CIO Business Intelligence

NOVEMBER 7, 2023

As the end of 2023 approaches, it becomes imperative to assess the current landscape of cybersecurity threats, explore potential strategies to combat them, and explore the new practice measures that can be taken. PAM can help prevent insider threat risks and reduce the potential of credentials becoming compromised.

Measurement 114

Measurement Risk Strategy Statistics 114

IBM Big Data Hub

AUGUST 9, 2023

A phishing simulation is a cybersecurity exercise that tests an organization’s ability to recognize and respond to a phishing attack. Why phishing simulations are important Recent statistics show phishing threats continue to rise. The only difference is that recipients who take the bait (e.g., million phishing sites.

Testing 80

Testing Measurement Behavioral Analytics Reporting 80

IBM Big Data Hub

APRIL 9, 2024

. “With the data we’ve prepared we can then calculate the odds of a birdie or an eagle from a particular sector; we can also look across to the opposite side of the fairway for contrastive statistics,” says Baughman. We also measure response time since this is a near real-time system.

Management 86

Management IT Machine Learning Metrics 86

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 124

Data Analytics Diagnostic Analytics Management Analytics 124

Smart Data Collective

OCTOBER 8, 2023

It is an interdisciplinary field, combining computer science, statistics , mathematics, and business intelligence. Data Analysis The cleaned data is then analyzed using various statistical techniques and algorithms. This could involve identifying patterns and trends, testing hypotheses, or making predictions.

Data Analytics 95

Data Analytics Analytics Statistics Data Collection 95

datapine

JANUARY 6, 2022

Yet, before any serious data interpretation inquiry can begin, it should be understood that visual presentations of data findings are irrelevant unless a sound decision is made regarding scales of measurement. Interval: a measurement scale where data is grouped into categories with orderly and equal distances between the categories.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

datapine

JANUARY 24, 2021

Once you have your data analytics questions, you need to have some standard KPIs that you can use to measure them. OK – so far, you’ve picked out some data analysis questions, and you’ve found KPIs to measure them. There are basically 4 types of scales: *Statistics Level Measurement Table*. Did the best according to what?

IT 317

IT Statistics KPI Data-driven 317

Smart Data Collective

SEPTEMBER 19, 2022

Statistics show that 93% of customers will offer repeat business when they encounter a positive customer experience. They can also anticipate industry trends, assess risks, and make strategic steps to elevate the customer experience. Improving Risk Assessment. Better UI/UX based on A/B testing. Improving Security.

Big Data 129

Big Data ROI Measurement Risk 129

IBM Big Data Hub

JULY 10, 2023

Vibration analysis—a component of condition monitoring systems—utilizes vibration sensors to measure frequencies in an asset and detect abnormalities that may indicate a problem. Understanding vibrations Vibrations are multidimensional, so vibration testing requires an understanding of various parameters.

Optimization 59

Optimization IT Measurement Cost-Benefit 59

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. 6] Debugging may focus on a variety of failure modes (i.e., Sensitivity analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

datapine

SEPTEMBER 29, 2022

5) How Do You Measure Data Quality? In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. How Do You Measure Data Quality? Table of Contents. 2) Why Do You Need DQM?

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

AUGUST 24, 2023

Gen AI has the potential to magnify existing risks around data privacy laws that govern how sensitive data is collected, used, shared, and stored. We’re getting bombarded with questions and inquiries from clients and potential clients about the risks of AI.” The risk is too high.” Not without warning signs, however.

Uncertainty 94

Uncertainty Risk Testing Enterprise 94

Cloudera

DECEMBER 3, 2021

Surely there are ways to comb through the data to minimise the risks from spiralling out of control. This involves identifying, quantifying and being able to measure ethical considerations while balancing these with performance objectives. Uncertainty is a measure of our confidence in the predictions made by a system.

Uncertainty 98

Uncertainty Measurement Metrics Risk 98

CIO Business Intelligence

FEBRUARY 13, 2023

The name references the Greek letter sigma, which is a statistical symbol that represents a standard deviation. Larger is Better involves a “lower specification limit,” such as test scores — where the target is 100%. At this stage, it’s important to establish performance baselines, future goals, and how performance will be measured.

Management 71

Management Statistics Manufacturing Measurement 71

Sisense

JANUARY 21, 2020

This is an example of Simpon’s paradox , a statistical phenomenon in which a trend that is present when data is put into groups reverses or disappears when the data is combined. It’s time to introduce a new statistical term. A new drug promising to reduce the risk of heart attack was tested with two groups.

