CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

Data Quality 76

Data Quality Metrics Data-driven Visualization 76

CIO Business Intelligence

MARCH 4, 2024

The data mesh debate This is not to say that there is a consensus that data mesh is a universal solution. Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies.

Insurance 95

Insurance Strategy Data Governance Data Integration 95

Ontotext

MARCH 20, 2024

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Smart Data Collective

APRIL 29, 2020

A survey from Tech Pro Research showed that 70 percent of organisations already have a digital transformation strategy or are developing one. Solutions for the various data management processes need to be carefully considered. Data transformation. Data analytics and visualisation. Microsoft Azure.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

CIO Business Intelligence

DECEMBER 22, 2022

Research firm Gartner further describes the methodology as one focused on “improving the communication, integration, and automation of data flows between data managers and data consumers across an organization.” The approach values continuous delivery of analytic insights with the primary goal of satisfying the customer.

Analytics 130

Analytics Machine Learning Software Data Quality 130

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 79

Cost-Benefit Metadata Optimization Management 79