AWS Big Data

AUGUST 21, 2024

To address this requirement, Redshift Serverless launched the artificial intelligence (AI)-driven scaling and optimization feature, which scales the compute not only based on the queuing, but also factoring data volume and query complexity. The slider offers the following options: Optimized for cost – Prioritizes cost savings.

Optimization 108

Optimization Data Lake Data Warehouse Cost-Benefit 108

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. Machine learning applications rely on three main components: models, data, and compute.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

O'Reilly on Data

SEPTEMBER 19, 2023

They’d grown tired of learning what is; now they wanted to know what’s next. Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. It felt like, almost overnight, all of machine learning took on some kind of neural backend. And it was good.

Machine Learning 339

Machine Learning Testing Modeling Cost-Benefit 339

CIO Business Intelligence

FEBRUARY 6, 2025

In retail, they can personalize recommendations and optimize marketing campaigns. Even basic predictive modeling can be done with lightweight machine learning in Python or R. Training and running these models require massive computing power, leading to a significant carbon footprint. You get the picture.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Machine Learning and Predictive Modeling of Customer Churn. Building Your Churn Model. segmentation on steroids).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. In this article, we explore model governance, a function of ML Operations (MLOps). Machine Learning Model Lineage. Machine Learning Model Visibility .

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

CIO Business Intelligence

JANUARY 19, 2024

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

Cloudera

DECEMBER 4, 2024

Today, Artificial Intelligence (AI) and Machine Learning (ML) are more crucial than ever for organizations to turn data into a competitive advantage. To unlock the full potential of AI, however, businesses need to deploy models and AI applications at scale, in real-time, and with low latency and high throughput.

Metrics 73

Metrics Data Processing Machine Learning Deep Learning 73

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 139

Predictive Analytics Analytics Predictive Modeling Data mining 139

Rocket-Powered Data Science

FEBRUARY 12, 2021

This is accomplished by adding more data-driven, machine learning, and AI (artificial intelligence) components to the process discovery, process mining, and process learning stages. IA incorporates feedback, learning, improvement, and optimization in the automation loop.

ROI 234

ROI Digital Transformation Reporting Machine Learning 234

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Manufacturing: Predict the location and rate of machine failures.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

The Unofficial Google Data Science Blog

JANUARY 31, 2017

By OMKAR MURALIDHARAN, NIALL CARDIN, TODD PHILLIPS, AMIR NAJMI Given recent advances and interest in machine learning, those of us with traditional statistical training have had occasion to ponder the similarities and differences between the fields. Some branches of machine learning (e.g.

Machine Learning 74

Machine Learning Modeling Statistics Predictive Modeling 74

CIO Business Intelligence

MARCH 22, 2022

Nvidia is hoping to make it easier for CIOs building digital twins and machine learning models to secure enterprise computing, and even to speed the adoption of quantum computing with a range of new hardware and software. Nvidia claims it can do so up to 45,000 times faster than traditional numerical prediction models.

Modeling 144

Modeling Machine Learning Forecasting Optimization 144

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167

Analytics Machine Learning Data Science Data Collection 167

CIO Business Intelligence

JULY 5, 2022

Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. Business analytics also involves data mining, statistical analysis, predictive modeling, and the like, but is focused on driving better business decisions.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. Another way of saying this is: given some desired optimal outcome Y, what conditions X should we put in place.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Statistics 157

Smarten

JUNE 20, 2023

Citizen Data Scientists Can Use Assisted Predictive Modeling to Create, Share and Collaborate! Gartner has predicted that, ‘40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

Predictive Modeling 52

Predictive Modeling Modeling Forecasting Data Science 52

CIO Business Intelligence

DECEMBER 19, 2024

In especially high demand are IT pros with software development, data science and machine learning skills. IT professionals with expertise in cloud architecture and optimization are needed to ensure these systems are scalable, efficient, and capable of real-time environmental monitoring, Breckenridge says.

IT 52

IT IoT Machine Learning Optimization 52

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. The exam consists of 40 questions and the candidate has 120 minutes to complete it.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

datapine

AUGUST 14, 2019

Big companies that utilize R in their analytics operations, such as Google, Facebook, and LinkedIn , usually are finance and analytics-driven, as R has proved to be the top mechanism for data analysis, statistics, and machine learning. Learning MATLAB is a great bonus for those who want to pursue a career in (academic) research.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

OCTOBER 2, 2024

Cities are embracing smart city initiatives to address these challenges, leveraging the Internet of Things (IoT) as the cornerstone for data-driven decision making and optimized urban operations. Advanced analytics platforms, leveraging machine learning (ML) algorithms and AI, extract meaningful insights from this data.

IoT 123

IoT Internet of Things Predictive Modeling Data-driven 123

DataRobot

AUGUST 15, 2019

To really know their customers, Pepper Spain relies on data science and predictive modeling, but without a big data science team, they turned to DataRobot’s automated machine learning solution:

Machine Learning 9

Machine Learning Finance Optimization Predictive Modeling 9

BizAcuity

APRIL 1, 2023

1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. Predictive Analytics can help businesses in reducing risk (eg.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. How Machine Learning Helps Detect and Prevent AML. Predictive Analytics can help businesses in reducing risk (eg.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Decision Management Solutions

DECEMBER 8, 2020

Enterprises today are eager to apply machine learning to improve their operations. But how do they ensure that it truly serves their business operations in the most optimal way? Machine learning can improve operations, but only when its predictive models are deployed, integrated, and—most importantly—acted upon.

Machine Learning 52

Machine Learning Data mining Predictive Modeling Data-driven 52

Smart Data Collective

MAY 17, 2021

Big data solutions are often created and supported using various technologies from IIoT to machine learning and AI. All that performance data can be fed into a machine learning tool specifically designed to identify certain events, failures or obstacles. It also introduces operational efficiencies.

Big Data 132

Big Data Cost-Benefit IoT Machine Learning 132

DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions. What Is Decision Intelligence?

Machine Learning 98

Machine Learning Manufacturing Predictive Modeling Optimization 98

datapine

DECEMBER 4, 2019

Moreover, as most predictive analytics capabilities available today are in their infancy — they have simply not been used for long enough by enough companies on enough sources of data – so the material to build predictive models on was quite scarce. Last but not least, there is the human factor again.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

Smarten

JANUARY 24, 2019

What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Examples include credit card fraud monitoring solutions used by banks, or tools used to optimize the placement of wind turbines in wind farms. What is data science?

Data Science 140

Data Science Statistics Machine Learning Visualization 140

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

Data Processing 111

Data Processing Data Lake Data Warehouse Optimization 111

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. Many stock market transactions use ML.

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

datapine

JANUARY 31, 2022

This benefit goes directly in hand with the fact that analytics provide businesses with technologies to spot trends and patterns that will lead to the optimization of resources and processes. As mentioned above, one of the great benefits of business intelligence and analytics is the ability to make informed data-based decisions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

In tech speak, this means the semantic layer is optimized for the intended audience. Predictive analytics applies machine learning to statistical modeling and historical data to make predictions about future outcomes. Predictive AI will shortly be a common feature of dedicated business planning software.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130