Testing 104

Testing Risk Data-driven Statistics 104

CIO Business Intelligence

APRIL 27, 2023

Relevant skills for a systems architect include risk management, performance optimization, security, leadership, and a strong knowledge of complex computer systems. The role requires identifying resource requirements, creating and defining project objectives, establishing necessary timelines, and determining potential risks.

IT 111

IT Software Risk Management 111

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. Predictive Analytics can help businesses in reducing risk (eg. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. Predictive Analytics can help businesses in reducing risk (eg. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. All descriptive statistics can be calculated using quantitative data. Digging into quantitative data. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

erwin

JANUARY 11, 2019

These source mappings generally are documented across a slew of unwieldy spreadsheets in their “pre-ETL” stage as the input for ETL development and testing. Doing so will require a hearty data management strategy and technology for automating the timely delivery of quality data that measures up to business demands.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. It might analyze real-time data from cameras, LiDAR and other sensors to identify objects, assess risks and anticipate environmental changes like sudden weather events or unexpected obstacles.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

AWS Big Data

APRIL 3, 2024

As data is refreshed and updated, changes can happen through upstream processes that put it at risk of not maintaining the intended quality. By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes.

Data Quality 88

Data Quality Visualization Metadata Metrics 88

Ontotext

APRIL 3, 2024

So, this is a big driver for the outcome because when you are saving money for the business, you can measure it and see its value. Nimit Mehta : You are talking about the three big ones: cost, revenue, and risk. And, when you get to the top, it’s about risks and existential threats to the business. It’s open. Maybe later.

Technology 59

Technology Risk Digital Transformation Measurement 59

AWS Big Data

DECEMBER 7, 2023

In this post, we outline planning a POC to measure media effectiveness in a paid advertising campaign. We chose to start this series with media measurement because “Results & Measurement” was the top ranked use case for data collaboration by customers in a recent survey the AWS Clean Rooms team conducted.

Measurement 91

Measurement Advertising Testing Data-driven 91

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. This has serious implications for software testing, versioning, deployment, and other core development processes. Machine learning adds uncertainty.

Management 332

Management Machine Learning Experimentation Metrics 332

Smart Data Collective

AUGUST 15, 2019

Ultimately, shipping audits allow you to identify measurable savings and discover a greater level of transparency between your current pricing across carriers. Market Testing. For example, Chime Bank used artificial intelligence to test 216 versions of its homepage in just three months. Indirect Costs.

Big Data 84

Big Data Sales Testing Statistics 84

IBM Big Data Hub

AUGUST 11, 2023

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. These insights can help drive decisions in business, and advance the design and testing of applications.

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

Rita Sallam

APRIL 2, 2023

For the vendors that participate in the Bake-Off and Show Floor Showdowns, it is in equal measure fun and extremely stressful. Qlik Key Findings: In the US alone, there’s $367 billion in agricultural commodities at risk to flooding in the US alone. million people at risk of catastrophic, flooding. In 2000, the Netherlands had 8.5

Optimization 52

Optimization Machine Learning Insurance Risk 52

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. Because individual observations have so little information, statistical significance remains important to assess.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

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. Even if you do not expect a slice to matter, looking at a few slices for internal consistency gives you greater confidence that you are measuring the right thing.

Metrics 107

Metrics Measurement Statistics Data Collection 107

O'Reilly on Data

MAY 27, 2020

Using the new scores, Apgar and her colleagues proved that many infants who initially seemed lifeless could be revived, with success or failure in each case measured by the difference between an Apgar score at one minute after birth, and a second score taken at five minutes. Books, in turn, get matching scores to reflect their difficulty.

Risk 355

Risk Testing Reporting Measurement 355

Business Over Broadway

SEPTEMBER 27, 2018

Your marketing strategy is only as good as your ability to deliver measurable results. pharmacogenomics) and risk assessment of genetic disorders (e.g., genetic counseling, genetic testing). At this point, you can extract a list of users who are at risk of churning by choosing a churn score cutoff e.g. greater than 0.80.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Smarten

JUNE 29, 2018

Logistic regression measures the relationship between the categorical target variable and one or more independent variables. Based on these labels, the bank can easily make a decision on whether to give a loan to an applicant and the credit limit and interest rate each applicant is eligible for based on the amount of risk involved.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Will this next trade return a profit?

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

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

The Unofficial Google Data Science Blog

JUNE 30, 2016

A naïve way to solve this problem would be to compare the proportion of buyers between the exposed and unexposed groups, using a simple test for equality of means. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

Statistics 44

Statistics Optimization Modeling Experimentation 44