Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JANUARY 16, 2024

Cloud-based Data Analytics Utilising cloud platforms for scalable analysis. billion 22.32% by 2030 Automated Data Analysis Impact of automation tools on traditional roles. by 2030 Real-time Data Analysis Need for instant insights in a fast-paced environment. billion Value by 2030 – $125.64

Data Analyst 52

Data Analyst Data Analysis Data Analysis Analytics 52

Pickl AI

NOVEMBER 28, 2024

million by 2030, with a remarkable CAGR of 44.8% Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data. Model evaluation and tuning involve several techniques to assess and optimise model accuracy and reliability.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 10, 2024

from 2024 to 2030, implementing trustworthy AI is imperative. Risk Management Strategies Across Data, Models, and Deployment Risk management begins with ensuring data quality , as flawed or biased datasets can compromise the entire system. The AI TRiSM framework offers a structured solution to these challenges.

AI 52

AI AI Artificial Intelligence Artificial Intelligence 52