IBM Big Data Hub

MAY 1, 2023

Continued advancement in AI development has resulted today in a definition of AI which has several categories and characteristics. The early versions of AI were capable of predictive modelling (e.g., recommending similar Netflix shows based on your previous choices) or robotics (e.g.,

Insurance 79

Insurance Predictive Modeling Cost-Benefit Statistics 79

CIO Business Intelligence

JULY 24, 2023

It has also developed predictive models to detect trends, make predictions, and simulate results. We realized with different tests with fans that sometimes the types of definitions we were preparing, or the kind of graphics to present this data, were not well understood by different people,” Bruno says.

Broadcasting 95

Broadcasting Recreation/Entertainment Testing Machine Learning 95

Juice Analytics

JULY 6, 2018

Here are 25 more lessons we've learned (the hard way) about what's easy and what's hard when it comes to telling data stories: Easy: Picking a good visualization to answer a data question Hard: Discovering the core message of your data story that will move your audience to action Easy: Knowing who is your target audience Hard: Knowing what motivates (..)

Slice and Dice 83

Slice and Dice Predictive Modeling Visualization Data-driven 83

IBM Big Data Hub

OCTOBER 5, 2022

The need to collaborate, share data and agree on definitions across organizational boundaries and systems. However, the reality of this is complicated by several factors including: Differing time horizons and cadences: Days/Weeks vs Months/Quarters. Differing levels of detail: SKUs/ Products vs Product Groups/ Lines of Business.

Analytics 52

Analytics Forecasting Predictive Modeling Manufacturing 52

Smart Data Collective

MARCH 23, 2022

The same could definitely be said about 5G technology. Utilizing advanced heuristics and AI modeling OEMs can simulate a multitude of conditions, fast-tracking these models using automation. OEMs also utilize live feedback from the vehicles they have produced to create predictive AI models.

IoT 108

IoT Internet of Things Testing Cost-Benefit 108

Smart Data Collective

MARCH 28, 2022

There are four main types of data analytics: Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. How to make the best use of data analytics.

Data Analytics 84

Data Analytics Software Analytics Statistics 84

DataRobot

NOVEMBER 29, 2021

The chart tells us that individuals over 40 and individuals under 40 are receiving different percentages of outcomes, which means the model is biased. DataRobot offers five bias definitions to choose from that are aligned to the categories described above. The DataRobot Solution provides prediction capabilities based on customer data.

Technology 52

Technology Metrics Predictive Modeling Modeling 52

Andrew White

MAY 4, 2020

The models are practically useless. Oh, and by the way, you now have less time to make the decisions (see How to Manage Your Predictive Models During the Pandemic’s Rapid Changes ). As a result, the guidance for the decisions are useless too. The answer is to think and look “wideward”.

Uncertainty 90

Uncertainty Data Quality Consulting Predictive Modeling 90

Juice Analytics

MARCH 11, 2021

Predictive models to take descriptive data and attempt to tell the future. The best product managers have a vision for the product, understand the target customers, communicate well, are definitive in their decisions and recognize the reality of technical trade-offs. How are you going to turn that data into a solution?

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

O'Reilly on Data

JUNE 18, 2019

Increasing the quality of the available data via either unification or cleaning, or both, is definitely an important and a promising way forward to leverage enterprise data assets. 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

MAY 6, 2024

Enter the age of data-driven protocol assessment: using benchmarking tools and predictive modeling to gauge protocol intricacies and forecast eligible patient numbers, which then inform protocol adjustments. Ensuring early assumptions resonate with real-world execution is paramount.

Advertising 69

Advertising Data-driven Optimization Strategy 69

DataRobot Blog

JUNE 23, 2022

Most successful ML and AI projects are replacing an existing prediction with a more accurate and/or faster one. Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. BA primarily predicts what will happen in the future. What About “Business Intelligence”?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Jedox

MAY 17, 2022

Nor could they have successfully predicted any number of the “black swan” events in any reasonable fashion; while some nations’ military intelligence capabilities might have detected these threats sooner rather than later, for the vast majority of businesses and finance departments, these are truly unique events.

Predictive Analytics 83

Predictive Analytics Finance Analytics Forecasting 83

CIO Business Intelligence

OCTOBER 12, 2023

They’re huge initiatives for the company and they’re definitely going to move the needle. All these things are now possible because we brought all the data together into one place. And now we have three launches happening here over the next month or two of our own private instance of ChatGPT we generated. That’s a healthy tension.

IoT 125

IoT Manufacturing Strategy Modeling 125

datapine

AUGUST 14, 2019

Computational mathematics is in the heart of this language, typically used in algorithm development, modeling and simulation, scientific and engineering graphics, data analysis, and exploration. It offers many statistics and machine learning functionalities such as predictive models for future forecasting. Source: mathworks.com.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smarten

JUNE 26, 2018

This article provides a brief definition of the multinomial-logistic regression classification algorithm and its uses and benefits. What is the Multinomial-Logistic Regression Classification Algorithm?

