Why Business Intelligence Initiatives Fail Without Clean and Connected Data
Executives love the promise of business intelligence (BI). Dashboards that tell the truth. Reports that line up across departments. And strategies driven by real data
Executives love the promise of business intelligence (BI). Dashboards that tell the truth. Reports that line up across departments. And strategies driven by real data
More than 55% of organizational data worldwide is dark, meaning it’s collected, processed, and stored, but never used. But over 80% of business leaders believe
What if we told you that you don’t have clean data – just clean CRM screens? It’s easy to believe your data is healthy when
Alteryx built its reputation as a powerful analytics and automation platform. But when the problem isn’t just workflow inefficiency – it’s unreliable, inconsistent, duplicated, or
About 68% of enterprise data goes unleveraged. Why? Because 90% of data is unstructured, making it difficult – if not impossible – to extract actionable
In 2024, National Public Data, a prominent background check and fraud prevention service, made headlines for all the wrong reasons. Over 2.7 billion records containing
In a survey conducted by Validity, 44% of the respondents revealed that duplicate data significantly impacted their ability to fully leverage their CRM systems. Now,
Data matching helps ensure that disparate data sources are accurately aligned, cleansed, and ready for use. And that’s where an effective data catalog becomes essential
Data cleaning and matching are critical processes for maintaining data integrity and deriving actionable insights from large datasets. This review dives into the advanced techniques
Poor data standardization is a hidden profit killer. When customer names, products, or sales figures appear in different formats across systems (and often even within
With 89% of employees reporting sifting through up to six data sources daily to find relevant information, data sprawl emerges as a major culprit undermining
You invested in big data technologies thinking it will help you understand your audience better. You switched to smart CRMs, hired data scientists to help
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