KDnuggets

OCTOBER 30, 2019

Here are five statistical fallacies — data traps — which data scientists should be aware of and definitely avoid.

Statistics 123

Statistics 123

datapine

NOVEMBER 13, 2019

Fortunately, we live in a digital age rife with statistics, data, and insights that give us the power to spot potential issues and inefficiencies within the business. The post Your Definitive Guide To Modern & Professional Procurement Reports appeared first on BI Blog | Data Visualization & Analytics Blog | datapine.

Reporting 158

Reporting KPI Cost-Benefit Metrics 158

David Menninger's Analyst Perspectives

SEPTEMBER 23, 2021

Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions.

Machine Learning 235

Machine Learning Key Performance Indicator Optimization Analytics 235

FineReport

JUNE 11, 2021

This article will discuss the definition of business intelligence and analytics and the difference between them. Definition. According to the definition, business intelligence and analytics refer to the data management solutions implemented in companies to collect, analyze and drive insights from data. Business Analytics.

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

Analytics Vidhya

JUNE 20, 2023

Both probabilities are associated with probabilities but differ in definition and usage. The article aims to clarify likelihood vs probability definitions, usage, and misconceptions for better understanding and application in the respective field. What is Likelihood?

Data Science 327

Data Science Analytics Statistics 327

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. But let’s see in more detail what experts say and how can we connect and differentiate the both.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Analytics Vidhya

JUNE 6, 2023

Beyond data storage, DBMS performs crucial functions such as data definition, manipulation, administration, and security. They serve as the backbone of information management by enabling efficient storage, retrieval, manipulation, and organization of vast amounts of data. appeared first on Analytics Vidhya.

Data-driven 291

Data-driven Management Analytics Statistics 291

Dataiku

APRIL 5, 2021

Data scientists: You may recognize or know some of these terms from your data science work, as they can be particularly helpful when applying statistics and probability to data science and machine learning. Whether you are working on a project where statistics might come in handy or you just want to discover (or freshen up on!)

Statistics 78

Statistics Data Science Machine Learning 78

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?

IT 317

IT Statistics KPI Data-driven 317

Analytics Vidhya

JULY 28, 2023

This article will discuss the definitions […] The post CDF vs PDF: What’s the Difference? Knowing differences between PDF vs CDF is crucial to analyze and interpret the probabilities linked to continuous and discrete random variables. appeared first on Analytics Vidhya.

Analytics 268

Analytics Statistics 268

O'Reilly on Data

JUNE 18, 2019

The good news is that researchers from academia recently managed to leverage that large body of work and combine it with the power of scalable statistical inference for data cleaning. business and quality rules, policies, statistical signals in the data, etc.). Data programming.

Machine Learning 263

Machine Learning Data Quality Statistics Modeling 263

datapine

MARCH 25, 2019

Conduct statistical analysis. One of the most pivotal types of data analysis methods is statistical analysis. Regression: A definitive set of statistical processes centered on estimating the relationships among particular variables to gain a deeper understanding of particular trends or patterns. Establish your questions.

Key Performance Indicator 217

Key Performance Indicator Statistics Visualization Big Data 217

DataKitchen

APRIL 28, 2021

Tools vendors are creating their own definitions of “data fabric” to promote their own product and solution offerings. If you search the Internet for a definition of data fabrics you can see discussions of storage, AI augmentation, and other tools. This is happening to the term “data fabric.”

Statistics 246

Statistics Optimization Technology Data Analytics 246

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

datapine

MAY 14, 2019

For those embarking on a journey to master the art of the ‘R’ language – a statistical computing program and framework for increased business intelligence-based success – Advanced R is intuitive, easy to follow, and will give you a well-rounded overview of this invaluable area of data science. click for book source**.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

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. Models will need to be customized (for specific locations, cultural settings, domains, and applications).

Machine Learning 223

Machine Learning Risk Management Statistics 223

Rocket-Powered Data Science

MARCH 19, 2019

Here, we broaden our meaning of “bias” to go beyond model bias, which has the technical statistical meaning of “underfitting”, which essentially means that there is more information and structure in the data than our model has captured.

Big Data 192

Big Data Statistics Manufacturing Data Science 192

FineReport

JUNE 11, 2021

This article will discuss the definition of business intelligence and analytics and the difference between them. Definition. According to the definition, business intelligence and analytics refer to the data management solutions implemented in companies to collect, analyze and drive insights from data. Business Analytics.

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

O'Reilly on Data

MARCH 26, 2024

But perhaps it should infringe something: even when the collection of data is legal (which, statistically, it won’t entirely be for any web-scale corpus), it doesn’t mean it’s legitimate, and it definitely doesn’t mean there was informed consent. To see this, let’s consider another example, that of MegaFace. joined Flickr.

