Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. their customer insights, connected products, risk mitigation). Mitigate risk to Cloudera’s business – for example in the area of Cybersecurity, and to ensure compliance with regulatory and consumer privacy policies and concerns.

Data-driven 44

Data-driven Data Quality Risk Interactive 44

bridgei2i

FEBRUARY 21, 2019

Traditional algorithmic solutions around structured data have gained and continue to gain traction. Matt Hellman a Transformation Leader at Microsoft writes in a September 2018 article titled, “How AI is transforming sales and marketing” in The Marketing Journal. Voice data quality). Examples of AI Solutions Usage.

Sales 40

Sales Structured Data Forecasting Enterprise 40

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. We’re not encouraging skepticism or fear, but companies should start AI products with a clear understanding of the risks, especially those risks that are specific to AI.

Enterprise 281

Enterprise Modeling Testing Reporting 281

Domino Data Lab

JULY 22, 2019

It’s also a driver for data science. The year 2018 was what Wall Street Journal called “ a global reckoning on data governance.” ” If you don’t know, there were hundreds of millions of people affected worldwide during 2018 with security breaches and then data privacy leakage.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. While compliance is not the No.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Alation

MARCH 21, 2023

Data security The travel industry collects, transmits, processes, and stores a wide range of personally identifiable information (PII) from customers, which are of interest to bad actors, as cybercriminals target this valuable data. Otherwise, they risk a data privacy violation.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Peter James Thomas

AUGUST 12, 2018

Let’s cover what can go wrong (note: this section is not intended to be exhaustive, links are provided to more in-depth articles where appropriate): Accuracy of Data that is captured. A number of factors can play into the accuracy of data capture. Honesty of Data that is captured. How to Measure the Unmeasurable.

Metrics 49

Metrics Statistics Data Quality Measurement 49

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? The ability to measure results (risk-reducing evidence).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Octopai

JANUARY 19, 2021

Whether your organization is using on-prem or cloud-based systems, or a combination of the two – Octopai’s enterprise-scale cloud-based BI Intelligence platform allows BI teams to speed analytics projects, achieve greater agility, and reduce risk.

Metadata 52

Metadata ROI Optimization Data Quality 52

Cloudera

JANUARY 22, 2019

Cloudera enables high-value analytical use cases from the edge to AI including proactive and predictive maintenance, usage-based analytics for targeted communications, recommendation engines, Enterprise Risk Management, AML (Anti-Money Laundering), Fraud Detection/Prevention, Cybersecurity, and Machine Models.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Domino Data Lab

MARCH 3, 2019

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 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

CIO Business Intelligence

MAY 30, 2024

Most recently, she has served as EVP and chief customer and technology officer at Ameren, which she joined 2018 as SVP and chief digital and information officer before adding customer experience and operations in 2023. Talk to us about how leaders should be thinking about the role of data quality in terms of their AI deployments.

Data Quality 87

Data Quality Key Performance Indicator Digital Transformation Management 87

Alation

APRIL 12, 2022

Two decades on, the role has expanded to include responsibility for analytics, and even data monetization. Between 2010 and 2018 the number of CDOs present in Fortune 1500 companies increased nearly 8-fold. Today, the modern CDO drives the data strategy for the entire organization. Improving Data Quality.

Data Quality 52

Data Quality Data Governance Metrics Data Strategy 52

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Peter James Thomas

AUGUST 30, 2018

The phrase came to mind for me today when coming across the following exhibit: © Business Over Broadway (2018). Based on Kaggle’s State of Data Science Survey 2017 (Sample size: 10,153). Did not instrument data useful for scientific analysis and decision-making. I prefer not to say. Follow @peterjthomas.

Data Science 75

Data Science Data Quality Machine Learning Business Intelligence 75