IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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How to Learn Machine Learning

APRIL 26, 2025

Data Storage and Management Once data have been collected from the sources, they must be secured and made accessible. The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark).

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ODSC - Open Data Science

MARCH 5, 2025

From the Early Days of Data Science to Todays Complex Ecosystem Marcks journey into data science began nearly 20 years ago when the field was still in its infancy. In the early 2010s, the rise of Hadoop and cloud computing transformed the industry, introducing data practitioners to new challenges in scalability and infrastructure.

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Pickl AI

APRIL 21, 2025

Key Takeaways Big Data focuses on collecting, storing, and managing massive datasets. Data Science extracts insights and builds predictive models from processed data. Big Data technologies include Hadoop, Spark, and NoSQL databases. Data Science uses Python, R, and machine learning frameworks.

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Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. These may range from Data Analytics projects for beginners to experienced ones.

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Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

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Pickl AI

NOVEMBER 4, 2024

They introduce two primary data structures, Series and Data Frames, which facilitate handling structured data seamlessly. With Pandas, you can easily clean, transform, and analyse data. Mastering libraries like Matplotlib and Seaborn will empower you to create compelling visualisations that tell a story with data.

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