Remove AI Remove Business Intelligence Remove Data Lakes Remove Predictive Analytics
article thumbnail

Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

Analytics 203
article thumbnail

How OLAP and AI can enable better business

IBM Journey to AI blog

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

article thumbnail

Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. ” Romain Gaborit, CTO, Eviden, an ATOS business “We’re looking at the potential usage of Large Language Models. .

AI 62
article thumbnail

What is Data Mining? 

Pickl AI

It involves using statistical and computational techniques to identify patterns and trends in the data that are not readily apparent. Data mining is often used in conjunction with other data analytics techniques, such as machine learning and predictive analytics, to build models that can be used to make predictions and inform decision-making.

article thumbnail

5 misconceptions about cloud data warehouses

IBM Journey to AI blog

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

article thumbnail

A Guide to Data Analytics in the Travel Industry

Alation

For example, they can create micro segmentations that incorporate multiple factors such as: Age Motive Socioeconomic status Reason for travel Geographic region These micro segmentations enable travel businesses to market more effectively to unique consumer types. Using Alation, ARC automated the data curation and cataloging process. “So