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 142

Unstructured Data Machine Learning Data Science Data mining 142

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data scientists use data science to discover insights from massive amounts of structured and unstructured data to shape or meet specific business needs and goals.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

CIO Business Intelligence

OCTOBER 13, 2023

Established and emerging data technologies: Data architects need to understand established data management and reporting technologies, and have some knowledge of columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

JUNE 28, 2023

The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace. Working with non-typical data presents us with a reality where encountering challenges is part of our daily operations.”

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Jedox

OCTOBER 22, 2020

In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

CIO Business Intelligence

JULY 22, 2024

Still, he says, it’s hard to do anything at a company the size of Dow by yourself, so it was vital to seek partnerships across the company’s businesses, within the IT organization, and in Dow’s other functions. There are data privacy laws, and security regulations and controls that have to be put in place.

Data Governance 119

Data Governance Unstructured Data Technology Manufacturing 119

Sisense

MAY 11, 2021

The right data model + artificial intelligence = augmented analytics. However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. Dig into AI. displaying BI insights for human users).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. displaying BI insights for human users).

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

Rita Sallam

JULY 22, 2016

decline in traditional BI ( See: Market Share Analysis: Business Intelligence and Analytics Software, 2015 ). Answer: The primary differences are described in detail in our research, Technology Insight for Modern Business Intelligence and Analytics Platforms and summarized in the table below from the report.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

FineReport

APRIL 26, 2023

Unlike traditional databases, processing large data volumes can be quite challenging. With Big Data Analytics, businesses can make better and quicker decisions, model and forecast future events, and enhance their Business Intelligence. How to Choose the Right Big Data Analytics Tools?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Grooper

AUGUST 19, 2019

Successfully navigating the 20,000+ analytics and business intelligence solutions on the market requires a special approach. Read on to learn how data literacy, information as a second language, and insight-driven analytics take digital strategy to a new level. The benefit of speaking data, a.k.a. Master data management.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

NOVEMBER 7, 2023

The Challenges of Extracting Enterprise Data Currently, various use cases require data extraction from your OCA ERP, including data warehousing, data harmonization, feeding downstream systems for analytical or operational purposes, leveraging data mining, predictive analysis, and AI-driven or augmented BI disciplines.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52