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

Data Analysis Knowledge Graph