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Companies need help making the dream of digital transformation a reality

IBM Big Data Hub

Organizations can mitigate this scenario by leveraging advanced analytics, artificial intelligence (AI) and machine learning (ML) to build next-generation capabilities today. Dublin-based Glen Dimplex has sales, manufacturing and distribution facilities around the world. This is especially important in customer interactions.

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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time.

Retail 91
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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

The challenge for IT departments working in data science is making sense of expanding and ever-changing data points. However, data scientists should monitor results gathered through unsupervised learning. “Means,” or average data, refers to the points in the center of the cluster that all other data is related to.

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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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Why a governance foundation is vital for cloud data platforms

Collibra

It is because they foster more agile data operations, cut through siloed architectures and unlock the potential of artificial intelligence and machine learning to drive new trusted business insights. . It is important to note that processing unstructured data typically yields outputs that are structured by nature.

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IBM to help businesses scale AI workloads, for all data, anywhere

IBM Big Data Hub

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data? .

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

It’s distributed both in the cloud and on-premises, allowing extensive use and movement across clouds, apps and networks, as well as stores of data at rest. An architecture designed for data democratization aims to be flexible, integrated, agile and secure to enable the use of data and artificial intelligence (AI) at scale.