Data analysis
Data analysis is the art and science of selecting, normalizing, and modeling data to derive useful information, typically for businesses. This generally involves querying data to identify trends and measure performance.
The discipline of data analysis overlaps significantly with data engineering, data science, and business intelligence. However, data analysis focuses on telling stories through data through reports and and visualizations.
Deeper Knowledge on Data Analysis
Apache Spark
A data processing engine for batch processing, stream processing, and machine learning
Data Products
Ways of making data available
Data Science
The scientific method applied to data analysis
Data Teams
The make up and measures of effective data teams
Data Visualizations
Visualizations that generate insights
DevOps Research and Assessment (DORA)
A research program at Google Cloud, notable for the State of DevOps reports
DORA's Four Key Metrics
The four key metrics for software development team performance, as identified by DevOps Research and Assessment (DORA)
Exploratory Data Analysis (EDA)
Research into an unfamiliar dataset, aimed at pattern discovery, assumption verification, and data summarization
Online Analytical Processing (OLAP)
A technique to create views and calculations from multi-dimensional data
PySpark Recipes for Data Cleansing, Analysis, and Science
Recipes for using PySpark
Python Open-Source Data Libraries
Python libraries commonly used in data science and analysis
SPACE Framework
SPACE Framework to Measure Developer Productivity: Satisfaction, Performance, Activity, Communication
Statistics
The analysis of numerical data
Broader Topics Related to Data Analysis
Business Intelligence
Methods to bridge the gap between data and business
Statistics
The analysis of numerical data