CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. You should also have experience with pattern detection, experimentation in business optimization techniques, and time-series forecasting.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 363

Marketing Experimentation Metrics Testing 363

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. A free plan allows experimentation. On premises or in SAP cloud.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. 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. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 95

Experimentation Statistics Testing Knowledge Discovery 95

CIO Business Intelligence

JULY 31, 2024

For teams that want to boil down their own data into predictive tools, Model Builder will turn all those records of past purchases sitting in the data lake into a big statistical hair ball of tendencies that passes for an AI these days. Salesforce is pushing the idea that Einstein 1 is a vehicle for experimentation and iteration.

Data Lake 119

Data Lake IT Sales Experimentation 119

CIO Business Intelligence

SEPTEMBER 30, 2024

Once we get more data from across a couple of areas into Mquiry, I would love to see the insights it might show us and do some training against that data.

Data Quality 116

Data Quality Experimentation Insurance Statistics 116

CIO Business Intelligence

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Business Over Broadway

AUGUST 4, 2020

Experimentation and iteration to improve existing ML models (39%). In prior research, I found that data professionals who self-identified as Researchers have a strong math/statistics/research skill set. The entire list of activities (shown in Figure 1) were: Analyze and understand data to influence product or business decisions (63%).

Machine Learning 145

Machine Learning Data Science Statistics Experimentation 145

Data Science 101

JANUARY 15, 2020

Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV. Bias can cause a huge error in experimentation results so we need to avoid them. Statistics Essential for Dummies by D. REFERENCES. McCabe & B.

Experimentation 96

Experimentation Statistics Measurement Testing 96

Occam's Razor

MAY 22, 2006

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers. Counter claims?

Experimentation 103

Experimentation Testing Optimization Measurement 103

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. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

Management 339

Management Machine Learning Experimentation Metrics 339

CIO Business Intelligence

JANUARY 2, 2024

He plans to scale his company’s experimental generative AI initiatives “and evolve into an AI-native enterprise” in 2024. But at the end of the day, it boils down to statistics. Statistics can be very misleading. That’s the case for Yi Zhou, CTO and CIO with Adaptive Biotechnologies.

IT 144

IT Cost-Benefit Statistics Consulting 144

IBM Big Data Hub

MAY 20, 2024

As algorithm discovery and development matures and we expand our focus to real-world applications, commercial entities, too, are shifting from experimental proof-of-concepts toward utility-scale prototypes that will be integrated into their workflows.

Data Processing 94

Data Processing Optimization Experimentation Enterprise 94

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). They cannot process language inputs generally. Examples: (1) Automated manufacturing assembly line. (2) 4) Prosthetics.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

FineReport

DECEMBER 11, 2019

. – Head First Data Analysis: A learner’s guide to big numbers, statistics, and good decisions. The big news is that we no longer need to be proficient in math or statistics, or even rely on expensive modeling software to analyze customers. By Michael Milton. – Data Divination: Big Data Strategies.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

DataRobot Blog

JANUARY 17, 2023

Not actually being a machine learning problem: Value-at-Risk modeling is the classic example here—VaR isn’t a prediction of anything, it’s a statistical summation of simulation results. As discussed, we massively accelerate that process of experimentation.

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

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

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. Continuous pipeline monitoring with SPC (statistical process control). What DataOps best practices put you on track to achieving this ideal? Let’s take a look. Results (i.e.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

CIO Business Intelligence

JUNE 11, 2024

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications.

IT 136

IT Digital Transformation Broadcasting Business Objectives 136

CIO Business Intelligence

MARCH 21, 2022

According to William Chen, Data Science Manager at Quora , the top five skills for data scientists include a mix of hard and soft skills: Programming: The “most fundamental of a data scientist’s skill set,” programming improves your statistics skills, helps you “analyze large datasets,” and gives you the ability to create your own tools, Chen says.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

Business Over Broadway

FEBRUARY 21, 2021

As such, data science requires three broad skill sets , including subject matter expertise, statistics/math and technology/programming. Experimentation and iteration to improve existing ML models (25%). The practice of data science is about extracting value from data to help inform decision making and improve algorithms.

Machine Learning 60

Machine Learning Data Science Statistics Experimentation 60

CIO Business Intelligence

JUNE 28, 2023

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 101

Digital Transformation Cost-Benefit Informatics Data mining 101

DataRobot

JANUARY 13, 2022

Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. Most data scientists are strong in one or two of these areas, but not all three.

