DataKitchen

OCTOBER 5, 2022

A 2019 DataKitchen/Eckerson survey found that 79% of companies have more than three data-related errors in their pipelines per month. Bad data reaches the customer because companies haven’t invested enough, or at all, in testing, automation, and monitoring. Crisis happens, errors are inevitable.

Testing 173

Testing Risk Data Processing Statistics 173

Smart Data Collective

MARCH 23, 2020

According to the SensorTower statistics , in 2019, a simple arcade game Stack Ball reached 100 million installs and only continued to grow. In 2019, this number increased to 2.4 The number of downloads and purchases increases every minute. PC gaming isn’t going to give up its position either. In 2014, there were about 1.82

Big Data 131

Big Data Recreation/Entertainment Data mining Optimization 131

CIO Business Intelligence

AUGUST 23, 2024

In 2019, CSU partnered with INE Security to integrate the Junior Penetration Tester (eJPT) certification into its curriculum. The Bureau of Labor Statistics projects a 31% growth in employment for information security analysts from 2019 to 2029, significantly faster than the average for all occupations.

Testing 111

Testing Statistics Risk Data-driven 111

datapine

NOVEMBER 27, 2019

2019 was a particularly major year for the business intelligence industry. The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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 363

Management Machine Learning Experimentation Metrics 363

CIO Business Intelligence

MARCH 15, 2022

Synthetic data can also be a vital tool for enterprise AI efforts when available data doesn’t meet business needs or could create privacy issues if used to train machine learning models, test software, or the like. For software testing: Using real data to test new software can create privacy and security problems.

Strategy 145

Strategy Testing Sales Modeling 145

CIO Business Intelligence

MAY 27, 2024

The path to securing the boardroom’s buy-in is more complex than simply having the right statistics and studies on paper,” says Dara Warn, the CEO of INE Security , a global cybersecurity training and certification provider. “To Leverage Data and Statistics Presenting data from reputable sources can lend credibility to the argument.

Cost-Benefit 116

Cost-Benefit Statistics ROI Measurement 116

Business Over Broadway

JANUARY 19, 2021

The top tool used by data professionals to analyze data are local development environments (48%), followed by basic statistical software (30%). Basic statistical software (Microsoft Excel, Google Sheets, etc.) (30%). Advanced statistical software (SPSS, SAS, etc.) (6%). Advanced statistical software: Statistician.

Business Intelligence 85

Business Intelligence Analytics Statistics Machine Learning 85

Smart Data Collective

APRIL 13, 2021

After a marginal increase in 2015, another steep rise happened in 2016 through 2017 before the volume decreased in 2018 and rose in 2019, and dropped again in 2020. One of the best solutions for data protection is advanced automated penetration testing. By 2012, there was a marginal increase, then the numbers rose steeply in 2014.

Testing 131

Testing Behavioral Analytics Data-driven Big Data 131

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. A single model may also not shed light on the uncertainty range we actually face.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

DataKitchen

OCTOBER 5, 2022

A 2019 DataKitchen/Eckerson survey found that 79% of companies have more than three data-related errors in their pipelines per month. Bad data reaches the customer because companies haven’t invested enough, or at all, in testing, automation, and monitoring. Crisis happens, errors are inevitable.

Testing 130

Testing Risk Data Processing Statistics 130

IBM Big Data Hub

APRIL 13, 2023

Creating train/test partitions of the dataset Before collecting deeper insights into the data, I’ll divide this dataset into train and test partitions using Db2’s RANDOM_SAMPLING SP. outtable=FLIGHT.FLIGHTS_TRAIN, by=FLIGHTSTATUS') Copy the remaining records to a test PARTITION. Create a TRAIN partition.

Modeling 81

Modeling Statistics Machine Learning Testing 81

Insight

MAY 14, 2020

Image source: [link] Motivation Beginning around December 2019, patients with severe respiratory infections began arriving at hospitals in Wuhan, kicking off a race to identify the cause of the illness. How can we quickly understand emerging infectious diseases? However, it would be about a month before the new pathogen was fully identified.

Deep Learning 98

Deep Learning Statistics Modeling Machine Learning 98

Cloudera

DECEMBER 3, 2021

In 2019, the Gradient institute published a white paper outlining the practical challenges for Ethical AI. Tracking key metrics and statistical distributions over time and alerting humans when either of these significantly drift can ensure that systems remain performant and fair. We need to get to the root of the problem.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

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 73

Testing Measurement Behavioral Analytics Statistics 73

CIO Business Intelligence

APRIL 7, 2022

The number of people quitting their jobs has been unprecedented throughout the pandemic, hitting a record high of 48 million people in 2020, up from 42 million in 2019, which was the previous record high. The “Great Resignation” has been no exaggeration. Not every company will be able to use AI to predict attrition, however.

Consulting 145

Consulting Interactive Management Metadata 145

Smart Data Collective

OCTOBER 14, 2019

In September 2019, Google decided to make it’s Differential Privacy Library available as an open-source tool. As long as two modules both conform to the same set of standards, you can swap them out, and due to the shared characteristics of the modules, this aspect of Kubernetes can shorten your integration testing process.

