Remove Descriptive Analytics Remove Strategy Remove Unstructured Data
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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

As someone deeply involved in shaping data strategy, governance and analytics for organizations, Im constantly working on everything from defining data vision to building high-performing data teams. My work centers around enabling businesses to leverage data for better decision-making and driving impactful change.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

“We get access, post-Games, to the ticket data to analyze any patterns in terms of incidents and responses.”. Descriptive analytics also help them understand the number of athletes and workers required to support that specific competition or sport. This analytics engine will process both structured and unstructured data. “We

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

Broadly, there are three types of analytics: descriptive , prescriptive , and predictive. The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. This data is gathered into either on-premises servers or increasingly into cloud data warehouses and data lakes.

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Data trust and the evolution of enterprise analytics in the age of AI

CIO Business Intelligence

In Prioritizing AI investments: Balancing short-term gains with long-term vision , I addressed the foundational role of data trust in crafting a viable AI investment strategy. This capability has become increasingly more critical as organizations incorporate more unstructured data into their data warehouses.