O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. 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. Machine learning adds uncertainty.

Management 333

Management Machine Learning Experimentation Metrics 333

CIO Business Intelligence

JULY 11, 2023

Winning with AI: Be mission driven and context aware A good way to test this sort of thinking is to assess whether an application of AI would be comparably valuable in a company that’s made similar decisions about how to win (and less in the opposite case). I can be inspired by that. Artificial Intelligence, Machine Learning

Strategy 75

Strategy Uncertainty Data-driven Consulting 75

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. In this session we explored what firms are doing to approach the uncertainty with more predictability. Pandemic “Pressure” Testing. ML and AI can react quickly and handle mass amounts of data to give leading indicators.

Risk 102

Risk Optimization Management Insurance 102

Smart Data Collective

FEBRUARY 23, 2022

How can your company benefit by adapting to an IoT-driven model? Here are some benefits of adapting to a new business model in an era driven by the IoT. Test your leadership’s ability to handle working in a new environment shaped by the IoT. Business managers should consider change as a test.

IoT 112

IoT Internet of Things Data-driven Uncertainty 112

CIO Business Intelligence

JUNE 28, 2022

Some call data the new oil. Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 138

Management Internet of Things Statistics Data-driven 138

Smart Data Collective

SEPTEMBER 30, 2022

The landscape of blockchain-driven solutions: from 2018 to 2022. In 2018-2019, budding blockchain-based advertising projects provided the first opportunity to buy clean and secure traffic, enriched with genuine data about ad campaign performance. This way, all data becomes auditable to every chain participant on an event-level basis.

Advertising 137

Advertising Marketing Technology Uncertainty 137

CIO Business Intelligence

JULY 31, 2023

To allow or not According to various news reports, some big-name companies initially blocked generative AI tools such as ChatGPT for various reasons, including concerns about protecting proprietary data. 1 question now is to allow or not allow,” says Mir Kashifuddin, data risk and privacy leader with the professional services firm PwC US.

Strategy 98

Strategy Risk Enterprise Risk Management 98

Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. Almost every modern organization is now a data-generating machine. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

JULY 31, 2023

Banks have the most to gain if they succeed (and the most to lose if they fail) at bringing their mainframe application and data estates up to modern standards of cloud-like flexibility, agility and innovation to meet customer demand. Couldn’t execs have run better analyses to spot risks within the data?

Digital Transformation 50

Digital Transformation Uncertainty Risk Data Warehouse 50

Insight

MAY 15, 2020

However, recent hiring trends show that many tech companies are still actively hiring, especially for data-driven roles! In this time of terrifying uncertainty, some might focus on their own career journey over others. Are you hiring in data science, AI, or engineering? As unemployment in the U.S.

Uncertainty 76

Uncertainty Data Science Statistics Marketing 76

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Probability, Uncertainty and Quantitative Risk (2017) 2:6. Dr. Richard L.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Sisense

JUNE 24, 2020

Time to make your data work for you. In Hacking the Analytic App Economy , we show you how to build a data monetization strategy that leverages your company’s data to open new revenue opportunities, drive value, and help you thrive in the new era of analytic apps. Is your analytic app a product or service?

Analytics 52

Analytics Cost-Benefit Consulting Strategy 52

bridgei2i

MAY 18, 2020

The current COVID-19 pandemic has spread waves of uncertainty across businesses and their customer base. Prior to the COVID-19 crisis, several B2B companies were on spiraling inward journeys to transform the way they engaged with customers by using data and technology to realign organization structures and acquire new skills.

B2B 52

B2B Sales ROI Marketing 52

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Jet Global

DECEMBER 10, 2020

To implement AI, you need four main resources: an algorithm, at least 15 years of data, massive amounts of data over that time period, and a way to test the algorithm and get feedback on its accuracy. It’s part of a mixed bag of tools that we use for data collection, tracking, reporting, and analysis.

