IBM Big Data Hub

AUGUST 9, 2023

Why phishing simulations are important Recent statistics show phishing threats continue to rise. Since 2019, the number of phishing attacks has grown by 150% percent per year— with the Anti-Phishing Working Group (APWG) reporting an all-time high for phishing in 2022 , logging more than 4.7 million phishing sites.

Testing 82

Testing Measurement Behavioral Analytics Reporting 82

CIO Business Intelligence

NOVEMBER 29, 2023

Prepping for success By focusing on training and certifying learners in valuable, in-demand skills, Per Scholas aims to be a “pathway to a thriving wage,” says Wayne Wilson, director of business solutions at the nonprofit, who graduated from Per Scholas’ software engineering program in 2019 before going on to work for the organization.

IT 105

IT Software Technology Cost-Benefit 105

Octopai

JANUARY 25, 2021

The cost of data breaches in 2019 was 87% higher than in 2018 , with the number rising each year. With such sensitive information at risk, the federal government passed the Health Insurance Portability and Accountability Act (HIPAA). million Americans experiencing compromised personal data in 2019, compliance is key.

Insurance 52

Insurance Metadata Statistics Reporting 52

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. 4] Fairwashing: The Risk of Rationalization , How Can We Fool LIME and SHAP?

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

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. They can use AI and data-driven cybersecurity technology to address these risks. By 2012, there was a marginal increase, then the numbers rose steeply in 2014. In summary.

Testing 124

Testing Behavioral Analytics Data-driven Big Data 124

Smart Data Collective

JUNE 15, 2022

trillion in 2019? Statistics such as average time on page, bounce rate, conversion rate, and others may be used to perfect your website and make changes to make it more appealing to visitors. Retailers who want to prosper in the future months and even years can’t risk making choices without using data.

Advertising 98

Advertising Cost-Benefit ROI Sales 98

Smart Data Collective

JUNE 3, 2019

They show statistics that 2.5 Essentially, the lender is assessing the risk of giving you this requested money. This isn’t always a risk that a bank is willing to take on. Each lender has their own limitations when it comes to the risk that they are willing to take on. Equity Amount.

Big Data 73

Big Data Cost-Benefit Unstructured Data Risk 73

O'Reilly on Data

FEBRUARY 18, 2020

Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%. But sustained interest in cloud migrations—usage was up almost 10% in 2019, on top of 30% in 2018—gets at another important emerging trend. Still cloud-y, but with a possibility of migration.

Data-driven 335

Data-driven Software Statistics Marketing 335

FineReport

FEBRUARY 25, 2020

Traditional paper and pen registrations have the risk of contracting viruses with each other, and managers can’t view the entry and exit records in real time. 2019’s Best Excel Reporting Tool that Reaches Far beyond Excel. During this virus crisis, personnel access restrictions have been adopted in various areas. Supplies usage.

Data Collection 96

Data Collection IT Dashboards Reporting 96

Cloudera

SEPTEMBER 15, 2022

Mark: Yes, another concept gaining traction with data leaders is the data mesh, which was introduced by Zhamak Dehghani in 2019 as an approach to address the challenges when deploying data programs. Distribution monitors the statistical characteristics of the data resource, which is an excellent linkage with data quality. .

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

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. Those cutting-edge ideas are also attractive, both to managers who don’t understand the risks and to developers who want to try something that’s really challenging.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

MARCH 15, 2022

Synthetic data that looks like real data but isn’t allows software to be tested across the full gamut of use cases without putting real data at risk. “If For example, in 2019, Norway’s Labour and Welfare Administration created a synthetic version of its entire population. Organizations can do something similar by using synthetic data.

Strategy 145

Strategy Testing Modeling Sales 145

Domino Data Lab

JANUARY 24, 2019

Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the market. This group of solutions targets code-first data scientists who use statistical programming languages and spend their days in computational notebooks (e.g., Reflections. Code-first data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

Smart Data Collective

AUGUST 8, 2019

FireEye claims that email is the launchpad for more than 90 percent of cyber attacks, while a multitude of other statistics confirm that email is the preferred vector for criminals. That being said, people are increasingly aware of things like phishing attacks and most people know that email links and attachments could pose a risk.

Big Data 86

Big Data Data Processing Machine Learning Predictive Analytics 86

Smart Data Collective

DECEMBER 18, 2020

According to Infosec statistics , cyber-attacks resulting in over $1 million in reported losses has risen exponentially over the past five years – with over 100 cases reported in both of 2018 and 2019. Image: Infosec ). Be sure to caution employees about visiting hazardous websites while on the company’s server.

