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Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

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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How the right data and AI foundation can empower a successful ESG strategy

IBM Journey to AI blog

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. It required a different data platform solution. It was Datawarehouse.

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Data Intelligence empowers informed decisions

Pickl AI

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. ” This notion underscores the pivotal role of data in today’s dynamic landscape. So, let’s get started.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

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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. “IBM and Cloudera customers will benefit from a truly open and interoperable hybrid data platform that fuels and accelerates the adoption of AI across an ever-increasing range of use cases and business processes.”

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How to choose the best AI platform

IBM Journey to AI blog

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.