O'Reilly on Data

MARCH 31, 2020

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. After training, the system can make predictions (or deliver other results) based on data it hasn’t seen before. Machine learning adds uncertainty.

Management 363

Management Machine Learning Experimentation Metrics 363

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

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

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? What happens next?

KPI 221

KPI Management Key Performance Indicator Measurement 221

FineReport

FEBRUARY 25, 2020

Data collection is nothing new, but the introduction of mobile devices has made it more interesting and efficient. But now, mobile data collection means information can be digitally recording on the mobile device at the source of its origin, eliminating the need for data entry after the information is collected.

Data Collection 59

Data Collection IT Dashboards Reporting 59

Smart Data Collective

DECEMBER 9, 2021

Businesses already have a wealth of data but understanding your business will help you identify a data need – what kind of data your business needs to collect and if it collects too much or too little of certain data. Collecting too much data would be overwhelming and too little – inefficient.

Big Data 142

Big Data Data-driven Key Performance Indicator Testing 142

CIO Business Intelligence

AUGUST 9, 2024

Gartner agrees that synthetic data can help solve the data availability problem for AI products, as well as privacy, compliance, and anonymization challenges. The alternative to synthetic data is to manually anonymize and de-identify data sets, but this requires more time and effort and has a higher error rate.

Risk 138

Risk Measurement Data Lake Data Collection 138

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. In the realm of legal affairs, data analytics can serve as a strategic ally.

Data Analytics 125

Data Analytics Analytics Statistics Data Collection 125

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). They provide more like an FAQ (Frequently Asked Questions) type of an interaction.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

DataKitchen

JUNE 24, 2021

So we really prioritized the data that we thought had the biggest chance of delivering success in the end. Chapin also mentioned that measuring cycle time and benchmarking metrics upfront was absolutely critical. “It DataOps Enables Your Data Mesh or Data Fabric. Design for measurability.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

Data Science 101

JANUARY 15, 2020

Bias ( syatematic unfairness in data collection ) can be a potential problem in experiments and we need to take it into account while designing experiments. Reliability: It means measurements should have repeatable results. For eg: you measure the blood pressure of a person. Statistics Essential for Dummies by D.

Experimentation 96

Experimentation Statistics Measurement Testing 96

FineReport

NOVEMBER 30, 2020

So, how can you measure your work on a larger scale? YoY growth can eliminate factors that can skew your data by comparing your monthly figures to a larger sample and comparable period. As you grow from year to year, comparing specific months or quarters can refine your statistics and make them appear more reliable to investors.

Statistics 98

Statistics Metrics Sales Data Collection 98

Smart Data Collective

MARCH 28, 2022

There are four main types of data analytics: Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. Improved decision-making will create more successful outcomes.

Data Analytics 105

Data Analytics Software Analytics Statistics 105

Smart Data Collective

APRIL 29, 2021

Big data has evolved from a technology buzzword into a real-world solution that helps companies and governments analyze data, extract the meaningful statistics, and apply it into their specific business needs. It’s not so much the realization that this information is collected, but what can be effectively done with it.

Big Data 125

Big Data Forecasting Unstructured Data Statistics 125

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. On the flip side, you sometimes have a small volume of data.

Metrics 107

Metrics Measurement Statistics Data Collection 107

Smart Data Collective

AUGUST 4, 2022

According to statistics, an astonishing 62% of managers are reluctant to talk to their employees about anything, while one in five business leaders feel uncomfortable when it comes to recognizing employees’ achievements. The authors state that data analytics saves managers time and reduces the risk of inadvertent bias.

Data-driven 135

Data-driven Metrics Data Collection Software 135

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

Smart Data Collective

AUGUST 31, 2020

At Smart Data Collective, we have talked extensively about the benefits of big data in digital marketing. We have focused a lot on using data analytics for SEO. However, there are a lot of other benefits of using big data in marketing. You shouldn’t limit yourself to using data analytics in your SEO strategy.

