CIO Business Intelligence

JULY 5, 2022

Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. Business analytics also involves data mining, statistical analysis, predictive modeling, and the like, but is focused on driving better business decisions.

Business Analytics 122

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 122

CIO Business Intelligence

MAY 14, 2024

As we are testing and dipping our toes in the water with AI, we are choosing to keep that as private as possible,” he says, noting that the public cloud has the horsepower needed for many LLMs of today but his company has the option of adding GPUs if needed via its privately owned Dell equipment.

IT 137

IT Data Processing Enterprise Modeling 137

datapine

NOVEMBER 27, 2019

2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM). A survey conducted by the Business Application Research Center stated the data quality management as the most important trend in 2020.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JANUARY 24, 2019

With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as business users leverage systems and solutions that are designed with Machine Learning capabilities to predict outcomes and analyze data.

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

Birst BI

AUGUST 23, 2018

For example, there are a plethora of software tools available to automatically develop predictive models from relational data, and according to Gartner, “By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.” [1] Source: Gartner (April 2018).

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Birst BI

MAY 29, 2018

These adoption rates include all the users of the BI system – administrators who manage the system, analysts who build reports, and business users who consume reports for better decision making. He published a paper proposing the development of a “relational database model” to address this issue.

Slice and Dice 74

Slice and Dice Analytics Business Intelligence Machine Learning 74

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

A single model may also not shed light on the uncertainty range we actually face. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. On the other hand, these customer forecasts can be aspirational and often lack high quality prediction intervals.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113