Why Is Data Quality Still So Hard to Achieve?
Dataversity
OCTOBER 25, 2023
We exist in a diversified era of data tools up and down the stack – from storage to algorithm testing to stunning business insights. appeared first on DATAVERSITY.
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Data Fabric and Address Verification Interface
IBM Data Science in Practice
NOVEMBER 28, 2022
Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture. How can organizations get a holistic view of data when it’s distributed across data silos?
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What is a data fabric?
Tableau
APRIL 18, 2022
What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Data modeling. Data preparation.
What is a data fabric?
Tableau
APRIL 18, 2022
What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Data modeling. Data preparation.
Bringing More AI to Snowflake, the Data Cloud
DataRobot Blog
FEBRUARY 28, 2023
Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. According to Flexera 1 , 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy.
Tackling AI’s data challenges with IBM databases on AWS
IBM Journey to AI blog
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.
Solving Complex Telecom Challenges with Data Governance and Location Analytics
Precisely
FEBRUARY 12, 2024
All that time spent on data preparation has an opportunity cost associated with it. Data Governance Drives Insights Data governance provides an important framework. Location-based data is often subject to additional regulatory requirements as well, further adding to the challenges of spatial data governance.
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