Smarten

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models. Insight Prescriptions goes beyond this process to recommend optimal actions that will help the business to achieve specific goals.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

CIO Business Intelligence

MARCH 22, 2022

Two groups of researchers are already using Nvidia’s Modulus AI framework for developing physics machine learning models and its Omniverse 3D virtual world simulation platform to forecast the weather with greater confidence and speed, and to optimize the design of wind farms. Accelerated learning.

Modeling 138

Modeling Machine Learning Forecasting Optimization 138

CIO Business Intelligence

OCTOBER 5, 2023

CBRE has also used AI to optimize portfolios for several clients, and recently launched a self-service generative AI product that enables employees to interact with CBRE and external data in a conversational manner. For AI, the high-value quadrant is where you’ll find most predictive modeling.

Experimentation 129

Experimentation Strategy Machine Learning Interactive 129

CIO Business Intelligence

OCTOBER 4, 2022

They identified two architectural elements for processing and delivering data: the “data platform,” which covers the sourcing, ingestion, and storage of data sets, and the “machine learning (ML) system,” which trains and productizes predictive models using input data. Putting data in the hands of the people that need it.

Machine Learning 114

Machine Learning Data Architecture Uncertainty Data-driven 114

Smarten

JUNE 8, 2022

‘Citizen Data Scientists can create new models, share models and collaborate, thereby improving business results and data literacy.’. In this article, we provide some examples of what a Citizen Data Scientist can do to advance the goals and interests of the organization and optimize their productivity and performance.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Optimization 52

Smarten

JUNE 10, 2022

Social BI Tools that allow for sharing of data, alerts, dashboards and interactivity to support decisions, enable online communication and collaboration. Predictive Modeling to support business needs, forecast, and test theories. Assisted Predictive Modeling. Business Intelligence. Dashboards. Cross-Tab Reporting.

Slice and Dice 52

Slice and Dice Analytics Key Performance Indicator Business Intelligence 52

FineReport

APRIL 9, 2024

Optimized Operational Efficiency: These tools streamline processes and resource allocation, leading to cost savings and improved resource utilization. Through real-time data analysis and predictive insights, clinicians can tailor treatment approaches to individual patient requirements, fostering a personalized approach to care delivery.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

CIO Business Intelligence

APRIL 22, 2022

Examples include credit card fraud monitoring solutions used by banks, or tools used to optimize the placement of wind turbines in wind farms. RapidMiner: This data science platform is geared to support teams, with support for data prep, machine learning, and predictive model deployment. Data science processes and methodologies.

Data Science 139

Data Science Statistics Machine Learning Visualization 139

Sisense

JANUARY 26, 2020

The process of producing goods is an enormous opportunity for data optimization. Because the steps are repeated so many times through the process, a small edge created via predictive analytics in manufacturing will be magnified at every repetition to produce significant benefit. Improve forecasts and maximize revenue.

Predictive Analytics 78

Predictive Analytics Manufacturing Analytics Forecasting 78

Business Over Broadway

SEPTEMBER 27, 2018

Figure 1 includes a good illustration of different data sets and how they fall along these two size-related dimensions (For the interested reader, check out the figure in an interactive graphic ). Machine Learning and Predictive Modeling of Customer Churn. segmentation on steroids).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

bridgei2i

DECEMBER 15, 2021

With significant adoption among industries as well as personal lives, AI is impacting enterprise transformation at scale, whilst changing the way humans interact with machines. Anticipating Demand through Predictive Modelling on OTT. Artificial Intelligence (AI) has reached a state of pervasiveness in everyday life.

Recreation/Entertainment 52

Recreation/Entertainment Metadata Advertising Predictive Modeling 52

O'Reilly on Data

MARCH 23, 2021

Content creators and content consumers are connected, share information, and develop mental models of the world, along with shared or distinct realities, based on the information they consume. Online spaces are novel forms of community: people who haven’t met and may never meet in real life interacting in cyberspace.

Internet Publishing and Broadcasting 317

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 317

Smarten

APRIL 2, 2019

Advanced analytics is the logical tool to help a business optimize its investments and achieve its goals. But, when an organization is ready to consider the implementation of an Advanced Analytics solution, it is difficult to know what it needs to ensure that it can satisfy current and future requirements and ensure user adoption.

Analytics 40

Analytics Predictive Modeling Visualization Cost-Benefit 40

Smarten

JANUARY 31, 2019

Today’s Advanced Analytics Tools allow business users to leverage features like self-serve data preparation, smart data visualization and assisted predictive modeling. Advanced Analytics is the logical tool to help a business optimize its investments and achieve its goals.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

O'Reilly on Data

JUNE 18, 2019

For example, a complex sophisticated model for finding duplicates or matching schema is the least of our worries if we cannot even enumerate all possible pairs that need to be checked. Data programming. An important paradigm for solving both these problems is the concept of data programming.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. They are used in everything from robotics to tools that reason and interact with humans. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model.

