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10 Must-Have AI Engineering Skills in 2024

Data Science Dojo

From healthcare where AI assists in diagnosis and treatment plans, to finance where it is used to predict market trends and manage risks, the influence of AI is pervasive and growing. As AI technologies evolve, they create new job roles and demand new skills, particularly in the field of AI engineering.

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Characteristics of Big Data: Types & 5 V’s of Big Data

Pickl AI

Summary: This blog delves into the multifaceted world of Big Data, covering its defining characteristics beyond the 5 V’s, essential technologies and tools for management, real-world applications across industries, challenges organisations face, and future trends shaping the landscape.

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A Comprehensive Guide to the main components of Big Data

Pickl AI

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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A Comprehensive Guide to the Main Components of Big Data

Pickl AI

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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What is Data-driven vs AI-driven Practices?

Pickl AI

Summary: The article explores the differences between data driven and AI driven practices. Data-driven and AI-driven approaches have become key in how businesses address challenges, seize opportunities, and shape their strategic directions.

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Big Data as a Service (BDaaS): A Comprehensive Overview

Pickl AI

Summary: Big Data as a Service (BDaaS) offers organisations scalable, cost-effective solutions for managing and analysing vast data volumes. By outsourcing Big Data functionalities, businesses can focus on deriving insights, improving decision-making, and driving innovation while overcoming infrastructure complexities.

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Business Analytics vs Data Science: Which One Is Right for You?

Pickl AI

Summary: Business Analytics focuses on interpreting historical data for strategic decisions, while Data Science emphasizes predictive modeling and AI. Introduction In today’s data-driven world, businesses increasingly rely on analytics and insights to drive decisions and gain a competitive edge. Masters or Ph.D.