Uncertainty 52

Uncertainty Technology Finance Business Intelligence 52

The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. The data showed us that metrics are not exactly straight-line functions of parameters.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

JUNE 8, 2022

Digital disruption, global pandemic, geopolitical crises, economic uncertainty — volatility has thrown into question time-honored beliefs about how best to lead IT. Thriving amid uncertainty means staying flexible, he argues. . The coming months are a leadership test for CIOs, and it’s a pass/fail grade.”. Keep calm and lead on.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

O'Reilly on Data

OCTOBER 13, 2020

In Bringing an AI Product to Market , we distinguished the debugging phase of product development from pre-deployment evaluation and testing. From a technical perspective, it is entirely possible for ML systems to function on wildly different data. Debugging AI Products. Proper AI product monitoring is essential to this outcome.

Management 244

Management Metrics Machine Learning Modeling 244

CIO Business Intelligence

MAY 6, 2022

Work began in late 2020 on the service, which enables customers to connect through a live video/audio session to a United agent who can, in times of traveler uncertainty and stress, make new reservations on-the-fly, assuage worries about gate changes, and even upgrade the passenger’s seating on their next flight.

Uncertainty 98

Uncertainty Testing Digital Transformation Metadata 98

Cloudera

NOVEMBER 18, 2021

With so many impactful and innovative projects being carried out by our customers using the Cloudera platform, selecting the winners of our annual Data Impact Awards (DIA) is never an easy task. So, without further ado, it is with great delight that we officially publish the 2021 Data Impact Award winners! Data Lifecycle Connection.

Data Lake 80

Data Lake Cost-Benefit Digital Transformation Risk 80

Jet Global

OCTOBER 21, 2020

Financial planning and analysis are usually categorised by a multitude of data sources, slow manual processes, and long planning cycles, which are out of step with the speed of the business. During periods of uncertainty, this helps us plan for – and be ready to respond to – different outcomes. A new world of data possibilities.

Forecasting 98

Forecasting Finance Business Driver Key Performance Indicator 98

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. But looking through the blogosphere, some go further and posit that “platformization” of forecasting and “forecasting as a service” can turn anyone into a data scientist at the push of a button.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Jet Global

MAY 18, 2020

In the last few months, this level of thinking has been tested more than ever before. It now includes data scientists and strategists, alongside the traditional controllers and accountants, meaning there are many more people looking at numbers. Humans are very visually driven, especially in this digitallyled age. A New Look.

Finance 64

Finance Reporting Uncertainty Testing 64

DataRobot Blog

OCTOBER 4, 2022

The shift in consumer habits and geopolitical crises have rendered data patterns collected pre-COVID obsolete. This has prompted AI/ML model owners to retrain their legacy models using data from the post-COVID era, while adapting to continually fluctuating market trends and thinking creatively about forecasting.

Forecasting 59

Forecasting Sales Data-driven Modeling 59

Occam's Razor

JULY 12, 2010

I want to constantly be in the know of new and more clever ways of working with data, tools that are often solutions to problems we don't know we have yet or tools that are sometimes seeking problems to solve!! Well not crap… lots of data that no one cared about or actioned. More desire to be data driven.

Analytics 96

Analytics Measurement Metrics KPI 96

Domino Data Lab

JUNE 23, 2019

Skomoroch advocates that organizations consider installing product leaders with data expertise and ML-oriented intuition (i.e., Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. A few highlights from the session include.

Management 110

Management Machine Learning Experimentation Metrics 110

Andrew White

MARCH 6, 2021

First it is hard to collect such data. Second such data might be hard to understand and compare across countries and regions. January’s jobs data was revised upwards too. We have hypothesis and we test them. Sometimes a model seems to fit data from the past and all hail, we have a new theory to apply to the future.

Marketing 52

Marketing Forecasting Uncertainty Strategy 52

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

by NIALL CARDIN, OMKAR MURALIDHARAN, and AMIR NAJMI When working with complex systems or phenomena, the data scientist must often operate with incomplete and provisional understanding, even as she works to advance the state of knowledge. There has been debate as to whether the term “data science” is necessary. Some don’t see the point.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

datapine

DECEMBER 28, 2021

With the rise of advanced technology and globalized operations, statistical analyses grant businesses an insight into solving the extreme uncertainties of the market. Statistics are infamous for their ability and potential to exist as misleading and bad data. Exclusive Bonus Content: Download Our Free Data Integrity Checklist.

Statistics 363

Statistics Advertising Visualization Data mining 363