Difference between revisions of "Data Science"
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| Line 25: | Line 25: | ||
* Projection $\Pi$ | * Projection $\Pi$ | ||
* Join $\bowtie$ | * Join $\bowtie$ | ||
| − | * Duplicate elimination $d$ (Extended RA) | + | * (Extended RA) Duplicate elimination $d$ |
| − | + | * (Extended RA) Grouping and aggregation $g$ | |
| − | + | * (Extended RA) Sorting $t$ | |
Revision as of 22:45, 2 September 2013
The Three V's of Big Data
- Volume: number of rows/objects/bytes
- Variety: number of columns/dimensions/sources
- Velocity: number of rows/bytes per unit time
(Veracity: Can we trust this data?)
Data Model
Three components:
- Structures
- Constraints
- Operations
What is a database? A collection of information organized to afford efficient retrieval.
Why do we need a database?
- Sharing
- Data model enforcement
- Scale
- Flexibility
Relational Algebra
Operations
- Union $\cup$, intersection $\cap$, difference $-$
- Selection $s$
- Projection $\Pi$
- Join $\bowtie$
- (Extended RA) Duplicate elimination $d$
- (Extended RA) Grouping and aggregation $g$
- (Extended RA) Sorting $t$