October 11, 2024
Headlines

Data Education

Self-Service Analytics: Pros and Cons

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Self-service analytics empowers the non-technical users in an organization. Traditionally, data analysis was the domain of specialized data scientists or IT professionals with skills to manipulate and interpret complex datasets. In self-service analytics, user-friendly tools enable ordinary business users to conduct data analyses without expert knowledge or support.   These tools typically feature user-friendly interfaces, drag-and-drop functionalities, and pre-built templates…

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Fundamentals of Data Preparation

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Data is often called the raw material of the information age, and it does share characteristics with the resources that power other industries. For example, imagine trying to make a car out of unrefined iron ore. A lot of processing happens between the mine and the factory. Data is no different. In its “raw” form,…

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Mind the Gap: Ask for Business Actions, Not Business Value

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I’m not sure I know anyone in the data and analytics field whose platform doesn’t face budget scrutiny. Analytics is expensive. And when cost-cutting is the order of the day, analytics is a big target. Up shields. Time for another business value inventory. I’ve spoken with consultants who have completed analytics business value inventories at…

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The Book Look: Enterprise Intelligence

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Every once in a while, a book comes along that contains such innovative ideas that I find myself whispering “wow” and “interesting” as I read through the pages. “Enterprise Intelligence,” by Eugene Asahara, is one such book. Eugene takes three basic ingredients that are not so new (business intelligence, knowledge graphs, and large language models),…

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Leveraging Citizen Data Scientists to Augment Data Science Teams

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According to some estimates, the average salary of a data scientist in the United States is over $150,000 per year. If your business wishes to accommodate a data-first strategy to improve metrics and measurable success and avoid guesswork and strategies that are based on opinion rather than fact, it can either employ a team of expensive…

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AAA Webinar: Intelligent Automation with AI

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Download the slides here>> About the Webinar In this webinar, we discuss the best practices for automating repetitive tasks with AI and automation platforms. We will learn how to design and integrate AI and automation components, how to optimize and monitor their efficiency and effectiveness, and how to handle exceptions and errors. About the Speaker…

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The Hidden Language of Data: How Linguistic Analysis Is Transforming Data Interpretation

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From Fortune 500 companies to local startups, everyone’s swimming in a sea of numbers, charts, and graphs. But here’s the thing: While structured data like sales figures and customer demographics have long been the backbone of analytics, there’s a growing realization that unstructured data is the real goldmine. Think about it. Every tweet, email, customer review, and social…

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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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Data Visualization in the Era of AI/ML

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How will data visualization evolve in the era of AI/ML? While AI is rapidly evolving, it is ironic that business users are still using “dumb” dashboards. The challenge is to move beyond these unintelligent dashboards to a genuinely transformative visual analytics solution that harnesses the power of AI/ML. While some vendors offer a ChatGPT-like querying…

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Data Product vs. Data as a Product (DaaP): Understanding the Difference

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Data quality (DQ), which ensures that data is fit for business and consumer needs, remains a significant challenge and is growing more complex. According to a dbt Labs 2024 report, 57% of survey respondents identified data quality as a challenging aspect to data preparation, up from 41% in 2022.  To address these data quality challenges, companies increasingly…

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