CIO Business Intelligence

FEBRUARY 6, 2025

For example, at a company providing manufacturing technology services, the priority was predicting sales opportunities, while at a company that designs and manufactures automatic test equipment (ATE), it was developing a platform for equipment production automation that relied heavily on forecasting. You get the picture.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

CIO Business Intelligence

JULY 5, 2022

Business analytics and business intelligence (BI) serve similar purposes and are often used as interchangeable terms, but BI can be considered a subset of business analytics. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward. Business analytics techniques.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

CIO Business Intelligence

JUNE 7, 2022

To ensure robust analysis, data analytics teams leverage a range of data management techniques, including data mining, data cleansing, data transformation, data modeling, and more. What are the four types of data analytics? In business analytics, this is the purview of business intelligence (BI).

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. Your Chance: Want to try a professional BI analytics software? This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

IBM Big Data Hub

SEPTEMBER 19, 2023

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.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

BizAcuity

MARCH 31, 2022

More use-cases are being tried, tested and built everyday, the innovation in this field will not cease for the next few years. But AI platforms like TensorFlow, MS Azure and Google AI allow large sets of data to be used for training, testing, developing and deploying AI applications and algorithms. Applications of AI. AI in Marketing.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Grooper

AUGUST 19, 2019

I have learned that trust is required to take data modeling in production. What is machine learning? Machine learning. We’re basically making the machine learn by itself. The ways we do that are called machine learning algorithms. What are some examples of effective machine learning?

Machine Learning 40

Machine Learning Metrics Descriptive Analytics Testing 40