O'Reilly on Data

FEBRUARY 16, 2023

It might be easy to dismiss these stories as anecdotal at best, fraudulent at worst, but I’ve seen many reports from beta testers who managed to duplicate them. That’s what beta tests are for. Remember that these tools aren’t doing math, they’re just doing statistics on a huge body of text.

Testing 296

Testing Statistics Modeling Optimization 296

O'Reilly on Data

MARCH 24, 2020

For example, a pre-existing correlation pulled from an organization’s database should be tested in a new experiment and not assumed to imply causation [3] , instead of this commonly encountered pattern in tech: A large fraction of users that do X do Z. HoloClean performs this automatically in a principled, statistical manner.

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Below we will explain how to virtually eliminate data errors using DataOps automation and the simple building blocks of data and analytics testing and monitoring. . Tie tests to alerts.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Smart Data Collective

MAY 18, 2022

A high-quality testing platform easily integrates with all the data analytics and optimization solutions that QA teams use in their work and simplifies testing process, collects all reporting and analytics in one place, can significantly improve team productivity, and speeds up the release. Data reporting.

Testing 126

Testing Data Analytics Analytics Big Data 126

datapine

JANUARY 24, 2021

You’ll want to be mindful of the level of measurement for your different variables, as this will affect the statistical techniques you will be able to apply in your analysis. There are basically 4 types of scales: *Statistics Level Measurement Table*. 5) Which statistical analysis techniques do you want to apply? Who are they?

IT 317

IT Statistics KPI Data-driven 317

Depict Data Studio

JULY 13, 2021

— Thank you to Ann Emery, Depict Data Studio, and her Simple Spreadsheets class for inviting us to talk to them about the use of statistics in nonprofit program evaluation! But then we realized that much of the time, statistics just don’t have much of a role in nonprofit work. Why Nonprofits Shouldn’t Use Statistics.

Statistics 98

Statistics Testing Recreation/Entertainment Experimentation 98

CIO Business Intelligence

FEBRUARY 6, 2025

They can also automate report generation and interpret data nuances that traditional methods might miss. In life sciences, simple statistical software can analyze patient data. While this process is complex and data-intensive, it relies on structured data and established statistical methods. Theyre impressive, no doubt.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

datapine

SEPTEMBER 6, 2022

1) What Is Content Reporting? 3) Why Is Content Report Analysis Important? 5) Content Reporting Best Practices. Enter modern content reports. What Is Content Reporting? This is no longer the case, thanks to the introduction of modern reporting tools such as interactive dashboards. Table of Contents.

Dashboards 179

Dashboards Reporting Metrics ROI 179

CIO Business Intelligence

JANUARY 14, 2025

The 2024 Enterprise AI Readiness Radar report from Infosys , a digital services and consulting firm, found that only 2% of companies were fully prepared to implement AI at scale and that, despite the hype , AI is three to five years away from becoming a reality for most firms. As part of that, theyre asking tough questions about their plans.

Strategy 141

Strategy ROI Experimentation Risk 141

Smart Data Collective

SEPTEMBER 22, 2021

In this blog post, we discuss the key statistics and prevention measures that can help you better protect your business in 2021. Cyber fraud statistics and preventions that every internet business needs to know to prevent data breaches in 2021. Sure, the above tips stand the test of time for cyber security.

Statistics 133

Statistics Risk Measurement Software 133

datapine

NOVEMBER 27, 2019

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process. 3) Artificial Intelligence.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

CIO Business Intelligence

APRIL 9, 2025

Since the AI chatbots 2022 debut, CIOs at the nearly 4,000 US institutions of higher education have had their hands full charting strategy and practices for the use of generative AI among students and professors, according to research by the National Center for Education Statistics. Would you like to apply?

Interactive 108

Interactive Technology Statistics Consulting 108

Laminar Security

JUNE 8, 2023

We’ve gathered some interesting data security statistics to give you insight into industry trends, help you determine your own security posture (at least relative to peers), and offer data points to help you advocate for cloud-native data security in your own organization. A 2022 ISC report highlighted a cybersecurity workforce gap of 3.4

Statistics 82

Statistics Risk Reporting Unstructured Data 82

O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. Currency amounts reported in Taiwan dollars.

Machine Learning 276

Machine Learning Modeling Testing Risk Management 276

DataKitchen

OCTOBER 11, 2021

There are no automated tests , so errors frequently pass through the pipeline. The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. All the code, Talend job, and the BI report are version controlled using Git. Adding Tests to Reduce Stress.

Testing 152

Testing Metadata Dashboards Statistics 152

O'Reilly on Data

DECEMBER 12, 2023

I can also ask for a reading list about plagues in 16th century England, algorithms for testing prime numbers, or anything else. Yes, it happens to be the next word in Hamlet’s famous soliloquy; but the model wasn’t copying Hamlet, it just picked “or” out of the hundreds of thousands of words it could have chosen, on the basis of statistics.

Modeling 331

Modeling Sales Software Statistics 331

Occam's Razor

OCTOBER 4, 2010

Ask a famous blogger, a published author, a random twitterer or your mom how to succeed in web analytics, or how not to be a Reporting Squirrel. Part of it is the case that we don't often understand the difference between a business question and a report request. Then fulfill that need. It is a good answer. Take a deep breath.

