Smart Data Collective

JUNE 8, 2023

The introduction of data collection and analysis has revolutionized the way teams and coaches approach the game. Liam Fox, a contributor for Forbes detailed some of the ways that data analytics is changing the NFL. Big data will become even more important in the near future.

Data Analytics 105

Data Analytics Analytics Data Collection Statistics 105

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

datapine

JANUARY 6, 2022

Qualitative data, as it is widely open to interpretation, must be “coded” so as to facilitate the grouping and labeling of data into identifiable themes. Quantitative analysis refers to a set of processes by which numerical data is analyzed. It is the sum of the values divided by the number of values within the data set.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

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

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

MAY 8, 2022

Let’s not forget that big data and AI can also automate about 80% of the physical work required from human beings, 70% of the data processing, and more than 60% of the data collection tasks. From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace.

Big Data 122

Big Data Data Analytics Analytics Cost-Benefit 122

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

Smart Data Collective

DECEMBER 8, 2020

The driving force behind this trend is mostly down to the rising concern people have over their online privacy and the unregulated data collection that has been going on silently in the background for many years. This is obviously more of an issue for some people than others, depending on where you live in the world.

Big Data 133

Big Data Data-driven Statistics Software 133

CIO Business Intelligence

SEPTEMBER 30, 2024

-based research firm is proud of its mission to deliver accurate data to ensure goods and services are distributed with equity and precision in a socially just manner.

Data Quality 116

Data Quality Experimentation Insurance Statistics 116

CIO Business Intelligence

SEPTEMBER 27, 2024

The data is then re-transported when the line is available. This doesn’t detract from the fact it’s a very advanced clinical data collection system since it’s digital, in real time, and secure because the data is encrypted on VPN and sent to Emergency’s central data center in Milan.

Management 128

Management IT Cost-Benefit Testing 128

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

Smart Data Collective

FEBRUARY 14, 2023

Features of Video Game Data Analytics Since we have touched on such important actors in the game dev field, it will be in the right place to remind us of what they do. After all, analytics is not just looking at statistics and reading player reviews.

Big Data 134

Big Data Data Analytics Analytics Testing 134

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. Exploratory analysis is a critical component of the data science lifecycle.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

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. This helps to protect sensitive data from prying eyes and reduces the risk of data breaches and cyber attacks.

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 85

Dashboards Statistics Data Collection Business Intelligence 85

FineReport

APRIL 15, 2020

Unlike state-run health care systems in countries like South Korea and China, in most countries, each state or area manages that health data differently, creating disparate data sets, which increases the difficulty of statistics and allocate resources. Five Data Collection Forms. Download template.

Visualization 52

Visualization Dashboards Statistics Data Collection 52

CIO Business Intelligence

FEBRUARY 3, 2023

Power Advisor tracks statistics about performance to locate bottlenecks and other issues. Pega wants to deliver “self-healing” and “self-learning” applications that can use AI and other statistics to recognize new opportunities for better automation. Microsoft is integrating some of its AI into Power.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

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

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

Generally, if the relative amount of data in a slice is the same across your two groups, you can safely make a comparison. Consider practical significance With a large volume of data, it can be tempting to focus solely on statistical significance or to hone in on the details of every bit of data.

Metrics 107

Metrics Measurement Statistics Data Collection 107

Smart Data Collective

JUNE 15, 2022

Accurate client data collection and analysis are critical to maximizing all of these activities. When customers visit your website, they generate data points that may be mined for important insights about what works and what doesn’t on your site. Better Understand Customer Demographics.

Advertising 111

Advertising Sales Cost-Benefit ROI 111

IBM Big Data Hub

SEPTEMBER 28, 2023

This process is designed to help mitigate risks so that model outputs can be deployed responsibly with the assistance of watsonx.data and watsonx.governance (coming soon). Building transparency into IBM-developed AI models To date, many available AI models lack information about data provenance, testing and safety or performance parameters.

Testing 87

Testing Finance Enterprise Modeling 87

Occam's Razor

MARCH 30, 2017

We are needed today because data collection is hard. Most humans employed by companies were unable to access data – not intelligent enough or trained enough or simply time pressures. Sidebar: If you don’t know these three phrases, please watch my short talk: A Big Data Imperative: Driving Big Action.]. 415 million (!)

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

FineReport

APRIL 15, 2020

Davis Wright Tremaine advised that employers should take the following considerations into account to determine if work from home may be possible: Operational requirements; Security of work data; Technological capabilities and equipment necessary to perform job duties; Productivity; and. And it is convenient for HRs to update statistics.

Visualization 52

Visualization Statistics Dashboards Data Collection 52

FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes.

Statistics 52

Statistics Data mining Visualization Reporting 52

IBM Big Data Hub

APRIL 22, 2024

The US City of Atlanta , for example, uses IBM data collection, machine learning and AI to monitor public transit tunnel ventilation systems and predict potential failures that could put passengers at risk. This will help advance progress by optimizing resources used.

IoT 77

IoT Internet of Things Cost-Benefit Reporting 77

The Unofficial Google Data Science Blog

APRIL 17, 2017

They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet. If unaccounted for, these data points can have an adverse impact on forecast accuracy by disrupting seasonality, holiday, or trend estimation.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

CDW Research Hub

NOVEMBER 6, 2020

Every year companies invest resources on data collection, and employees spend countless hours mulling over that data to make informed business decisions like how to market to their target audience or where to expand the business. Will just any data protection solution get the job done? Know your security risks.

Scorecard 40

Scorecard Risk Business Driver Strategy 40

Jet Global

FEBRUARY 25, 2025

Saving Money Bad data costs businesses big. Stronger Security Outdated or irrelevant data is a liability and cleaning house reduces risks. But what happens when businesses dont clean their data? Lets take a closer look at just how expensive dirty data can be. Which Comes First, Data Cleanse or CPM solution?

Cost-Benefit 52

Cost-Benefit Data Collection Finance Reporting 52

DataRobot Blog

DECEMBER 1, 2022

Artificial intelligence (AI) can help improve the response rate on your coupon offers by letting you consider the unique characteristics and wide array of data collected online and offline of each customer and presenting them with the most attractive offers. How Can AI Target the Right Prospects with Sharper Personalization?

Machine Learning 52

Machine Learning Statistics Marketing Sales 52

IBM Big Data Hub

AUGUST 7, 2023

In an ideal scenario, they would be able to, with relative and consistent accuracy, predict performance of clinical trial sites that are at risk of not meeting their recruitment expectations. Ultimately, enabling real-time monitoring of site activities and enrollment progress could prompt timely mitigation actions ahead of time.

Optimization 55

Optimization Forecasting Data-driven Strategy 55

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

Snapshot 95

Snapshot Data Lake Testing Strategy 95

Jet Global

MAY 15, 2020

As such, it can be concluded that the higher the ratio, the higher the risk to shareholders. This ratio is often used by lenders when considering a loan, as it gives an idea of how much risk they will be taking on. Total-Debt-to-Equity = (Short-Term Debt + Long-Term Debt) / Shareholder’s Equity. Instant updates.

Metrics 98

Metrics Finance Reporting KPI 98

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

JUNE 23, 2019

All you need to know, for now, is that machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn based on data by being trained on past examples. The biggest time sink is often around data collection, labeling and cleaning.

Management 110

Management Machine Learning Experimentation Metrics 110

O'Reilly on Data

JULY 28, 2020

This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. A product needs to balance the investment of resources against the risks of moving forward without a full understanding of the data landscape. Conclusion.

Marketing 364

Marketing Experimentation Metrics Testing 364