Modeling 279

Modeling Machine Learning Risk Advertising 279

Rocket-Powered Data Science

JULY 7, 2019

Definitions of terminology frequently seen and used in discussions of emerging digital technologies. Examples: (1-3) All those applications shown in the definition of Machine Learning. (4) Example applications: (1) High-definition and 3D video. (2) Career Relevance. NOTE: This page is a WIP = Work In Progress.). 4) Prosthetics.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

DataKitchen

MARCH 12, 2024

Thanks to Observability, I could diagnose the problem – definitely helped me a lot during the process.” It’s definitive, and that changes the game, especially for senior leadership.” DataKitchen helped us completely transform our operations by broadening our testing definition. Databricks was all green.

Metrics 124

Metrics Software Cost-Benefit Testing 124

datapine

SEPTEMBER 16, 2022

But often that’s how we present statistics: we just show the notes, we don’t play the music.” – Hans Rosling, Swedish statistician. It is a definitive reference for anyone who wants to master the art of dashboarding. 14) “Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics” by Nathan Yau.

Visualization 304

Visualization Dashboards Data-driven Statistics 304

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics. and an error term ??

Statistics 27

Statistics Uncertainty Risk Marketing 27

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Among these, only statistical uncertainty has formal recognition.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

datapine

JANUARY 6, 2022

First of all, let’s find a definition to understand what lies behind data interpretation meaning. 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.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Smart Data Collective

NOVEMBER 18, 2020

The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Previously, such problems were dealt with by specialists in mathematics and statistics. Definition: Data Mining vs Data Science. Statistics, mathematics, linear algebra.

Data mining 144

Data mining Data Science Informatics Statistics 144

DataKitchen

OCTOBER 11, 2021

Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. Statistical Process Control – applies statistical methods to control a process. When is a project ready to be pushed to production? When can you declare it done?

Testing 162

Testing Metadata Dashboards Statistics 162

CIO Business Intelligence

JUNE 21, 2024

of market share separating SAP and Salesforce, IDC regards these two companies as statistically tied for the number 1 position in the worldwide enterprise applications market for 2023,” it said in a new study, Worldwide Enterprise Applications Software Forecast, 2024–2028. market share between them, according to International Data Corp.

Marketing 128

Marketing Enterprise Forecasting Statistics 128

The Data Visualisation Catalogue

APRIL 26, 2024

This allows for the definition of functional quantiles and the identification of central and outlying observations. Median Curve: The median curve represents the most central observation and serves as a robust statistic for centrality. The key features of a Functional Box Plot includes: Data Ordering: The functional data (e.g.

Snapshot 102

Snapshot Statistics Visualization Measurement 102

O'Reilly on Data

JUNE 18, 2024

During training, the AI model learns the statistical relationships between the words or images in its training set. Rather, they are a statistical representation of the probability, based on the training data, that one word will follow another, or in an image, that one pixel will be adjacent to another. We need to achieve both goals.

Advertising 353

Advertising Modeling Publishing Data Processing 353

TDAN

JANUARY 3, 2024

Edwards Deming, the father of statistical quality control, said: “If you can’t describe what you are doing as a process, you don’t know what you’re doing.” When looking at the world of IT and applied to the dichotomy of software and data, Deming’s quote applies to the software part of that pair. The analogous […]

Statistics 52

Statistics Software Data Quality IT 52

Business Over Broadway

JULY 29, 2020

Analysis of usage of 5 primary tools used to analyze data showed that the top tool used by data professionals to analyze data are local development environments (54%), followed by basic statistical software (20%), cloud-based data software and APIs (8%), advanced statistical software (6%) and business intelligence software (6%).

Statistics 92

Statistics Business Intelligence Software Data Science 92

datapine

APRIL 2, 2019

Let’s start with a simple definition. A KPI scorecard is a term used to describe a statistical record that measures progress or achievement towards a set performance indicator. We have established the definition, general characteristics, benefits and the difference between scorecard and dashboard. What Is A KPI Scorecard?

Scorecard 226

Scorecard KPI Dashboards Reporting 226

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. Commonly used models include: Statistical models. They emphasize access to and manipulation of a model.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

OCTOBER 26, 2023

It’s a role that combines hard skills such as programming, data modeling, and statistics with soft skills such as communication, analytical thinking, and problem-solving. Business intelligence analyst resume Resume-writing is a unique experience, but you can help demystify the process by looking at sample resumes.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

FineReport

JUNE 14, 2022

Definition of Business Report. A business report is a formal document that objectively provides statistical data, summarizes historical facts, and sometimes offers reasonable recommendations for a company’s managers. And a report with plenty of statistical data or words is not intuitive enough to read and comprehend.

Reporting 52

Reporting IT Sales Dashboards 52

FineReport

JANUARY 5, 2022

Definition. In addition, it can provide a predictive analysis of a specific issue based on statistics and historical data. One method is using Excel built-in charts to do some conventional statistical charts and some advanced dynamic charts. Analytics Report: Definite Guide You Will Ever Need shows at FineReport first.

Reporting 52

Reporting Analytics Visualization Dashboards 52