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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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How process mining improves IT service management to save your business time and money

IBM Big Data Hub

Similarly with ticket reopens: if a ticket is reopened after being resolved, it indicates the need to address an issue with training or IT resources. Auto-discovery tools like process mining — a tool gaining popularity with organizations — does just that. Process mining is an ideal solution to start planning for automation.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge. How does text mining work?

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How to unlock a scientific approach to change management with powerful data insights

IBM Big Data Hub

Grasping these opportunities at IBM, we’re increasingly building our specialism in process mining and data analysis tools and techniques we believe to be true ‘game changers’ when it comes to building cultures of continuous change and innovation. CoE = Center of Excellence = Accelerator for Change. Making it happen: Driving faster adoption.

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Role of Big Data in Human Resource Management

AIIM

Those who have been practicing Human resource management for years knows the importance of relying on data analytics for creating an enhanced work culture or else they might lag behind that of other departments. Think of using HR analytics models which use existing records of successful candidates to create profiles of high performers.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. It’s also necessary to understand data cleaning and processing techniques.

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Research shows extensive use of AI contains data breaches faster and saves significant costs

IBM Big Data Hub

It can determine root cause analysis and the orchestrate next steps based on the knowledge the models have trained on and built based on the threats your organization has faced. UBA’s Machine Learning Analytics add-on extends the capabilities of QRadar by adding use cases for ML analytics.