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Data architecture strategy for data quality

IBM Journey to AI blog

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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What is Data Integration in Data Mining with Example?

Pickl AI

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. It ensures that the integrated data is available for analysis and reporting.

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What is a data fabric?

Tableau

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.* Analytics data catalog. Data quality and lineage. Data modeling.

Tableau 99
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What is a data fabric?

Tableau

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.* Analytics data catalog. Data quality and lineage. Data modeling.

Tableau 97
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dbt Labs’ Coalesce 2023 Recap

phData

Enhanced Collaboration: dbt Mesh fosters a collaborative environment by using cross-project references, making it easy for teams to share, reference, and build upon each other’s work, eliminating the risk of data silos. Tableau (beta) Google Sheets (beta) Hex Klipfolio PowerMetrics Lightdash Mode Push.ai