Data Pine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. The data warehouse. 1) The raw data.

Business Intelligence 108

Business Intelligence Business Intelligence Procurement Data Warehouse 108

Astera

APRIL 28, 2023

Additionally, AI-powered data modeling can improve data accuracy and completeness. For instance, Walmart uses AI-powered smart data modeling techniques to optimize its data warehouse for specific use cases, such as supply chain management and customer analytics.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

MARCH 20, 2024

The increasing digitization of business operations has led to the generation of massive amounts of data from various sources, such as customer interactions, transactions, social media, sensors, and more. This data, often referred to as big data, holds valuable insights that you can leverage to gain a competitive edge.

Data Management 52

Data Management Master Data Management Government Data Warehouse 52

Astera

MARCH 28, 2024

While a data catalog serves as a centralized inventory of metadata, a data dictionary focuses on defining data elements and attributes, describing their meaning, format, and usage. The former offers a comprehensive view of an organization’s data assets.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

MAY 14, 2024

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.

Government 52

Government Data Governance Master Data Management Documentation 52

Astera

MAY 30, 2024

This approach often involves more complex processes like drill-down, data discovery, mining, and correlations. Example : Companies monitor social media mentions using text analytics to understand public sentiment about their brand and competitors.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

ElegantJ BI

NOVEMBER 16, 2016

If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. Self-Serve Analytical Capability (see Data Discovery) Not every business intelligence solution supports true, self-serve data analysis.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

NOVEMBER 16, 2016

If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. Self-Serve Analytical Capability (see Data Discovery) Not every business intelligence solution supports true, self-serve data analysis.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

NOVEMBER 16, 2016

If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. Data Access. Self-Serve Analytical Capability (see Data Discovery). Not every business intelligence solution supports true, self-serve data analysis. Data Discovery.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

DECEMBER 5, 2016

Factors like poor User Adoption, Data Access, Features and Benefits, Self-Serve Analytical Capability, Data Sharing and Reporting, Cost vs. Benefit, and Data Discovery issues must be considered in order to ensure the success of your self-serve business intelligence initiative.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Data Governance 130

ElegantJ BI

DECEMBER 5, 2016

Factors like poor User Adoption, Data Access, Features and Benefits, Self-Serve Analytical Capability, Data Sharing and Reporting, Cost vs. Benefit, and Data Discovery issues must be considered in order to ensure the success of your self-serve business intelligence initiative.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Data Governance 130

ElegantJ BI

DECEMBER 5, 2016

Factors like poor User Adoption, Data Access, Features and Benefits, Self-Serve Analytical Capability, Data Sharing and Reporting, Cost vs. Benefit, and Data Discovery issues must be considered in order to ensure the success of your self-serve business intelligence initiative. Data Source and Data Structural Review.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Data Governance 130

Astera

DECEMBER 6, 2024

By analyzing datasets, LLMs can automatically generate descriptive metadata tags, improving data cataloging and facilitating faster data discovery in storage or warehousing systems. NLP Use Cases NLP is useful for spam detection, social media monitoring, and customer feedback analysis.

Documentation 52

Documentation E-Commerce Artificial Intelligence Data Warehouse 52

Insight Software

MAY 1, 2023

Salesforce monitors the activity of a prospect through the sales funnel, from opportunity to lead to customer. The functionality allows them to zero in on the pipeline data that is associated with the account record of interest. Their devices monitor a user’s activity and transmit data to the cloud.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52