Data Analysis: Introduction
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
Historical Data Transformations
The 1960s saw the first use of the term 'data analysis'. But historical acts, like the 1880 census, took over 7 years to process, highlighting the evolution of data analysis methods through time.
Modern Data Analytics Types
Today, data analysis encompasses descriptive analytics (what happened), diagnostic analytics (why it happened), predictive analytics (what will happen), and prescriptive analytics (how we can make it happen).
Big Data's Exponential Growth
90% of the world's data has been generated in the last two years. Every day, we create approximately 2.5 quintillion bytes of data, showcasing the explosive growth of data generation.
The Algorithmic Breakthroughs
Algorithms like Google's PageRank and Netflix's recommendation system have revolutionized how we interact with information, making data analysis critical for user experience and business models.
Data Analysis in Healthcare
Predictive analytics in healthcare can anticipate outbreaks, avoid preventable diseases, and improve the quality of life by mining data to find trends that can lead to enhanced patient care.
Challenges in Data Privacy
With great power comes great responsibility. The rise of data analysis has led to significant data privacy challenges, with regulations like GDPR being implemented to protect personal information.
What is data analysis primary goal?
Collection and storage of large datasets
Discovering information, informing conclusions
Programming algorithms for businesses
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