CIO Business Intelligence

SEPTEMBER 6, 2023

Since ChatGPT’s release in November of 2022, there have been countless conversations on the impact of similar large language models. While the potential of Generative AI in software development is exciting, there are still risks and guardrails that need to be considered. To learn more, visit us here.

Software 119

Software Experimentation Risk Data Lake 119

CIO Business Intelligence

JUNE 28, 2023

These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As Belcorp operates under a direct sales model in 14 countries. That, in turn, led to a slew of manual processes to make descriptive analysis of the test results.

Digital Transformation 99

Digital Transformation Cost-Benefit Informatics Data mining 99

Cloudera

DECEMBER 3, 2021

Surely there are ways to comb through the data to minimise the risks from spiralling out of control. Systems should be designed with bias, causality and uncertainty in mind. For example, training an interview screening model using education data often contains gender information. Model Drift. System Design.

Uncertainty 97

Uncertainty Measurement Metrics Risk 97

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. Machine learning adds uncertainty. Models also become stale and outdated over time.

Management 332

Management Machine Learning Experimentation Metrics 332

Jedox

SEPTEMBER 3, 2020

The new normal introduced new risks from employee health and safety, supply chain stress and government mandates – all with working capital implications. The unprecedented uncertainty forced companies to make critical decisions within compressed time frames. This placed an acute spotlight on planning agility. Conclusion.

Uncertainty 81

Uncertainty Forecasting Digital Transformation Risk 81

DataKitchen

OCTOBER 2, 2023

Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions. A Data Journey supplies real-time statuses and alerts on start times, processing durations, test results, and infrastructure events, among other metrics. .’ What’s a Data Journey?

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

CIO Business Intelligence

JULY 31, 2023

As vendors add generative AI to their enterprise software offerings, and as employees test out the tech, CIOs must advise their colleagues on the pros and cons of gen AI’s use as well as the potential consequences of banning or limiting it. How has, say, ChatGPT hit your business model?” How is your business impacted by generative AI?

Strategy 98

Strategy Risk Enterprise Risk Management 98

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93

CIO Business Intelligence

JANUARY 11, 2023

New products and ideas are tested every day, just as new opportunities are ignored. Noteworthy companies like Airbnb, Uber, and Apple innovated through major technology breakthroughs, but innovation doesn’t have to be a completely new business model. Blockbuster thought going digital would be too expensive.

Enterprise 105

Enterprise Uncertainty Consulting Sales 105

CIO Business Intelligence

OCTOBER 18, 2023

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 140

Risk Manufacturing Enterprise Technology 140

DataRobot

JUNE 1, 2021

Before you put a model into production, you may first need to clear compliance hurdles. You should first identify potential compliance risks, with each additional step again tested against risks. Typically, these areas require the most attention: model development, implementation, and use.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. To facilitate risk modeling in this new normal, agility and flexibility is required. Data Variety. This will only become more important as we move into 2021 and a post-pandemic new normal.

Insurance 92

Insurance Digital Transformation Unstructured Data Machine Learning 92

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Domino Data Lab

MAY 15, 2019

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. This work includes model improvements as well as adding new signals and features into the model.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

CIO Business Intelligence

JULY 7, 2023

As an IT management framework, ITIL can help businesses manage risk, strengthen customer relations, establish cost-effective practices, and build a stable IT environment that allows for growth, scale, and change. You’ll be tested on a situation of your choosing, so the material will be personal to your experience.

Cost-Benefit 98

Cost-Benefit Strategy Management Uncertainty 98

Domino Data Lab

FEBRUARY 20, 2019

“The last company I worked for was a very interesting story as well, because I joined the company that had a very good established culture of software development…with tests, with CI/CD, experienced engineers, experienced engineering management, and product management. But not much experience in building data products.

Data Science 76

Data Science Testing Software Uncertainty 76

Jet Global

NOVEMBER 4, 2020

Intangible-asset transactions present a challenge when organizations are quantifying prices and profits to serve their transfer pricing models. Certain authorities may have different preferences or expectations when it comes to adjustments, even in a period of economic uncertainty.