Data-driven 102

Data-driven Marketing Big Data Broadcasting 102

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

CIO Business Intelligence

JANUARY 17, 2024

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. According to Mohammed, the results of this digital transformation journey are measurable and impressive. js and React.js.

Digital Transformation 119

Digital Transformation Dashboards Data Science Reporting 119

Juice Analytics

MARCH 30, 2021

Data analyst —Data authors can’t create great art if they don’t like working with their materials. Data authors need to be comfortable with core statistical concepts and comfortable with manipulating data. Getting involved with deep data analysis can reveal the important messages and accurate ways to convey them.

Cost-Benefit 131

Cost-Benefit Statistics Metrics Dashboards 131

Smart Data Collective

MAY 4, 2023

Big data has been discussed by business leaders since the 1990s. It refers to datasets too large for normal statistical methods. Professionals have found ways to use big data to transform businesses. Furthermore, many websites have implemented anti-scraping measures to prevent bots from collecting data.

Data mining 109

Data mining Big Data Data-driven Measurement 109

AWS Big Data

MAY 16, 2023

In this first post of the series, we show you how data collected from smart sensors is used for building automated dashboards using QuickSight to help distribution network engineers manage, maintain and troubleshoot smart sensors and perform advanced analytics to support business decision making.

Dashboards 98

Dashboards Statistics Data Collection Business Intelligence 98

Rocket-Powered Data Science

SEPTEMBER 18, 2018

For the modern digital organization, the proof of any inference (that drives decisions) should be in the data! Rich and diverse data collections enable more accurate and trustworthy conclusions. In “big data language”, we are talking about one of the 3 V’s of big data: big data Variety!

Big Data 103

Big Data Data Science Data Collection Measurement 103

CIO Business Intelligence

FEBRUARY 13, 2023

The name references the Greek letter sigma, which is a statistical symbol that represents a standard deviation. The process aims to bring data and statistics into the mesh to help objectively identify errors and defects that will impact quality. Six Sigma was trademarked by Motorola in 1993.

Management 97

Management Statistics Manufacturing Measurement 97

Domino Data Lab

AUGUST 12, 2021

Taking a closer look at the data you will notice that some columns have questions marks ? For this dataset that is the way the data collection denotes missing data. Let’s look at some examples of the data in the dataset: masses.iloc[[20, 456, 512],:]. Severity is made out of integers. Pandas Profiler.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

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

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

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

FineReport

MARCH 7, 2024

However, due to regulatory controls on sensitive data like phone numbers and technical challenges in cross-platform integration of Internet and mobile reporting data, our current matching rates are relatively low, reaching around 20% in ideal scenarios, excluding telecom data.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Domino Data Lab

OCTOBER 2, 2019

As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences. You’ll measure this effect by looking at a quantity called the average treatment effect (ATE). What you really want to measure is the difference in outcomes. Let’s continue with this example.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Depict Data Studio

JULY 28, 2020

Staff were asked whether they received the support and resources they needed in spring 2020; whether they would be comfortable being inside a classroom with physical distancing measures in place; and whether they were comfortable taking their temperatures and wearing face coverings. Reactions from the School Board and Parents.

Visualization 102

Visualization Reporting Modeling Statistics 102

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

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

The Unofficial Google Data Science Blog

APRIL 17, 2017

First, the system may not be understood, and even if it was understood it may be extremely difficult to measure the relationships that are assumed to govern its behavior. They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

FineReport

JUNE 29, 2023

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. Generally, the primary objective of any IoT device in a connected environment is data collection.

IoT 52

IoT Dashboards Visualization Cost-Benefit 52

Depict Data Studio

APRIL 16, 2019

Long ago, I had majored in psychology so I could take as many research methods and statistics courses as possible. And learning how we learn–the courses on cognition, memory, perception, and brain biology–are critical in my everyday work as a data visualization designer and speaker. Increase the Inclusivity of Your Writing.

Visualization 56

Visualization Reporting Statistics Dashboards 56