Reporting 119

Reporting Metrics Sales Strategy 119

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. Quantitative data analysis focuses on numbers and statistics. This type of analysis is measured rather than observed.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

APRIL 12, 2024

Large banking firms are quietly testing AI tools under code names such as as Socrates that could one day make the need to hire thousands of college graduates at these firms obsolete, according to the report.

Experimentation 143

Experimentation Reporting Testing Statistics 143

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. Human resources must also contribute to transparent reporting requirements here. Subsequently, the reporting should be set up properly.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

FineReport

AUGUST 4, 2020

When selecting the reporting software , whether the reporting system will enable report developers to develop reports quickly would be the priority of the enterprise’s consideration. However, it’s common to ignore choosing the reports portal. And it is hard to customize the reporting systems.

Reporting 92

Reporting Sales Software Statistics 92

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. So, the only way for a data journey to truly observe what’s happening is to get his tools and pipelines to auto-report events. Data and tool tests.

Testing 130

Testing Statistics Measurement Dashboards 130

DataKitchen

JUNE 7, 2021

A burn-down chart, velocity chart, or tornado report can help your team understand its bottlenecks. A data arrival report enables you to track data suppliers and quickly spot delivery issues. Test Coverage and Inventory Reports show the degree of test coverage of the data analytics pipeline. Lower Error Rates.

Testing 130

Testing IT Data-driven Measurement 130

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. Business analytics also involves data mining, statistical analysis, predictive modeling, and the like, but is focused on driving better business decisions.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Occam's Razor

OCTOBER 31, 2011

In this case for my data it is not statistically significant (more on that later in this post), but there is no way you would know that (or not know that) just from the data in front of you. Statistical Significance is Your BFF. It does 1-tail and 2-tail tests and the even more beloved chi-square test. Download it.

Statistics 131

Statistics Testing Reporting Key Performance Indicator 131

Smart Data Collective

JUNE 10, 2022

The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. To work in this field, you will need strong programming and statistics skills and excellent knowledge of software engineering. Are you interested in a career in data science? Enterprise Architect.

Data Science 144

Data Science Machine Learning Statistics Business Intelligence 144

Domino Data Lab

OCTOBER 7, 2020

Statistical methods for analyzing this two-dimensional data exist. MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. Each property is discussed below with R code so the reader can test it themselves.

Statistics 145

Statistics Testing Predictive Modeling Big Data 145

datapine

JANUARY 6, 2022

More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Sources of model risk. Model monitoring.

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

datapine

FEBRUARY 9, 2024

4) How to Select Your KPIs 5) Avoid These KPI Mistakes 6) How To Choose A KPI Management Solution 7) KPI Management Examples Fact: 100% of statistics strategically placed at the top of blog posts are a direct result of people studying the dynamics of Key Performance Indicators, or KPIs. 3) What Are KPI Best Practices?

KPI 221

KPI Management Key Performance Indicator Measurement 221

Smart Data Collective

OCTOBER 8, 2021

For instance, you want to generate effective AUM, NAV, and share value reports to improve investor confidence as a manager. Modern machine learning and back-testing; how quant hedge funds use it. Similarly, hedge funds often use modern machine learning and back-testing to analyze their quant models. Machine learning tests.

Machine Learning 132

Machine Learning Testing Strategy Modeling 132

Perceptual Edge

APRIL 9, 2020

Statistics are playing a major role during the COVID-19 pandemic. The ways that we collect, analyze, and report them, greatly influences the degree to which they inform a meaningful response. Reported new COVID-19 cases is a proxy for the measure that concerns us. It was the first drop since March 21. points, or 7.73%).

Testing 109

Testing Statistics Reporting Marketing 109

O'Reilly on Data

MARCH 23, 2023

There are more that I haven’t listed, and there will be even more by the time you read this report. That statement would certainly horrify the researchers who are working on them, but at the level we can discuss in a nontechnical report, they are very similar. Why are we starting by naming all the names?

IT 346

IT Modeling Testing Risk 346

Wayne Yaddow

MARCH 5, 2025

In this post, well see the fundamental procedures, tools, and techniques that data engineers, data scientists, and QA/testing teams use to ensure high-quality data as soon as its deployed. First, we look at how unit and integration tests uncover transformation errors at an early stage. Key Tools & Processes Testing frameworks (e.g.,

Testing 52

Testing Data Transformation Statistics Metadata 52

O'Reilly on Data

MAY 21, 2019

A catalog or a database that lists models, including when they were tested, trained, and deployed. In particular, auditing and testing machine learning systems will rely on many of the tools I’ve described above. How much model inference is involved in specific applications? Metadata and artifacts needed for audits.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

DataKitchen

OCTOBER 5, 2022

Observability also validates that your data transformations, models, and reports are performing as expected. Through the yelling, he learns that a compliance report, sent to critical business partners, was empty! A survey of data engineers conducted by DataKitchen in 2022 revealed some shocking statistics. his boss’s boss?and

Testing 169

Testing Risk Data Processing Statistics 169