IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

DECEMBER 26, 2024

Summary: Big Data revolutionises promotional strategies by enabling personalised, data-driven marketing campaigns. Real-time insights, predictive analytics, and ethical considerations ensure impactful, consumer-focused approaches. Predictive analytics and segmentation optimise targeting and improve campaign success rates.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

OCTOBER 10, 2024

It integrates well with cloud services, databases, and big data platforms like Hadoop, making it suitable for various data environments. Typical use cases include ETL (Extract, Transform, Load) tasks, data quality enhancement, and data governance across various industries.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

Scikit-learn also earns a top spot thanks to its success with predictive analytics and general machine learning. Knowing all three frameworks covers the most ground for aspiring data science professionals, so you cover plenty of ground knowing thisgroup. Kafka remains the go-to for real-time analytics and streaming.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Dataconomy

MARCH 19, 2025

Overview of core disciplines Data science encompasses several key disciplines including data engineering, data preparation, and predictive analytics. Data engineering lays the groundwork by managing data infrastructure, while data preparation focuses on cleaning and processing data for analysis.

Data Science 91

Data Science Citizen Data Scientist Data Scientist Machine Learning 91