Analytics 84

Analytics Broadcasting Measurement Data Processing 84

FineReport

FEBRUARY 25, 2020

Traditional paper and pen registrations have the risk of contracting viruses with each other, and managers can’t view the entry and exit records in real time. 2019’s Best Excel Reporting Tool that Reaches Far beyond Excel. During this virus crisis, personnel access restrictions have been adopted in various areas. Supplies usage.

Data Collection 59

Data Collection IT Dashboards Reporting 59

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. ” The Atlantic – Workers Love AirPods Because Employers Stole Their Walls , Amanda Mull, April 2019. For example in 20 Risks that Beset Data Programmes. . [7].

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

O'Reilly on Data

MARCH 18, 2020

The new survey, which ran for a few weeks in December 2019, generated an enthusiastic 1,388 responses. This year, about 15% of respondent organizations are not doing anything with AI, down ~20% from our 2019 survey. It seems as if the experimental AI projects of 2019 have borne fruit. But what kind? Bottlenecks to AI adoption.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

CDW Research Hub

JUNE 5, 2019

Varonis compiled 60 cybersecurity statistics to give you a better idea of the current cybersecurity state, and we’ve broken out five key facts to help you rethink your data security program. Check out Varonis’ full list of 60 Must-Know Cybersecurity Statistics for 2019. Show Me the Money. Risky Business.

Statistics 72

Statistics Risk Management Finance Risk 72

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. In 2019, Netflix alone released 371 new TV shows and movies. and even set their risk tolerance.

Risk 67

Risk ROI Modeling Metrics 67

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. And we can keep repeating this approach, relying on intuition and luck.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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. A survey of data engineers conducted by DataKitchen in 2022 revealed some shocking statistics. Why has the company never addressed this kind of risk? Crisis happens, errors are inevitable.

Testing 176

Testing Risk Data Processing Statistics 176

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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. A survey of data engineers conducted by DataKitchen in 2022 revealed some shocking statistics. Why has the company never addressed this kind of risk? Crisis happens, errors are inevitable.

Testing 130

Testing Risk Data Processing Statistics 130

Jet Global

APRIL 27, 2023

Tax teams of multinational enterprises (MNEs) in the manufacturing industry face increasing challenges to manage business and market risks effectively. For your tax team to be agile, you’ll need to optimize tax technology and processes so you can both spot data insights and mitigate risk.

Manufacturing 52

Manufacturing Marketing Experimentation Reporting 52

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. It provides the occasion for deeper exploration of which inputs that can be influenced and which risks can be proactively managed. The alternative we use is the forecast triangulation framework described above.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

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. KPMG calculates a score for an employee’s risk of attrition, tries to identify a reason for that, and then suggests a remediation.

Consulting 145

Consulting Management Interactive Metadata 145

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. The probabilistic nature changes the risks and process required. They tend to use less machine learning, but more advanced statistical practices, since the outcomes (government policies, etc.) machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

O'Reilly on Data

MARCH 20, 2019

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. An attacker could use an adversarial example attack to grant themselves a large loan or a low insurance premium or to avoid denial of parole based on a high criminal risk score. O’Reilly Ideas (2019). DZone (2018).

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Domino Data Lab

MAY 8, 2019

That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Given how so much of IT gets driven by concerns about risks and costs, in practice auditability tops the list for many business stakeholders. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Sisense

JUNE 30, 2020

The primary objective of data visualization is to clearly communicate what the data says, help explain trends and statistics, and show patterns that would otherwise be impossible to see. Her debut novel, The Book of Jeremiah , was published in 2019.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics.

Statistics 27

Statistics Uncertainty Risk Marketing 27

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. In our case, it turns out that the monotonicity regularizer allows us to increase the number of knots without incurring much risk of overfitting there are fewer ways for the model to go wrong. linear regression, trees) can be too rigid in their functional forms.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Smart Data Collective

OCTOBER 14, 2019

In September 2019, Google decided to make it’s Differential Privacy Library available as an open-source tool. When Google talked about releasing this tool in its blog, the brand pointed out that if you don’t protect user data, you risk losing people’s trust. Kubernetes.

Data Science 68

Data Science Machine Learning Big Data Interactive 68

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). By November 2018, 43% reported that they planned to incorporate AutoML into their workflows sometime in 2019.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

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

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