David Menninger's Analyst Perspectives

JANUARY 24, 2023

It creates a need for decision makers to utilize technologies such as artificial intelligence and machine learning (AI/ML) to better understand the external factors that impact their business. However, manual modeling is a time-consuming process and results in a limited number of models and tests.

Forecasting 130

Forecasting Analytics Machine Learning Testing 130

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. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you. A more general approach is to learn a Generalized Additive Model (GAM).

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective. Our team does a lot of forecasting. It also owns Google’s internal time series forecasting platform described in an earlier blog post.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Corinium

JUNE 6, 2019

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. There is usually a steep learning curve in terms of “doing AI right”, which is invaluable. What is the most common mistake people make around data?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Smarten

JANUARY 24, 2019

What is Automated Machine Learning? With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. Take for example, the task of performing predictive analytics.

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

CIO Business Intelligence

JULY 5, 2022

It uses data mining, data modeling, and machine learning to answer “why” something happened and predict what might happen in the future. Predictive analytics is the use of techniques such as statistical modeling, forecasting, and machine learning to make predictions about future outcomes.

Business Analytics 131

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 131

CIO Business Intelligence

APRIL 9, 2024

Previously head of cybersecurity at Ingersoll-Rand, Melby started developing neural networks and machine learning models more than a decade ago. I was literally just waiting for commercial availability [of LLMs] but [services] like Azure Machine Learning made it so you could easily apply it to your data.

Digital Transformation 96

Digital Transformation Machine Learning Data Lake Software 96

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. In business, predictive analytics uses machine learning, business rules, and algorithms.

Data Analytics 133

Data Analytics Diagnostic Analytics Management Analytics 133

DataRobot Blog

AUGUST 18, 2022

Challenges in inventory management, demand forecasting, price optimization, and more can result in missed opportunities and lost revenue. Retailers and manufacturers that incorporate AI in supply chain management greatly enhance their ability to forecast demand, manage inventory, and optimize price. Application of AI in Supply Chain.

Manufacturing 98

Manufacturing Cost-Benefit Forecasting Data-driven 98

CIO Business Intelligence

DECEMBER 14, 2023

AI and machine learning (ML) can do this by automating the design cycle to improve efficiency and output; AI can analyze previous designs, generate novel design ideas, and test prototypes, assisting engineers with rapid, agile design practices.

Manufacturing 138

Manufacturing Cost-Benefit Unstructured Data Optimization 138

Smart Data Collective

JULY 9, 2023

Optimizing Conversion Rates with Data-Driven Strategies A/B Testing and Experimentation for Conversion Rate Optimization A/B testing is essential for discovering which version of your website’s elements are most effective in driving conversions.

Optimization 74

Optimization Data Analytics Analytics Data-driven 74

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. Before selecting a tool, you should first know your end goal – machine learning or deep learning.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

CIO Business Intelligence

JUNE 14, 2023

Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training. The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

bridgei2i

JULY 15, 2020

Companies will need to invest in accelerators powered by machine learning that will help gain insights into complex supply chain processes through KPI measurements. Are you curious about a New-Age Forecasting System that builds and improves your organizations’ ability to sense changes and disrupt the market? Read it Here.

Testing 52

Testing KPI Risk Management Measurement 52

Smarten

DECEMBER 3, 2023

‘Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

CIO Business Intelligence

JULY 18, 2023

It was when Nvidia reported strong results for the three months to April 30, 2023, and forecast that its sales could jump by 50% in the following fiscal quarter, that its stock market valuation soared, catapulting it into the exclusive trillion-dollar club alongside well-known tech giants Alphabet, Amazon, Apple, and Microsoft.

Manufacturing 98

Manufacturing Forecasting Software Marketing 98

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. What is the Holt-Winters Forecasting Algorithm? The Holt-Winters algorithm is used for forecasting and It is a time-series forecasting method. 2) Double Exponential Smoothing Use Case.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Cloudera

JANUARY 5, 2021

In today’s retail environment, retailers realize that building demand forecasts simply based upon historical transaction, promo, and pricing data alone is not good enough. Retail supply chains are a recognized and proven source of ROI when data analytics are leveraged to improve forecast accuracy and product availability.

Forecasting 91

Forecasting Cost-Benefit Sales Unstructured Data 91

CIO Business Intelligence

OCTOBER 3, 2023

However since then great strides have been made in machine learning and artificial intelligence. Another research company, Mordor Intelligence, is forecasting annual CAGR of 19.8 Process optimisation: processes are examined, re-engineered, standardised and carefully tested prior to being automated processes.

Cost-Benefit 115

Cost-Benefit Machine Learning Interactive Software 115

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Agreeing on metrics.

Marketing 361

Marketing Experimentation Metrics Testing 361

DataRobot

JUNE 29, 2021

Well, just imagine a production machine learning model that always stays accurate after it’s deployed—all by itself. Machine learning models trained on 2019 data didn’t know what to do. As part of the same process, it also generates and tests a whole host of new models and presents the top ones as recommended challengers.

