January 25, 2025
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predictive analytics

Prescriptive Analytics Use Cases

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Optimizing business outcomes through advanced analytics and real-time scenario analysis represents a significant leap forward in decision-making processes. In practice, advanced analytics provides a framework for evaluating an extensive array of potential outcomes derived from different decision paths.  It integrates ML models that simulate various scenarios in real time, thereby offering a dynamic decision-support system….

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Predictive Analytics Techniques

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The process of predictive analytics has three main steps: defining the objectives, collecting relevant data, and developing a predictive model using sophisticated algorithms. These models are further tuned for greater accuracy before being applied to real-world situations like risk analysis or fraud detection.  Predictive analytics techniques are at the forefront of modern data science, enabling organizations to…

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From Instincts to Data-Driven Success: The AI-Powered Path to Product-Led Growth

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Have you noticed the way that businesses grow is changing? We are moving away from standard sales-driven models to more innovative product-led tactics. And what is fueling this shift? You guessed it: AI and predictive analytics. These tools are not just fancy jargon; they are transforming how we understand customer needs, customize experiences, and upgrade…

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AI Is Now A Core Capability Of BI Platforms

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Scientists estimate that insects account for 80% of all animal life on Earth. It’s no wonder that you can’t walk even one foot into a forest without stepping on something crawling or being overwhelmed with buzzing and biting insects. While I am not ready to say that AI-based functionality accounts for 80% of a typical…

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Fundamentals of Descriptive Analytics

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In descriptive analytics, data aggregation, and data mining techniques are used to collect and review the historical data of a business to gauge the past performance. The most common example of descriptive analytics is the reports that a user gets from Google Analytics tools. A web server’s summarized performance reports may help the user analyze…

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Enhancing the Reliability of Predictive Analytics Models

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Predictive analytics is a branch of analytics that identifies the likelihood of future outcomes based on historical data. The goal is to provide the best assessment of what will happen in the future. Basically, predictive analytics answers the question “What will happen?” The value of predictive analytics lies in enabling business enterprises to proactively anticipate…

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Demystifying Advanced Analytics: Which Approach Should Marketers Take?

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“Advanced analytics” has been the new buzzword on every organization’s mind for the past several years. Recent advancements in machine learning have promised to optimize every arm of an organization – from marketing and sales to supply-chain operations.  For some, investments in advanced analytics have been worth the hype. Those who succeed can gain a…

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Preparing for La Niña: Adopting Predictive Maintenance Before Hurricane Season

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With a La Niña watch issued for the summer, businesses operating in hurricane-prone regions face heightened concerns about the impending storm season. La Niña heavily impacts the wind shear and atmospheric conditions over the Atlantic, where most hurricanes form thanks to its warm waters. It’s rare to go a year without a hurricane hitting some part of…

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Demystifying Data Analytics Models

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In today’s global landscape, organizations worldwide are increasingly turning to data analytics to enhance their business performance. Research conducted by McKinsey Consulting revealed that data-driven companies not only experience above-market growth but also witness EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) increases of up to 25% [1]. Additionally, Forrester’s findings indicate that organizations utilizing…

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The FAAR Framework for Consuming Insights from Data and Analytics 

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Faced with overwhelming amounts of data, organizations across the world are looking at leveraging data and analytics (D&A) to derive insights to increase revenue, reduce costs, and mitigate risks. McKinsey found that insight-driven companies report EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [1]. According to Forrester, organizations that use data and insights…

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