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Data architecture strategy for data quality

IBM Big Data Hub

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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How Knowledge Graphs Power Data Mesh and Data Fabric

Ontotext

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

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DataOps with Matillion and DataKitchen

DataKitchen

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. DataKitchen acts as a process hub that unifies tools and pipelines across teams, tools and data centers. Stronger Together.

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Five benefits of a data catalog

IBM Big Data Hub

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Ensuring data quality is made easier as a result.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). These reports include the cash flow statement, income statement, and balance sheet.

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How Metadata Makes Data Meaningful

erwin

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair.

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9 Distinct Threats to Your BI Implementation

Jet Global

Recently released is a report by Gartner about all the things that can go wrong in your BI implementation. In Gartner’s report, an analyst goes to great pains to say that there is “much more risk associated to non-technology issues than there is to deploying the infrastructure, tools, and apps.”. Data quality issues.