datapine

AUGUST 14, 2019

Many users also report its power in constructed-in capabilities and libraries, data manipulation, and reporting. Whether the company needs a comprehensive financial analytics strategy or process, R has become one of the most used data science tools to explore and manage data. Source: mathworks.com.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smarten

JUNE 20, 2018

The business can use this information for forecasting and planning, and to test theories and strategies. For example, the decision to the ARIMA or Holt-Winter time series forecasting method for a particular dataset will depend on the trends and patterns within that dataset.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

JUNE 29, 2018

Multiple linear regression models are useful in helping an enterprise to consider the impact of multiple independent predictors and variables on a dependent variable, and can be beneficial for forecasting and predicting results. About Smarten.

Business Analysis 40

Business Analysis IT Sales Statistics 40

Smarten

JUNE 29, 2018

Weather Forecasting – Based on temperature, humidity, pressure etc., an organization can predict if it will be rainy/sunny/windy tomorrow. a business can predict the likelihood of fraud. It is useful for making predictions and forecasting data based on historical results. About Smarten.

Enterprise 40

Enterprise IT Business Intelligence Forecasting 40

Smarten

NOVEMBER 3, 2017

The world of business analytics has changed dramatically in the past few years. If your business is looking to upgrade BI tools or to begin implementing an analytics solution, the solution must be user friendly for business users.

Analytics 40

Analytics Visualization Experimentation Cost-Benefit 40

Smarten

JUNE 29, 2018

Business Benefit: Given the health and body profile of a patient and the recent treatments and drugs prescribed for the patient, the doctor can predict the probability and make recommendations on changes in treatment/drugs. About Smarten.

Enterprise 40

Enterprise 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’s the difference between Business Analytics and Business Intelligence?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Smarten

JULY 10, 2018

Use Case(s): Weather Forecasting, Fraud Analysis and more. Frequent Pattern Mining (Association): What is Frequent Pattern Mining (Association) and How Does it Support Business Analysis? ARIMAX Forecasting: What is ARIMAX Forecasting and How is it Used for Enterprise Analysis?

Analytics 40

Analytics Forecasting Statistics Sales 40

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. They are sentinel, precursor, and cognitive analytics. ” “Just 26.5%

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

datapine

NOVEMBER 27, 2019

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process. 3) Artificial Intelligence.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52