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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

Data platform architecture has an interesting history. A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution.

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Re-evaluating data management in the generative AI age

IBM Journey to AI blog

For example: Validating and creating data protection capabilities : Data platforms must be prepped for higher levels of protection and monitoring. Data discovery and cataloging tools can assist but should be augmented to make the classification specific to the organization’s understanding of its own data.

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

IBM Journey to AI blog

Watsonx.data will be core to IBM’s new AI and Data platform, IBM watsonx, announced today at IBM Think. Supporting the data management life cycle According to IDC’s Global StorageSphere, enterprise data stored in data centers will grow at a compound annual growth rate of 30% between 2021-2026. [2]

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Google AI Introduces Croissant: A Metadata Format for Machine Learning-Ready Datasets

Marktechpost

Even among datasets that include the same subject matter, there is no standard layout of files or data formats. This obstacle lowers productivity through machine learning development—from data discovery to model training. Taken as a whole, these enhancements significantly lessen the load of data development.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Your data strategy should incorporate databases designed with open and integrated components, allowing for seamless unification and access to data for advanced analytics and AI applications within a data platform. This enables your organization to extract valuable insights and drive informed decision-making.

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What is ETL? Top ETL Tools

Marktechpost

assists e-commerce businesses in creating a 360-degree perspective of their customers, creating a single source of truth for data-driven choices, enhancing consumer insights through improved operational insights, and boosting ROI. An online SQL client, a cloud data backup tool, and an OData server-as-a-service option are also included.

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Top 30 Artificial Intelligence (AI) Tools for Data Analysts

Marktechpost

Tableau Tableau is well known for its user-friendly data visualization features, which let users make dynamic, interactive dashboards without knowing any code. Ask Data, an AI-powered element of the tool, allows users to ask questions in natural language and instantly get visual insights.