CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

Unstructured Data 141

Unstructured Data Modeling Machine Learning Data mining 141

FineReport

MARCH 24, 2024

Given the critical role they play, employers actively seek data analysts to enhance efficiency and stimulate growth. This article explores the data analyst job description, covering essential skills, tools, education, certifications, and experience. SQL manages and retrieves data from databases, handling larger datasets.

Statistics 52

Statistics Data mining Visualization Reporting 52

FineReport

JUNE 11, 2021

And do you know what the key to unlocking value from data is? This article will discuss the definition of business intelligence and analytics and the difference between them. Business analytics is how companies use statistical methods and techniques to analyze historical data to gain new insights and improve strategic decision-making.

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

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. Your Chance: Want to extract the maximum potential out of your data?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

FineReport

JULY 28, 2021

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. Typical tools for data science: SAS, Python, R. Photo by Chris Ried on Unsplash.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. This beats projections for almost all other occupations. BI engineer. Here we will name 3 of the top ones.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

datapine

NOVEMBER 27, 2019

DQM consists of acquiring the data, implementing advanced data processes, distributing the data effectively and managing oversight data. We detailed the benefits and costs of good or bad quality data in our previous article on data quality management , where you can read the five important pillars to follow.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

FineReport

JUNE 11, 2021

And do you know what the key to unlocking value from data is? This article will discuss the definition of business intelligence and analytics and the difference between them. Business analytics is how companies use statistical methods and techniques to analyze historical data to gain new insights and improve strategic decision-making.

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

Smart Data Collective

MAY 8, 2022

Brands are closely working to solve this as they dive deep into the world of big data analytics. Well, don’t go anywhere because, in this article, we will show you how you can use big data analytics combined with AI to achieve the best performance possible. What is the relationship between big data analytics and AI?

Big Data 105

Big Data Data Analytics Analytics Cost-Benefit 105

Smart Data Collective

MARCH 23, 2020

Big data is driving a number of changes in our lives. Forbes recently wrote an article about the impact of big data on the food and hospitality industry. Big data phenomenon has revolutionized almost every aspect of an average citizen’s life. However, other sectors are changing as well. Practically, everything.

Big Data 103

Big Data Recreation/Entertainment Data mining Optimization 103

Peter James Thomas

AUGUST 18, 2018

No this article has not escaped from my Maths & Science section , it is actually about data matters. The image at the start of this article is of an Ichthyosaur (top) and Dolphin. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data. We’ll actually do this later in this article. R: Analytics powerhouse. R libraries.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

FineReport

DECEMBER 19, 2019

Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen. In addition, tools for data analysis and data mining are also important. Excel, Python, Power BI, Tableau, FineReport are frequently used by data analysts.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Jet Global

MAY 1, 2023

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.” Some cloud applications can even provide new benchmarks based on customer data. Standalone is a thing of the past. They can then pinpoint areas for improvement.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52