CIO Business Intelligence

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Transforming data into value What is a data scientist?

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

CIO Business Intelligence

APRIL 22, 2022

For most organizations, it is employed to transform data into value in the form of improved revenue, reduced costs, business agility, improved customer experience, the development of new products, and the like. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. It doesn’t matter if you use graphs or charts, you need to get better at data visualization.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

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 Is The Difference Between Business Intelligence And Business Analytics.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Sisense

AUGUST 11, 2019

BA is a catch-all expression for approaches and technologies you can use to access and explore your company’s data, with a view to drawing out new, useful insights to improve business planning and boost future performance. BA primarily predicts what will happen in the future. Or is Business Intelligence One Part of Business Analytics?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

FineReport

APRIL 9, 2024

Through the utilization of predictive models, clinicians can forecast patient outcomes and resource needs, enabling early intervention and personalized care delivery. Furthermore, the implementation of healthcare data mining techniques allows organizations to uncover hidden patterns and correlations within their datasets.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

MAY 24, 2018

Smarten Augmented Analytics represents the evolution of the ElegantJ BI approach to business intelligence, and the significance of self-serve data preparation, smart visualization, and assisted predictive modeling.

Analytics 40

Analytics Data Analytics Data mining Visualization 40

Jet Global

MAY 1, 2023

All of the above points to embedded analytics being not just the trendy route but the essential one. Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Standalone is a thing of the past.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52