Austin Chia's Blog Posts

Austin Chia is a data analyst, analytics consultant, and technology writer. He is the founder of Any Instructor, a data analytics & technology-focused online resource. Austin has written over 200 articles on data science, data engineering, business intelligence, data security, and cybersecurity. His work has been published in various companies like RStudio/Posit, DataCamp, CareerFoundry, n8n, and other tech start-ups. Previously worked on biomedical data science, corporate analytics training, and data analytics in a health tech start-up.

Business Intelligence (BI): What It Means for Your Organization
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8 Minute Read

Business Intelligence (BI): What It Means for Your Organization

Learn how BI transforms raw data into actionable insights to drive decisions, boost efficiency, and enhance ROI.
Data Science vs. Data Analytics: Key Differences
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7 Minute Read

Data Science vs. Data Analytics: Key Differences

Don’t be confused! Data science and data analytics are different concepts. Learn all about it here, so you’ll know exactly how they can work together.
Top 6 Data Analysis Techniques Used by Pro Data Analysts
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5 Minute Read

Top 6 Data Analysis Techniques Used by Pro Data Analysts

Data analysis is important, but how do you get started? These top techniques, used by professional data analysts, will help you get the most value out of your data.
Data Warehouse vs. Database: Differences Explained
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6 Minute Read

Data Warehouse vs. Database: Differences Explained

Understand how databases and data warehouses work, how they vary and when to use which – all in this beginner’s guide to data warehousing and databases.
Big Data Analytics, Explained
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9 Minute Read

Big Data Analytics, Explained

Unlock insights from vast datasets with big data analytics. Explore real-life applications, tools, techniques, benefits, and challenges in this comprehensive guide.
Open Neural Network Exchange (ONNX) Explained
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4 Minute Read

Open Neural Network Exchange (ONNX) Explained

ONNX is an open-source format that engineers and ML experts use in their ML models to ensure interoperability and model portability across ML and AI frameworks.