O'Reilly on Data

NOVEMBER 13, 2018

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. As we deploy ML in many real-world contexts, optimizing statistical or business metics alone will not suffice. Classification parity means that one or more of the standard performance measures (e.g.,

Machine Learning 220

Machine Learning Risk Management Statistics 220

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. Alex Ratner on “Creating large training data sets quickly”.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

AWS Big Data

MAY 16, 2023

In this series of posts, we walk you through how we use Amazon QuickSight , a serverless, fully managed, business intelligence (BI) service that enables data-driven decision making at scale. Solution overview The following highly simplified architectural diagram illustrates the smart sensor data collection and processing.

Dashboards 78

Dashboards Statistics Data Collection Business Intelligence 78

FineReport

JUNE 29, 2023

The Internet of Things (IoT) has revolutionized the way we interact with devices and gather data. Advanced levels of IoT analytics dashboards facilitate the identification of statistical trends, enabling the use of data for predictive failure analysis and extracting precise information and correlations from datasets.

IoT 52

IoT Dashboards Visualization Cost-Benefit 52

Sisense

SEPTEMBER 3, 2020

Data scientists usually build models for data-driven decisions asking challenging questions that only complex calculations can try to answer and creating new solutions where necessary. Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

IBM Big Data Hub

AUGUST 7, 2023

AI algorithms have the potential to surpass traditional statistical approaches for analyzing comprehensive recruitment data and accurately forecasting enrollment rates. A mitigation plan facilitates trial continuity by providing contingency measures and alternative strategies.

Optimization 62

Optimization Forecasting Data-driven Strategy 62

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 156

Metrics KPI Analytics Key Performance Indicator 156

Sisense

OCTOBER 15, 2020

Every data professional knows that ensuring data quality is vital to producing usable query results. Streaming data can be extra challenging in this regard, as it tends to be “dirty,” with new fields that are added without warning and frequent mistakes in the data collection process.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book? Instead, I built the AIgent. features) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

Alation

OCTOBER 12, 2022

Companies collect and analyze vast amounts of data to make informed business decisions. From product development to customer satisfaction, nearly every aspect of a business uses data and analytics to measure success and define strategies. Some examples of quantitative data include: Counts or units, stored as raw numbers.

Statistics 52

Statistics Sales Testing Marketing 52

Domino Data Lab

AUGUST 12, 2021

In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase. We covered the importance of Exploratory Analytics including observing the frequency of missing data and computing interactions of all features. Pandas Profiler.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

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. Bonus: Interactive CD. Immediately actionable web analytics (your biggest worries covered). In 480 pages the book goes from from beginner's basics to a advanced analytics concepts.

Analytics 60

Analytics Metrics Marketing Dashboards 60

datapine

APRIL 11, 2019

Download our 10-step checklist and see how to tell the best data story. Rather than listing facts, figures, and statistics alone, people used gripping, imaginative timelines, bestowing raw data with real context and interpretation. Create an interactive dialogue. No one likes being told what to do.

Dashboards 169

Dashboards Visualization Data-driven Key Performance Indicator 169

FineReport

JUNE 26, 2023

These reports commonly incorporate graphical elements such as charts, graphs, tables, and statistics, which complement the text-based information and offer visual representation. Status Reports These reports provide the current state of a project at a specific moment, detailing its alignment with the performance measurement baseline.

Reporting 52

Reporting Key Performance Indicator Sales Visualization 52

datapine

JUNE 4, 2020

A CTO report is based on a curated collection of data and statistics that exist within the dashboard and offer a wealth of information based on established KPIs that can be easily automated and shared across the board, in order to monitor relevant IT performance. Besides, these dashboards can also be used as CTO reports.

Dashboards 130

Dashboards Reporting Metrics Visualization 130

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. measure the subjects’ ability to trust the models’ results. training data”) show the tangible outcomes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. In the real world, things are never this easy, and it is a battle to get the data into the correct shape as we will see later in this chapter. shows the output in Jupyter Notebook of the describe command.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 20, 2019

Real-world datasets can be missing values due to the difficulty of collecting complete datasets and because of errors in the data collection process. Drop a column from a table—either based on a principled argument (we know the two columns are measuring the same thing) or based on a randomness. Filling missing values.

Testing 68

Testing Modeling Interactive Measurement 68

Jet Global

MAY 15, 2020

A financial Key Performance Indicator (KPI) or metric is a quantifiable measure that a company uses to gauge its financial performance over time. Under modern day reporting standards, companies are formally obligated to present their financial data in the following statements: balance sheet, income statement, and cash flow statement.

Metrics 98

Metrics Finance Reporting KPI 98

O'Reilly on Data

OCTOBER 18, 2022

Audits are usually more official, tracking adherence to some policy, regulation, or law, and tend to be conducted by independent third parties with varying degrees of limited interaction between auditor and auditee organizations. Data labeling is a problem. Assessments tend to be more informal and cooperative.

Risk Management 291

Risk Management Risk Testing Measurement 291

Domino Data Lab

JUNE 23, 2019

This talk will describe how you can navigate all these challenges that you’re going to face and build a business where every product interaction benefits from your investment in machine learning. These measurement-obsessed companies have an advantage when it comes to AI. All of these people need to get together to make this work.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. Usually for free.

Analytics 118

Analytics Consulting Metrics Experimentation 118

datapine

APRIL 16, 2019

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. What Is Data Driven Decision Making? Quantitative data analysis focuses on numbers and statistics.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Let’s just give our customers access to the data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

O'Reilly on Data

JUNE 16, 2020

We know, statistically, that doubling down on an 11 is a good (and common) strategy in blackjack. One way to correct for this bias in the data is to look at the statistics of “excess deaths,” the numbers when compared with previous years. Mike: But I lost! How can you say always ?!? The decision-making process was fine.

Uncertainty 275

Uncertainty Testing Risk Reporting 275