ROI 52

ROI Machine Learning Experimentation Data Science 52

DataRobot Blog

JULY 28, 2022

Initially, the customer tried modeling using statistical methods to create typical features, such as moving averages, but the model metrics (R-square) was only 0.5 The first baseline model we created used spectrograms of speech waveform data, statistical features, and spectrogram images. This approach got us to an R-squared of 0.7,

Data Science 72

Data Science Machine Learning Statistics Modeling 72

DataRobot Blog

OCTOBER 27, 2022

You might think that overall, the model’s features drifted relatively little in production, but in reality, the model’s drift statistics might be fluctuating quite a bit up and down. Prior to using DataRobot, the customer was conducting tedious experimentation to track and investigate drift patterns.

Data Science 52

Data Science Experimentation Visualization Data-driven 52

IBM Big Data Hub

MAY 17, 2024

” Given the statistics—82% of surveyed respondents in a 2023 Statista study cited managing cloud spend as a significant challenge—it’s a legitimate concern. Teams are comfortable with experimentation and skilled in using data to inform business decisions.

Modeling 96

Modeling Cost-Benefit Optimization Digital Transformation 96

CIO Business Intelligence

AUGUST 21, 2024

The flashpoint moment is that rather than being based on rules, statistics, and thresholds, now these systems are being imbued with the power of deep learning and deep reinforcement learning brought about by neural networks,” Mattmann says. But multiagent AI systems are still in the experimental stages, or used in very limited ways.

Risk 136

Risk Insurance Cost-Benefit Software 136

The Unofficial Google Data Science Blog

APRIL 16, 2019

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime. But these are not usually amenable to A/B experimentation.

Experimentation 68

Experimentation Sales Metrics Measurement 68

Ontotext

FEBRUARY 14, 2024

As a statistical model, LLM inherently is random. Experimentation is important, but be explicit when you do. So, we’ve learned our lesson. AI will solve it We’ve seen a massive increase in interest in LLMs and ‘AI’ But LLM without guide rails could lead to unbridled hallucinations. Start with “why?”

Recreation/Entertainment 105

Recreation/Entertainment Data Integration Modeling Data Quality 105

Jet Global

APRIL 27, 2023

Understand Your Research and Development Manufacturing accounted for 58 percent of US domestic research and development (R&D) spending in 2019, according to the  National Center for Science and Engineering Statistics. That  That means tax law changes to R&D investment are a major concern in the industry.

Manufacturing 52

Manufacturing Marketing Reporting Experimentation 52

Octopai

MAY 2, 2022

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. Issue detected?

Manufacturing 98

Manufacturing Testing Experimentation Data Quality 98

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant.

Experimentation 40

Experimentation Statistics Metrics Measurement 40

Sisense

JANUARY 21, 2020

This is an example of Simpon’s paradox , a statistical phenomenon in which a trend that is present when data is put into groups reverses or disappears when the data is combined. It’s time to introduce a new statistical term. So how do we get totally different results when breaking the data down by gender? See Kievit, Rogier, et al. ).

Testing 104

Testing Risk Data-driven Statistics 104

Data Science and Beyond

JULY 22, 2018

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. Like other authors, they argue that causal inference has been neglected by traditional statistics and some scientific disciplines. In a recent article , Hernán et al.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Paul DeBeasi

JANUARY 30, 2019

Machine learning projects are inherently different from traditional IT projects in that they are significantly more heuristic and experimental, requiring skills spanning multiple domains, including statistical analysis, data analysis and application development.

Machine Learning 56

Machine Learning IoT Experimentation Statistics 56

AWS Big Data

JULY 8, 2024

In every Apache Flink release, there are exciting new experimental features. You can find valuable statistics you can’t normally find elsewhere, including the Apache Flink Dashboard. However, in this post, we are going to focus on the features most accessible to the user with this release.

Management 98

Management Consulting Snapshot Dashboards 98

Occam's Razor

MARCH 23, 2021

This is very hard to do, we now have a proven seven-step experimentation process, with one of the coolest algorithms to pick matched-markets (normally the kiss of death of any large-scale geo experiment). What does the diminishing returns curve look like for TV GRPs for our company? More shouting is not really better – and it is expensive!

Analytics 133

Analytics Scorecard Strategy Testing 133