Risk 73

Risk Modeling Management Metadata 73

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal. Computer Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

AWS Big Data

MARCH 7, 2023

They should also provide optimal performance with low or no tuning. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. The focus is on the ease of consumption and integration with consuming services.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

datapine

AUGUST 14, 2019

In fact, MySQL Workbench is a visual tool that provides “data modeling, SQL development, and administration tools for server configuration, backup, and much more,” according to the product listing at the MySQL website. It offers many statistics and machine learning functionalities such as predictive models for future forecasting.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. This approach does demand skills, data curation, and significant funding, but it will serve the market for third-party, specialized models. This technology can be a valuable tool to automate functions and to generate ideas.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

DataRobot Blog

NOVEMBER 9, 2017

I’ve spent the last 2+ years working with business analysts and MBA’s to build predictive models. You could: Change the way your company handles sales prospects by ranking them with a machine learning model. Enhance the way people interact with your product by adding voice assistance. You’ve got to start somewhere.

Machine Learning 52

Machine Learning Data-driven Software Sales 52

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. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

O'Reilly on Data

SEPTEMBER 19, 2023

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.”

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

CIO Business Intelligence

MAY 10, 2022

Gartner defines a CDP as “a marketing technology that unifies a company’s customer data from marketing and other channels to enable customer modeling and to optimize the timing and targeting of messages and offers.”. It requires SQL for optimal use, so is best suited for data engineers and analysts. Bloomreach Engagement.

Advertising 118

Advertising Interactive Marketing Data Integration 118

IBM Big Data Hub

DECEMBER 20, 2023

Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available.

Machine Learning 77

Machine Learning Modeling Deep Learning Predictive Modeling 77

CIO Business Intelligence

AUGUST 15, 2023

The scalable avatar can have hundreds of thousands of conversations individually and simultaneously, and is highly customizable and interactive in real-time, thereby providing an immersive experience for each user. For example, it can learn and use students’ names and provide personalized information.

IT 98

IT Manufacturing IoT Cost-Benefit 98

Domino Data Lab

NOVEMBER 17, 2020

Predictive models fit to noise approach 100% accuracy. For example, it’s impossible to know if your predictive model is accurate because it is fitting important variables or noise. Understanding the meaning and interactions of 500 coefficients is not possible. Pairwise distances between points become the same.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

Cloudera

NOVEMBER 2, 2020

the time it takes for the data to be optimally queryable is faster – query immediately upon arrival with no need for processing or aggregation or compaction. the time it takes for the data to be optimally queryable is faster – query immediately upon arrival with no need for processing or aggregation or compaction.

Data Warehouse 91

Data Warehouse Optimization Dashboards Interactive 91

AWS Big Data

JANUARY 25, 2023

An Amazon Personalize job predicts for each line of input data (restaurants and restaurant articles) and produces ML-generated recommendations in the designated S3 output folder. The recommendation records are surfaced using interaction data, product data, and predictive models.

Visualization 78

Visualization Interactive Modeling Machine Learning 78

FineReport

APRIL 24, 2024

Interactivity: Incorporating interactive features allows users to explore the data more deeply, gaining comprehensive insights from the visualizations. Moreover, interactive features in data visualization tools allow users to delve deeper into the data, exploring specific data points or segments with ease.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

Cloudera

NOVEMBER 18, 2020

OVO UnCover enables access to real-time customer data using advanced, intelligent data analytics and machine learning to personalize the customer product interaction experience. To optimize investments, effectively bundle product offerings, and deliver contextual campaigns, Globe Telecom created a new analytical environment.

Internet Publishing and Broadcasting 118

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 118

DataRobot Blog

JANUARY 10, 2023

By predicting which patients are at risk of readmission before they are discharged, doctors can follow appropriate medical procedures to prevent readmission, optimize costs, and enhance the quality of treatment. Built-in Code Snippets and Interactive Visualizations to Accelerate Experimentation.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

The Unofficial Google Data Science Blog

JANUARY 31, 2017

Take, for instance, how each field views the provenance of the training data when building predictive models. For most of ML, the training data is a given, often presumed to be representative of the data against which the prediction model will be deployed, but not much else. Some branches of machine learning (e.g.

Machine Learning 73

Machine Learning Modeling Statistics Predictive Modeling 73

AWS Big Data

NOVEMBER 14, 2023

The same data foundation built on Kinesis Data Streams is used to continuously analyze how users interact with the generated content and helps the product team fine-tune the application. These services help customers bring data to their applications and models, making them smarter. “We

IoT 55

IoT Data-driven Data Lake Data Strategy 55

Alation

APRIL 14, 2022

Supports the ability to interact with the actual data and perform analysis on it. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Parametrization. A technique to automate changes in iterative passes. Pattern Matching. Visual Profiling. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Smarten

MAY 17, 2024

For example, a Data Scientist can use PMML integration to Import models created in other languages like R and Python with a PMML format, and use those models with analytical workflows to roll out predictive models to users, enabling business users to participate in analysis and making Data Scientists more productive.

Analytics 52

Analytics Predictive Modeling ROI Cost-Benefit 52