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Accelerating your transition from traditional BI to advanced analytics with data intelligence

Collibra

What is advanced analytics? The term “advanced analytics” gained widespread recognition in the fields of data analysis and business intelligence (BI) during the early 2000s. Today, advanced analytics encompasses a broad array of techniques and methodologies used to extract deep insights from data.

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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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Past, present and future in a digital transformation journey

OpenText Information Management

According to Gartner, a digital transformation includes information technology modernization, adoption of cloud computing, … The post Past, present and future in a digital transformation journey appeared first on OpenText Blogs. The objective is often tied to cost leadership, increased competitiveness or simply moving into a niche.

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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. So how do you spot this early, and react or even prevent this in a timely and effective manner?

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. Scaling AI in business presents unique challenges: Data accessibility : Fragmented and siloed data stifle advancement. AWS, on the other hand, provides robust, scalable cloud infrastructure.

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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. appeared first on IBM Blog.

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MY TAKE: The no. 1 reason ransomware attacks persist: companies overlook ‘unstructured data’

The Last Watchdog

Typical unstructured data includes a long list of files—emails, Word docs, social media, text files, job applications, text messages, digital photos, audio and visual files, spreadsheets, presentations, digital surveillance, traffic and weather data, and more. But with no orderly internal framework, unstructured data defies data mining tools.