Machine Learning 80

Machine Learning Data Processing Forecasting Modeling 80

AWS Big Data

FEBRUARY 1, 2023

Furthermore, it created further opportunities for our data scientists and engineers to use AI and machine learning (ML) services to continuously feed and analyze data. This will make launching and testing models simpler. Before the implementation of this system, one dataset took 1 month to onboard.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Smarten

MAY 31, 2022

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Forecasting. Hypothesis Testing. Trends and Patterns. Classification. Descriptive Statistics. Correlation. Regression. Clustering. Frequent Pattern Mining.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

DataRobot

JUNE 4, 2021

DataRobot enables organizations to leverage the transformational power of machine learning by delivering the world’s most trusted enterprise AI platform that spans the full lifecycle from data to value. Forecasting In-Store Foot Traffic. is good, we want to improve the overall accuracy of our machine learning model.

Forecasting 52

Forecasting Machine Learning Predictive Modeling Modeling 52

IBM Big Data Hub

APRIL 21, 2023

. “We’re in hills, so some areas need less water, and some areas need more,” said David Chapin, a farmer and IBMer in Lampasas, Texas, that has been helping IBM test water management solutions. New versions of the app and sensor are currently being tested.

Technology 87

Technology Testing Forecasting Machine Learning 87

CIO Business Intelligence

NOVEMBER 14, 2022

Decision intelligence seeks to update and reinvent decision support systems with a sophisticated mix of tools including artificial intelligence (AI) and machine learning (ML) to help automate decision-making. Forecasting models. These models are used for “what-if” analysis. Optimization analysis models.

Data mining 136

Data mining Data-driven Statistics OLAP 136

Jedox

SEPTEMBER 10, 2020

Reinventing for dynamic forecasting. Now, CFOs must go further with dynamic forecasting. For dynamic forecasting to work effectively, CFOs need a scenario and modeling platform that supports real-time data updates. Instead of only tracking to an outdated budget, driver-based scenario forecasts become a primary tool.

Forecasting 69

Forecasting Dashboards Measurement Risk 69

IBM Big Data Hub

APRIL 28, 2022

Problem : Traditionally, developing a solid backorder forecast model that takes every factor into consideration would take anywhere from weeks to months as sales data, inventory or lead-time data and supplier data would all reside in disparate data warehouses. How does a data fabric impact the bottom line?

Metadata 82

Metadata Data Warehouse Forecasting Predictive Modeling 82

Smarten

APRIL 10, 2023

By analyzing historical data and using it to test theories and to hypothesize, the business can determine the best alternative and better understand the outcome before it decides on a direction, thereby avoiding missteps.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Analytics Prescriptive Analytics 52

Smart Data Collective

FEBRUARY 9, 2022

Learn how DirectX visualization can improve your study and assessment of different trading instruments for maximum productivity and profitability. A growing number of traders are using increasingly sophisticated data mining and machine learning tools to develop a competitive edge. But first, What is DirectX Anyway?

Visualization 133

Visualization Optimization Analytics Testing 133

Smart Data Collective

SEPTEMBER 19, 2022

However, fintech businesses can use big data and machine learning to build fraud detection systems that uncover anomalies in real time. Forecasting Future Market Trends. Better UI/UX based on A/B testing. Fraud is a cause for concern in the banking industry, especially now that mobile banking takes a center stage.

Big Data 129

Big Data ROI Measurement Risk 129

Smart Data Collective

AUGUST 19, 2021

Product testing and progress. Through product testing and trialing, it can help properly access the product and ultimately, it’s chances of success when the product launches. Through product testing and trialing, it can help properly access the product and ultimately, it’s chances of success when the product launches.

Analytics 126

Analytics Cost-Benefit Software Testing 126

IBM Big Data Hub

NOVEMBER 29, 2023

Aggregates as predictive insights : Aggregates, which consolidate data from various sources across your business environment, can serve as valuable predictors for machine learning (ML) algorithms. Learn more about how you can build or enhance your own complete, composable enterprise-wide event-driven architecture.

Unstructured Data 88

Unstructured Data Data-driven ROI Machine Learning 88

IBM Big Data Hub

FEBRUARY 13, 2024

Like diligent students, these generative models soak up information and identify patterns, structures and relationships between data points, which is how they learn the grammar of poetry, artistic brushstrokes and musical melodies. Imagine each data point as a glowing orb placed on a vast, multi-dimensional landscape.

Enterprise 122

Enterprise Modeling Testing Data-driven 122

Jen Stirrup

FEBRUARY 24, 2024

In marketing, for example, analyzing customer data and detecting patterns allows firms to forecast demand, prevent churn, personalize pricing, and make other data-driven decisions. Ongoing bias testing is required (Forbes, 2023). Sales Forecasting algorithms help small businesses predict future sales trends based on historical data.

Cost-Benefit 71

Cost-Benefit Data-driven Testing Risk 71