Feel free to add your keywords. Here's a start:

The alphabet:

• Algorithm (also: API, accountability)
• Big data
• Computational complexity (also: clustering, cross-validation, computer science, confidence intervals, compression, collaborative filtering)
• Databases (also: data mining, dashboards, data dictionary, decision science)
• Experimental design (also: entropy, encryption)
• Fraud detection
• Graph databases (also: goodness-of-fit, geospatial data)
• Hadoop (also: hypothesis testing, high performance computing aka HPC)
• Information theory (also: inventory management)
• Java (also: javascript)
• Knowledge discovery (also: Kaggle, K-mean, K-nn, KPI)
• Logistic regression (also: lift)
• Machine learning (also: map-reduce, modeling, metrics)
• NoSQL (also: network topology)
• Optimization (also: operations research, overfitting)
• Predictive modeling (also: Python, Perl)
• Quality as in data quality or quality assurance (also: query)
• Recommendation engine (also: R programming language, R-squared)
• Statistics (also: scoring, segmentation, search technology)
• Taxonomy creation (also: topology)
• User profiling
• Visualization
• Web analytics (also: web crawling)
• XML
• Yottabyte = 10^24 bytes = 1 trillion terabytes, the largest information unit (also: yield optimization)
• Z-score (also: Z-test, Z-transform)

Other links

• From the trenches: 360-degree data science
• 17 short tutorials all data scientists should read (and practice)
• 10 types of data scientists
• 66 job interview questions for data scientists
• Data Science Certification
• Update about our Data Science Apprenticeship
• Our Wiley Book on Data Science
• Data Science Top Articles
• Our Data Science Weekly Newsletter
• Practical illustration of Map-Reduce (Hadoop-style), on real data
• What makes up data science?
• Data science webinars
• Data science competition