Data Analytics Data Integration Data Quality Digital Transformation 
Data Virtualization
NOVEMBER 25, 2020
In recent years, we have seen wide adoption of data analytics. Some issues that have been most often cited for this include: Poor data quality: While preparing. However, most organizations continue to find it challenging to quickly yield actionable insights.
CIO Business Intelligence
MARCH 4, 2024
Data fabric introduces an intelligent semantic layer that orchestrates disparate data sources, applications, and services into a unified and easily accessible framework. Enabled via a data integration hub, the data fabric architecture connects, organizes, and manages data, providing a consistent view across the data ecosystem.
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erwin
JANUARY 30, 2020
However, the latest group of survey participants say better decision-making is their primary driver (62 percent), with analytics secondary (51 percent), and regulatory compliance coming in third (48 percent). Constructing a Digital Transformation Strategy: How Data Drives Digital. Stop Wasting Your Time.
CIO Business Intelligence
SEPTEMBER 2, 2022
The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work.
CIO Business Intelligence
AUGUST 31, 2022
The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work.
IBM Big Data Hub
JANUARY 17, 2023
Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. This capability will provide data users with visibility into origin, transformations, and destination of data as it is used to build products. Data integration. Start a trial.
Ontotext
FEBRUARY 26, 2024
This happenstance approach may eventually get organizations to a reasonable data maturity level but at massive costs. Until C-level executives start to take graph technologies more seriously, they will struggle to deliver on the promises of their digital transformations and become data-driven.
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