Risk 98

Risk Uncertainty Sales Strategy 98

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. These examples are well covered by many others (e.g.,

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Cloudera

OCTOBER 21, 2020

Today’s models, norms, and averages are being re-written on the fly, with insurers forced to cope with the inevitable conflict between old standards and the new normal. . Along the way, tried and tested models and processes are proving unreliable, triggering an evolution in the insurance industry. Health data. Financial data.

Insurance 71

Insurance Unstructured Data Digital Transformation Cost-Benefit 71

Jet Global

SEPTEMBER 10, 2020

Living through periods of rapid upheaval and uncertainty, like the recent pandemic, forces us to adapt quickly to new working practices. Add to that the additional users and number of planning models you now create. One of the long-lasting lessons learned from COVID-19 is that the old way of planning doesn’t work anymore.

Forecasting 52

Forecasting Finance Uncertainty Sales 52

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Jet Global

APRIL 2, 2020

Exploring all these unknowns becomes significantly easier with scenario planning capabilities that allow companies to model conditions and forecast financial health based on changing customer behavior and how long the the economy takes to recover. Let us help you find a solution that fits your needs and works with your available resources.

Finance 64

Finance Forecasting Uncertainty Sales 64

Sisense

OCTOBER 6, 2020

Additionally, quantitative data forms the basis on which you can confidently infer, estimate, and project future performance, using techniques such as regression analysis, hypothesis testing, and Monte Carlo simulations.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

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. It is a big picture approach, worthy of your consideration.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

SEPTEMBER 19, 2023

How can enterprises attain these in the face of uncertainty? Rogers: This is one of two fundamental challenges of corporate innovation — managing innovation under high uncertainty and managing innovation far from the core — that I have studied in my work advising companies and try to tackle in my new book The Digital Transformation Roadmap.

Digital Transformation 130

Digital Transformation Uncertainty Testing Enterprise 130

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk.

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

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. If people need to go through multiple layers of approvals, they run the risk of building a very inefficient system. Tumultuous times redefine what constitutes success.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

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. I held out 20% of this as a test set and used the remainder for training and validation.

Risk 67

Risk ROI Modeling Metrics 67

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Cloudera

NOVEMBER 18, 2021

This allows for an omni-channel view of the customer and enables real-time data streaming and a safe zone to test machine learning models using Cloudera Data Science Workbench (CDSW). With such an agile response, customers can transact with minimal disruptions and get access to financial services, without putting employees at risk. .

Data Lake 74

Data Lake Cost-Benefit Digital Transformation Risk 74

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Jet Global

OCTOBER 21, 2020

The way we perceive business risk, and how we manage it, is fundamentally different for every finance leader on the planet. Even the most careful and diligent financial planning process is vulnerable, running the risk of being obsolete. In the past few months, planning has changed – and it has changed dramatically.

Forecasting 98

Forecasting Finance Business Driver Key Performance Indicator 98

Domino Data Lab

JUNE 23, 2019

As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. They lack probably what a lot of folks in this room have in terms of domain expertise around data, machine learning, and how these models work. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment.

Statistics 27

Statistics Uncertainty Risk Marketing 27

The Unofficial Google Data Science Blog

MAY 31, 2016

Similarly, we could test the effectiveness of a search ad compared to showing only organic search results. Structure of a geo experiment A typical geo experiment consists of two distinct time periods: pretest and test. After the test period finishes, the campaigns in the treatment group are reset to their original configurations.

Advertising 42

Advertising Testing Sales Statistics 42

CIO Business Intelligence

FEBRUARY 12, 2024

As genAI caught fire in 2023, many organizations rushed to test and learn from the technology and harness it to grow productivity and improve processes. 4 Additionally, while 63% have guardrails in place to use AI safely, these organizations worry about its role in misinformation, ethical bias and job loss among other risks, Wavestone found.

IT 130

IT Consulting Cost-Benefit Uncertainty 130