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Sisense

APRIL 10, 2020

All common and necessary data science tasks (data loading, data analysis, data exploration, data preprocessing, data featurization, data modeling, and predictive modeling) are available in both R programming and Python languages. Both languages are user-friendly and easy to implement.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Ms SQL Girl

MAY 19, 2016

To simplify, “In-database Advanced Analytics”: you can run powerful statistical / predictive modelling (from R) inside SQL Server. Read the official definition here. As you may already know In-database Analytics (also known as Advanced Analytics) is available in SQL Server 2016. Check Out SQL Latest Bits.

Visualization 45

Visualization Predictive Modeling Statistics Reporting 45

Ms SQL Girl

MAY 19, 2016

To simplify, “In-database Advanced Analytics”: you can run powerful statistical / predictive modelling (from R) inside SQL Server. Read the official definition here. As you may already know In-database Analytics (also known as Advanced Analytics) is available in SQL Server 2016. Check Out SQL Latest Bits.

Visualization 40

Visualization Predictive Modeling Statistics Reporting 40

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Definition: description vs prediction.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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. This article is a short summary of my understanding of the definition of data science in 2018. Even better – I still get paid for being a data scientist. But what does it mean?

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. The pandemic falls into the macro-level because we really can’t predict those kinds of events.

Uncertainty 97

Uncertainty Manufacturing Data-driven Business Intelligence 97

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. The pandemic falls into the macro-level because we really can’t predict those kinds of events.

Uncertainty 97

Uncertainty Manufacturing Data-driven Business Intelligence 97

Occam's Razor

AUGUST 9, 2021

Predictive metrics! Here’s the definition of a metric from my first book: A metric is a number. Note: Strictly speaking what we are doing above is closer to Predictive Modeling, even though we have a bunch of Predictive Metrics. But first, let's take a small step back. What is a metric? Simple enough.

Metrics 142

Metrics Analytics Key Performance Indicator Predictive Modeling 142

Smarten

NOVEMBER 26, 2023

Before you can decide which BI tools and approach are right for your business, you must have a solid definition of Business Intelligence and the tools on the market today. ‘Find out how business intelligence and analytics technology can support your enterprise and engage the experts to help you choose an approach.’

Marketing 40

Marketing Business Intelligence Key Performance Indicator Prescriptive Analytics 40

AWS Big Data

JANUARY 25, 2023

An AWS Glue crawler populates the AWS Glue Data Catalog with the data schema definitions (in a landing folder). 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.

Visualization 79

Visualization Interactive Modeling Machine Learning 79

Smarten

NOVEMBER 19, 2018

The process of predictive analytics has come far in the past decade. Today’s self-serve predictive analytics and forecasting tools are designed to support business users and data analysts alike. What is Predictive Analytics? No longer is this process the sole responsibility of data scientists or IT staff.

Business Objectives 40

Business Objectives Predictive Analytics Analytics Forecasting 40

Cloudera

NOVEMBER 18, 2020

The pipeline provides its clinicians fast access to real-time patient data and prediction models. We also want to extend a heartfelt thank you to each and every member of our judging panel. We owe you a great debt of gratitude for contributing your expertise to reviewing and scoring each of this year’s awards submissions.

Internet Publishing and Broadcasting 118

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 118

Domino Data Lab

AUGUST 12, 2021

In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase. If we were to use this column in a model, we are now aware that we have an unbalanced dataset.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

IBM Big Data Hub

JULY 5, 2023

First, though, let’s start with some definitions that will be key to understanding the value of ALM to the modern enterprise. This information is then used to build predictive models of asset performance over time and help spot potential problems before they arise. What is an asset?

Strategy 55

Strategy Management IoT Cost-Benefit 55

Alation

APRIL 14, 2022

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. It’s not a simple definition. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”).

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Darkhorse

JULY 6, 2017

Let’s further pretend you’re starting out with the aim of doing a big predictive modeling thing using machine learning. Sometimes, you need to re-categorize the past to match up to the current category definitions. Sales are growing steadily, our definitions simply changed. I hope you enjoy that sort of thing. Keep going.

Data Lake 74

Data Lake Sales Machine Learning Visualization 74

Domino Data Lab

APRIL 21, 2021

The fraudulent transactions definitely have a higher standard deviation, but given their relatively low number we can’t be certain if this is a genuine pattern or just a statistical coincidence. def compare_leg_fraud(attribute): leg_trS = dataDF.loc[dataDF["Class"] == 0][attribute].rename("Legitimate").describe()

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Domino Data Lab

SEPTEMBER 18, 2019

This is definitely worth exploring more. It may be that your organization can build an AI application by using their prediction models as a base, and then layering other AI and ML techniques on top. By scrolling through the graph, it can be shown that in December 2017, the price in Palo Alto was about $2.7

Visualization 99

Visualization Interactive Machine Learning Data Science 99

Smarten

JULY 10, 2018

This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented data discovery tools.

Analytics 40

Analytics Forecasting Statistics Sales 40