Category: Analytics
General topics related to data, analysis, and analytics.
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4 Steps to Avoid Difficult Forecasts
Forecasting is often treated as essential, yet it fails for socially driven behavior due to complicating factors. Instead of relying on unreliable predictions, we should reframe the problem, focus on the real issue, and deliver actionable solutions. This aligns with the Advanata framework emphasizing practical, tailored outcomes over generic analytics
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Pattern-Driven Analytics: The Mirage That Misleads
Misidentified patterns can produce serious analytical errors. Valid pattern recognition requires an inductive approach that starts with a hypothesis explaining the underlying mechanism, tests observed patterns against it, validates results using external evidence, and confirms conclusions with a problem expert. Decomposing complex problems into simpler components improves validation reliability.
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More Analytics Myths Holding You Back
There are plenty of analytics myths that discourage adoption. In this second article we discuss how Advanata overcomes such myths as analytics being time-consuming, impractical, insufficient, and incorrect.
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We Need Effectiveness, Not Analytics
Quantification is essential for problem solving and can be used to convert between content types. Advanata is based on the concept of effectiveness that utilizes all quantification methods and leverages each resource according to what it does best in a structured manner to deliver results that effectively solve customer problems.
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Can Data Ever Tell the Truth?
Data can never be objective since its construction requires the use of preconceptions. This increases usability for users but decreases objectivity. As content is transformed into more usable forms, it becomes more complex and less available. Advanata simplifies problems thus reducing the need for complex content and increasing its availability.
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6 Fixes for Great Analytics Results
Analysts face challenges due to poorly framed questions from customers, leading to ineffective analytics. Improved communication is essential for collaboration. By refining questions to be precise, analysts can derive actionable insights. Advanata’s technologies aim to bridge this communication gap, ensuring successful analytics outcomes by promoting better question formation.
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The Hidden Value of Data: Useful or Useless?
Content is essential but varies in value across users. The same document serves different needs, demonstrating content’s polymorphic nature. Effective transformation requires analyzing problems to meet specific requirements. Advanata employs a structured approach to tackle analytics issues, emphasizing customer-driven solutions and the necessity of clear problem definition.
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Analytics Myths Holding You Back
There are plenty of analytics myths that discourage adoption. In this article we discuss how Advanata overcomes such myths as analytics being useless, confusing, expensive, and unnecessary.
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We Need Information, Not Data
It is important to emphasize the importance of transitioning from viewing data as the final product to recognizing the necessity of information. We discuss the classification of content, the biases involved, and how Advanata utilizes information in analytics for more effective problem solving. By prioritizing information, businesses can better address challenges.
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You Don’t Need Another Dashboard
Dashboards often distract from effective problem-solving in business operations, focusing on data volume rather than actionable insights. While useful for reporting and transparency, their complexity can hinder decision-making. Analytics, like those enabled by Advanata, are essential for addressing real business challenges and fostering survival in an evolving marketplace.
Advanata 