such as brand analysis, market research reports present and arrange data in a way that is digestible and logical in equal measures through professional online reporting software and tools. c) Customer Effort Score (CES). b) Purchase Intention.

Reporting 247

Reporting Marketing KPI Dashboards 247

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. The Active Data Ratio metric determines the percentage of datasets that deliver value.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

CIO Business Intelligence

OCTOBER 2, 2024

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. But some IT leaders are getting it right because they focus on three key aspects.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

Smart Data Collective

OCTOBER 8, 2023

The Power of Data Analytics: An Overview Data analytics, in its simplest form, is the process of inspecting, cleansing, transforming, and modeling data to unearth useful information, draw conclusions, and support decision-making. This involves data collection , data cleaning, data analysis, and data interpretation.

Data Analytics 125

Data Analytics Analytics Statistics Data Collection 125

Occam's Razor

JANUARY 7, 2014

The organization functions off a clearly defined Digital Marketing & Measurement Model. #1. Remember none of these jobs will do any data collection/IT work, even in medium-sized companies.) More on the Digital Marketing & Measurement Model, DMMM, in #2 below.). Most companies hire a Web Analyst, Sr.

Data-driven 142

Data-driven Consulting Reporting Marketing 142

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. All this data is then used to set pricing fees, meet demand, and ensure an excellent service for both their drivers and clients.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Cloudera

MAY 9, 2019

The number one challenge that enterprises struggle with their IoT implementation is not being able to measure if they are successful or not with it. The report created a readiness model with five dimensions and various metrics under each dimension. The five dimensions of the readiness model are –.

IoT 56

IoT Modeling Metrics Measurement 56

Rocket-Powered Data Science

JULY 21, 2023

Organizations are able to monitor integrity, quality drift, performance trends, real-time demand, SLA (service level agreement) compliance metrics, and anomalous behaviors (in devices, applications, and networks) to provide timely alerting, early warnings, and other confidence measures.

Machine Learning 190

Machine Learning Metrics Reporting Internet of Things 190

CIO Business Intelligence

APRIL 14, 2022

The ability to provide transparent, data-driven insights and measure progress toward ESG commitments makes the technology leader critical to the success of any ESG strategy. Smarter operations through integrated data and analytics. For example, a client in the oil and gas sector recently equipped their U.S.

Strategy 111

Strategy Digital Transformation IoT Measurement 111

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

By PATRICK RILEY For a number of years, I led the data science team for Google Search logs. We were often asked to make sense of confusing results, measure new phenomena from logged behavior, validate analyses done by others, and interpret metrics of user behavior. Then, check to see if these multiple measurements are consistent.

Metrics 107

Metrics Measurement Statistics Data Collection 107

Smart Data Collective

MARCH 23, 2022

After all, when you personalize your services with your customers, they’ll feel valued and help you gather the correct data. Use the 5Ps model (People, Product, Promotion, Price, Place). The 5Ps model is a popular model that isn’t only used for marketing purposes and data mining.

Data mining 133

Data mining Marketing Data Collection Insurance 133

CIO Business Intelligence

SEPTEMBER 18, 2024

Transparency — explain and justify the entire process of model development. Security — ensure that models do not produce unintended outcomes. CIOs, as well as CTOs, should advocate for measuring how humane their AI-powered services are because, typically, we’re more prone to improving what we decided to measure, Jain adds.

Interactive 128

Interactive Cost-Benefit Measurement Testing 128

Occam's Razor

MAY 19, 2014

Why not just measure Profit?" " That is right, we will measure it. Where I've implemented a simple where you able to complete your task qualitative data collection mechanism, I always pair Conversion Rate with Task Completion Rate. It should be immediately adjacent. Two simple reasons. Likes – ?

Metrics 160

Metrics Key Performance Indicator Analytics Marketing 160