datapine

APRIL 14, 2022

“You can have data without information, but you cannot have information without data.” – Daniel Keys Moran. When you think of big data, you usually think of applications related to banking, healthcare analytics , or manufacturing. However, the usage of data analytics isn’t limited to only these fields. Discover 10.

Big Data 244

Big Data Recreation/Entertainment Analytics Data-driven 244

Cloudera

MARCH 30, 2022

Sometimes it takes a billion-dollar mistake to bring the murkier side of data ethics into sharp focus. Equifax found this out to their own cost in 2017 when they failed to protect the data of almost 150 million users globally. The ongoing challenges of the data-driven business model.

Data-driven 116

Data-driven Marketing Measurement Modeling 116

CIO Business Intelligence

MAY 16, 2023

higher [in 2022] than in 2017.” The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening. McKinsey & Company’s 2022 Global Survey on AI says , “AI adoption globally is 2.5x

Advertising 87

Advertising Recreation/Entertainment Experimentation Enterprise 87

Jet Global

OCTOBER 8, 2020

Most operational finance activities are driven by the month end and ledger close, typically involving a web of steps including transaction processing, reconciliation, journal entry capture, and financial statement preparation. It also decreases the risk of errors by eliminating disjointed, manual processes.

Finance 98

Finance Reporting Forecasting Metrics 98

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

BizAcuity

MARCH 25, 2019

This is resulting in the largest event management companies across this sector spending more than $43 billion on revenue analytics – which is a multi-dimensional and evolving field harnessing statistics, Artificial Intelligence and other tools to identify meaningful patterns in large data sets. Image Source: [link].

Analytics 74

Analytics Dashboards Sales Marketing 74

Data Insight

APRIL 15, 2019

“ It’s no coincidence that Google, Amazon and some of the most valuable companies in the world today were built not on product but on data from the outset.” We are now living in a world that is increasingly driven by data thanks to the emergence of digital and cloud-based technologies and the proliferation of social mobility.

Data-driven 40

Data-driven Metrics Measurement Strategy 40

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance. to Data Governance 2.0

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Domino Data Lab

MAY 20, 2021

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. This renders measures like classification accuracy meaningless. 1988), E-state data (Hall et al., Merging the two results in a completely balanced dataset (50:50). Their tests are performed using C4.5-generated

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Jet Global

MARCH 2, 2022

ESG reporting is the process of disclosing data by a company or organization about its environmental, social, and governance impacts. Privacy and data security. As such, there are no formal requirements that require companies and organizations to report and provide their ESG data. What is ESG Reporting? Social opportunity.

Reporting 59

Reporting Recreation/Entertainment Risk Insurance 59

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction. This is not that.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Cloudera

MAY 18, 2021

This article is the second in a multipart series to showcase the power and expressibility of FlinkSQL applied to market data. Code and data for this series are available on github. Flink SQL is a data processing language that enables rapid prototyping and development of event-driven and streaming applications.

Risk 94

Risk Marketing Risk Management Data-driven 94

Peter James Thomas

AUGUST 12, 2018

These normally appear at the end of an article, but it seemed to make sense to start with them in this case: Recently I published Building Momentum – How to begin becoming a Data-driven Organisation. A number of factors can play into the accuracy of data capture. Honesty of Data that is captured. Timing issues with Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction. Ever heard of it before?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. Unlike labels, embeddings are learned from the training data, not produced by humans.

IT 262

IT Modeling Testing Risk 262

CIO Business Intelligence

APRIL 12, 2022

Even though Nvidia’s $40 billion bid to shake up enterprise computing by acquiring chip designer ARM has fallen apart, the merger and acquisition (M&A) boom of 2021 looks set to continue in 2022, perhaps matching the peaks of 2015, according to a report from risk management advisor Willis Towers Watson. M&A volume climbed from $3.26

Enterprise 142

Enterprise Technology Consulting Software 142

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” These questions are: Who is using what data?

Metadata 64

Metadata Data Governance Dashboards Software 64