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

IBM Big Data Hub

For example, if a user’s email is down, they submit a ticket to IT. 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. Process mining is an ideal solution to start planning for automation.

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3 new steps in the data mining process to ensure trustworthy AI

IBM Big Data Hub

Often the bias creeps in through training data and then is amplified and embedded in the model. To help data scientists reflect and identify possible ethical concerns the standard process for data mining should include 3 additional steps: data risk assessment, model risk assessment and production monitoring. Data risk assessment.

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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.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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

IBM Big Data Hub

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. One challenge in applying data science is to identify pertinent business issues.

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Top GRC Tools & Software for 2021

eSecurity Planet

Data privacy regulations like the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) can be hard to navigate for businesses of any size, but GRC tools can simplify and streamline compliance with all of the requirements. Contents: Top GRC tools comparison. Top GRC tools comparison.