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? Can Predictive Analytics Help You Achieve Business Objectives?

Business Objectives 40

Business Objectives Predictive Analytics Analytics Forecasting 40

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 61

Machine Learning Data Science Statistics Deep Learning 61

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. pharmacogenomics) and risk assessment of genetic disorders (e.g., Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Smarten

JUNE 28, 2018

Business Problem: A bank wants to group loan applicants into high/medium/low risk based on attributes such as loan amount, monthly installments, employment tenure, the number of times the applicant has been delinquent in other payments, annual income, debt to income ratio etc. Use Case – 1. Use Case – 2.

IT 40

IT Business Intelligence Predictive Modeling Risk 40

Smarten

JUNE 27, 2018

For example, if an outlier indicates a risk or a mistake, that outlier should be identified and the risk or mistake should be addressed. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

IT 40

IT Business Intelligence Predictive Modeling Testing 40

Smarten

JUNE 25, 2018

Loan applicants in a bank might be grouped as low, medium, and high risk applicants based on applicant age, annual income, employment tenure, loan amount, the number of times a payment is delinquent etc. About Smarten.

Enterprise 40

Enterprise IT Business Intelligence Predictive Modeling 40

Smarten

JUNE 29, 2018

Based on these labels, the bank can easily make a decision on whether to give a loan to an applicant and the credit limit and interest rate each applicant is eligible for based on the amount of risk involved. Use Case – 2.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 27, 2018

Based on these labels, the bank can easily make a decision on whether to give loan to an applicant and how much credit to extend, as well as the interest rate each applicant is eligible for based on the amount of risk involved. Use Case – 2.

Business Analytics 40

Business Analytics Analytics IT Business Intelligence 40

Smarten

JUNE 29, 2018

Based on these labels, the bank can easily make a decision on whether to give a loan to an applicant and the credit limit and interest rate for each applicant, based on the amount of risk. Use Case – 2.

Enterprise 40

Enterprise Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 27, 2018

In this way, the riskier customers are identified easily and bank can avert the risk of delinquencies. Business Problem: Based on customer attributes and past online shopping behavioral data, an online retail giant wants to predict the future purchases of customers. Use Case – 2.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. What Is Business Intelligence And Analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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. temperature, salary).

Machine Learning 83

Machine Learning Modeling Deep Learning Predictive Modeling 83

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

FineReport

APRIL 24, 2024

This simplification allows stakeholders to grasp the underlying patterns and trends within the data without getting lost in the complexity of raw numbers and statistics. By presenting comprehensive insights through visualizations, decision-makers can assess trends, risks, and opportunities with greater clarity.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

Rocket-Powered Data Science

OCTOBER 6, 2023

What is the point of those obvious statistical inferences? The point is that the 100% association between the event and the preceding condition has no special predictive or prescriptive power. How do predictive and prescriptive analytics fit into this statistical framework? Or more simply: given Y, find X.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Smarten

JUNE 25, 2018

This article provides a brief explanation of the definition and uses of the Descriptive Statistics algorithms. What is a Descriptive Statistics? Descriptive statistics helps users to describe and understand the features of a specific dataset, by providing short summaries and a graphic depiction of the measured data.

Statistics 40

Statistics Enterprise Measurement Business Intelligence 40

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Approaches need to take this dynamic nature into mind.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Jet Global

MAY 1, 2023

Positioning Embedded Analytics for Each Executive Here are some tips on understanding executives’ priorities and getting them on board with the project. Show how embedded analytics will enhance sales and marketing through better demos and shorter sales cycles. It will help to eliminate some of the development risks.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52