Category: Technology

  • More Analytics Myths Holding You Back

    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

    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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  • The Hidden Value of Data: Useful or Useless?

    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

    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

    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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  • Three Steps to Success with Advanata

    Three Steps to Success with Advanata

    Practical analytics problems can often be solved in three simple steps, focusing on reframing research into business issues. Analysts refine parameters for effective solutions using data, while Advanata’s AI optimizes outcomes for immediate action. The approach simplifies complex challenges, making analytics accessible and impactful. This demonstrated in a marketing budget example.

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  • You Don’t Need Another Dashboard

    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.

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  • Smarter Analytics: Less Work, Bigger Impact

    Smarter Analytics: Less Work, Bigger Impact

    The analytics sector faces a significant disconnect between customers and analysts, resulting in confusion and inefficiencies. Customers seek clarity, while analysts provide depth. Advanata addresses this by employing a top-down approach that simplifies processes and enhances usability, enabling more effective analytics and maximizing value without unnecessary complexity or waste.

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  • Don’t Fall for the Correlation Trap

    Don’t Fall for the Correlation Trap

    Correlation does not imply causation; many analysts erroneously conflate the two. Collaboration between data analysts and customers, who possess domain expertise, is crucial for accurate conclusions. Employing an inductive approach allows for clearer identification of causation, improving efficiency and outcomes in analytics. This balance enhances the analysis process and results.

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  • Redefine Analytics with Advanata

    Redefine Analytics with Advanata

    Everyone should be using data analytics to help solve their business challenges. To help overcome difficulties in adopting data analytics Advanata reduces complexity through the use of a business problem framework, involves customers through the use of the inductive approach, and generates actionable outputs using the data effectiveness methodology.

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