Data Science 94

Data Science Machine Learning Big Data Interactive 94

datapine

FEBRUARY 23, 2023

2) Charts And Graphs Categories 3) 20 Different Types Of Graphs And Charts 4) How To Choose The Right Chart Type Data and statistics are all around us. That said, there is still a lack of charting literacy due to the wide range of visuals available to us and the misuse of statistics. Table of Contents 1) What Are Graphs And Charts?

Visualization 177

Visualization Dashboards Sales Measurement 177

IBM Big Data Hub

JANUARY 25, 2024

trillion, up from USD 864 billion in 2019 to 2020. Over time, inventory managers have tested different approaches to determine the best fit for their organizations. Consider these questions: Do you have a platform that combines statistical analyses, prescriptive analytics and optimization algorithms? Is it easier said than done?

Optimization 73

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 73

Smarten

MAY 11, 2017

Advanced Data Discovery allows business users to perform early prototyping and to test hypothesis without the skills of a data scientist, ETL or developer. Plug n’ Play Predictive Analysis enables business users to explore power of predictive analytics without indepth understanding of statistics and data science.

Experimentation 49

Experimentation Visualization Predictive Analytics Business Intelligence 49

KDnuggets

JULY 30, 2019

This article is designed to give you a full picture from constructing a hypothesis testing to understanding p-value and using that to guide our decision making process.

Testing 93

Testing Statistics Data Science 93

Depict Data Studio

APRIL 16, 2019

GRADprofdev #GradsDo pic.twitter.com/Dw15UFiFDh — GradSchoolatUSC (@GradSchoolatUSC) April 5, 2019. Long ago, I had majored in psychology so I could take as many research methods and statistics courses as possible. link] — Heather Brandt (@BlondeScientist) April 11, 2019. Hey check out this data viz!

Visualization 56

Visualization Reporting Statistics Dashboards 56

Domino Data Lab

AUGUST 8, 2019

Sci Foo 2019. For example, meeting Carole Goble was one of the top highlights of Sci Foo 2019 for me. Putting discussions about security aside, the statistics competency required to confront fairness and bias issues for machine learning models in production set quite a high bar. Do those concerns sound familiar?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). As introduced in Zaheer et al. Louidor, E.,

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. e-handbook of statistical methods: Summary tables of useful fractional factorial designs , 2018 [3] Ulrike Groemping.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Jen Stirrup

OCTOBER 21, 2019

I’m holding a Diversity and Inclusion Unconference session at Microsoft Ignite in November 2019. For the leaders, the simplest option can simply be doing nothing, but let someone run around burning themselves out so that eventually it becomes a test of patience and stamina, rather than a test of what is right and wrong.

Data-driven 49

Data-driven Marketing Testing Insurance 49

Domino Data Lab

MARCH 3, 2019

Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). AI Adoption in the Enterprise: How Companies Are Planning and Prioritizing AI Projects in Practice (Feb 2019). I’m here mostly to provide McLuhan quotes and test the patience of our copy editors with hella Californian colloquialisms.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Andrew White

JANUARY 11, 2021

Storytelling is a nice one to use early on to test the approach. But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change. Yes, and no. We do have good examples and bad examples.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. We use the diagnostic test results of our regression model to support the reasons why CIs should not be used in financial data analyses. and an error term ??

Statistics 32

Statistics Uncertainty Risk Marketing 32

Domino Data Lab

MAY 8, 2019

They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. evaluate the effects of models on human subjects. Agile to the core.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Smart Data Collective

MAY 19, 2021

As recently as 2019, the consumption of renewable energy sources in the US grew for a fourth consecutive year, reaching a record 11.5 The trend for clean energy has been prevalent for years now, against the backdrop of the assertion that global fossil fuel resources are likely to be depleted by the year 2060.

Data Analytics 98

Data Analytics Analytics Big Data Predictive Analytics 98

Insight

FEBRUARY 19, 2020

In 2019, Netflix alone released 371 new TV shows and movies. I held out 20% of this as a test set and used the remainder for training and validation. Below is the result of a single XGBoost model trained on 80% of the data and tested on the unseen held-out 20%. The solid line shows the y=x line for comparison.

Risk 67

Risk ROI Modeling Metrics 67

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

O'Reilly on Data

JANUARY 25, 2021

Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019. It’s particularly difficult if testing includes issues like fairness and bias. Enough preliminaries. O’Reilly Online Learning.

Machine Learning 364

Machine Learning Software Testing Technology 364

Sisense

JULY 27, 2021

The box score was developed by sportswriter Henry Chadwick in 1858, and over 150 years later, statistics, data, and analysis have revolutionized the sport. Beyond the spike in strikeouts (which would have been noticeable by sheer mathematics), researchers at The Post also relied on another time-tested sports-analysis method: watching tape.

Analytics 52

Analytics Data-driven Statistics Measurement 52

Jet Global

MAY 1, 2023

According to a 2019 ESG survey , developers were able to customize analytics based on what was best for the applications instead of making design choices to work with existing tools and were able to offer products that improved average selling price (ASP)and/or order value, which increased by as much as 25 percent.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

The Unofficial Google Data Science Blog

MARCH 24, 2025

This role has several explicit requirements including statistical expertise, programming/ML, communication, data analysis/intuition. Focusing narrowly on the first of these, the description currently states that candidates will bring scientific rigor and statistical methods to the challenges of product creation.

Statistics 58

Statistics Testing Interactive Sales 58