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Fundamentals of Big Data - Aula 7, DMI

 

Prerequisites: Basic courses in Information and Communication Technologies, e.g., programming, information and coding theory, databases. Basic knowledge of probability theory.

Sillabus and Instructors

1. Algorithms (Eight hours)- R. Giancarlo,

05/02/18 9.30-11.00; 06/02/18 9.30-11.00; 07/02/18 10:00-13:00; 08/02/18 10:00-12:00.

1.a Searching in Small Space

1.a.1 Universal Hash Function

1.a.2 Bloom Filters

1.b Counting in Small Space

1.b.1 Hyperlogaritmic counters

1.b.2 Frequent Elements in Streams

1.b.3 Frequency Moments (outline)

1.c Algorithms in External Memory (outline of Model)

 

 

2. Compression (Six hours)- M. Sciortino.

4/02/18 10:00-12:00; 15/02/18 10:00-12:00; 16/02/18 10:00-12:00

2.a Dictionary-based data compression.

2.a.1 The LZ78 and LZ77 Algorithm

2.a.2 Applications to String alignment and Compressed Full-Text Indexing

2.b Block-sorting data compression

2.b.1 The Burrows-Wheeler Transform

2.b.2 The FM-index

 

 

3. Management (Five hours)- S.E. Rombo

05/02/18 09:30-11:00; 06/02/2018 09:30-11:00

3.a Technologies

3.a.1 Map Reduce, Apache Hadoop, Apache Spark

3.a.2 Programming with Spark (in laboratory)

3.b Storage

3.b.1 NoSQL Databases

3.b.2 Data Warehousing

3.b.2.I Conceptual Modelling

3.b.2.II Logic Modelling

3.b.2.III OLAP

3.c Practice on Business Intelligence (in laboratory)