Analytics Vidhya

APRIL 29, 2023

Data security is a critical concern for individuals, organizations, and governments as cyber attacks continue to rise in frequency and severity. These alarming numbers underscore the need for robust data security measures to protect sensitive information such as personal data, […] The post What is Data Security?

Risk 222

Risk Measurement Reporting Analytics 222

Smart Data Collective

OCTOBER 11, 2021

A central server is likely collecting tons of data from multiple sources; onboard measurements from the self-driving car, feedback from the driver, and external sources of data are all feeding into the system. It’s not strictly necessary to have a bachelor’s degree to begin working in data engineering, but it certainly helps.

Data mining 113

Data mining Data Science Software Machine Learning 113

Smart Data Collective

NOVEMBER 12, 2021

Big data technology has been instrumental in changing the direction of countless industries. Companies have found that data analytics and machine learning can help them in numerous ways. However, there are a lot of other benefits of big data that have not gotten as much attention. Global companies spent over $92.5 Here’s why.

Data-driven 103

Data-driven Cost-Benefit Data mining Big Data 103

Smart Data Collective

APRIL 5, 2022

Digital marketers have an easier time compiling data on customer engagements, because most behavior and variables can be easily tracked. Earlier this year, VentureBeat published an article titled How data science can boost SEO strategy. You can use data mining tools to find new keywords to target.

Marketing 127

Marketing Data Analytics Analytics Advertising 127

FineReport

DECEMBER 10, 2019

In column coordinates, column 0 represents the serial number, column 1 represents the name of the member, column 2 represents the age, column 3 represents the weight, columns 4-6 represent the measurements of the male members, and columns 7-9 represent the measurements for female members. Data Cleaning in Python.

Data mining 98

Data mining Data Quality Statistics Measurement 98

CIO Business Intelligence

DECEMBER 22, 2022

According to the DataOps Manifesto , DataOps teams value analytics that work, measuring the performance of data analytics by the insights they deliver. Analytics, Collaboration Software, Data Management, Data Mining, Data Science, IT Strategy, Small and Medium Business.

Analytics 126

Analytics Machine Learning Software Data Quality 126

Rocket-Powered Data Science

DECEMBER 16, 2018

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. e.g., true positive rate, true negative rate, total accuracy, F1-score , or what? How many hidden layers should there be?

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Smart Data Collective

MARCH 29, 2021

Unfortunately, this is not implemented in most cases, which leaves you with massive data amounts that are not useful. Additionally, data collection becomes a costly process. IoT automates data collection, in addition to simplifying data mining. Predictive and preventative maintenance.

Big Data 137

Big Data Management Cost-Benefit Internet of Things 137

Rocket-Powered Data Science

DECEMBER 15, 2018

The objective function (also known as cost function, or benefit function) provides an objective measure of model performance. Again, we measure the slope of the performance curve from two models, then proceed in the direction of better-performing models. That is the true key that unlocks performance in a cold-start challenge.

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

CIO Business Intelligence

MAY 30, 2024

To do that, McIntosh and OMES turned to process mining, a technique for analyzing event data to better understand and improve operational processes.

IT 127

IT Cost-Benefit Key Performance Indicator Dashboards 127

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., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Domino Data Lab

MAY 20, 2021

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. References. link] Fisher, R.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

IBM Big Data Hub

JANUARY 10, 2023

Leveraging data to replace the ‘gut feel’ on which too many business decisions are made enables change practitioners to separate perceptions from reality and decide which processes need the most focus. By applying process mining, you can quickly see levels of process compliance right across the organisation and right across the value chain.

Management 52

Management Data-driven Data mining Business Objectives 52

Ontotext

APRIL 15, 2020

As most of this data is relevant to specific regions, it is very important to be able to traverse sub-region relationships in order to aggregate information, discover correlations and other types of analysis.

Publishing 105

Publishing Metadata Data mining Technology 105

CIO Business Intelligence

MARCH 24, 2023

Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs. Key features include a collaborative business glossary, the ability to visualize data lineage, and generate data quality measurements based on business definitions.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Sisense

AUGUST 19, 2020

Disrupting Markets is your window into how companies have digitally transformed their businesses, shaken up their industries, and even changed the world through the use of data and analytics. The use of big data analytics and cloud computing has spiked phenomenally during the last decade.

Big Data 52

Big Data Machine Learning Digital Transformation Marketing 52

datapine

MARCH 31, 2022

BI developer skills encompass crafting and executing data-driven queries upon request as well as the ongoing technical development of a company’s BI platforms or solutions. Here is a more specific rundown of BI developer skills: Demonstrable experience in the areas of BI development or data science. Yes, they exist.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

datapine

NOVEMBER 27, 2019

While we work on programs to avoid such inconvenience , AI and machine learning are revolutionizing the way we interact with our analytics and data management while increment in security measures must be taken into account. It’s an extension of data mining which refers only to past data.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Domino Data Lab

AUGUST 1, 2021

but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. Instead, you should focus on how techniques like PDPs and LIME can be used to gain insights into the model’s inner workings and how you can add those to your data science toolbox. See Wei et al. References.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. In this post we explore how and why we can be “ data-rich but information-poor ”. There are many reasons for the recent explosion of data and the resulting rise of data science.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

JULY 22, 2020

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. Ramp-up solution: measure epoch and condition on its effect If one wants to do full traffic ramp-up and use data from all epochs, they must use an adjusted estimator to get an unbiased estimate of the average reward in each arm.

Experimentation 95

Experimentation Statistics Testing Strategy 95

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

Posteriors are useful to understand the system, measure accuracy, and make better decisions. Methods like the Poisson bootstrap can help us measure the variability of $t$, but don’t give us posteriors either, particularly since good high-dimensional estimators aren’t unbiased.

KDD 40

KDD Testing Machine Learning Modeling 40

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

And since the metric average is different in each hour of day, this is a source of variation in measuring the experimental effect. Let’s go back to our example of measuring the fraction of user sessions with purchase. Let $Y_i$ be the response measured on the $i$th user session.

Experimentation 40

Experimentation Metrics Statistics Measurement 40