CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? Fortunately, advances in analytic technology have made the ability to see reliably into the future a reality.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

MARCH 2, 2018

Banking, transportation, healthcare, retail, and real estate, all have seen the emergence of new business models fundamentally changing how customers use their services. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42

FineReport

APRIL 26, 2023

By leveraging Big Data technologies, companies can collect, store, and analyze information to make informed decisions and improve their operations. For example, a computer manufacturing company could develop new models or add features to products that are in high demand. How to Choose the Right Big Data Analytics Tools?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

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. A fundamental differentiation factor is in the method each of them uses as a base.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110