Week 1: Understanding Services
INFS 5710: IT Infrastructure for BA
Course Review
Chung-Li Tseng
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IT Infrastructure for BA
Business (Data) Analytics is the ultimate goal, Other courses focus on analytics, taking data for granted.
This course addresses the data issues before one can talk about analytics. That is, this course paves the way to do analytics. For example,
Where are (big) data from?
How are (big) data stored in an organized and efficient fashion?
How can data be retrieved?
The project let you experience how data and analytics are closely tied.
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Assessment
Three home assignments (programming) 15%
One big project (group, ≤ 3 people) 30%
Project (Big data analytics)
Final exam (will not include lab material) 45%
Lab participation 10%
TOTAL 100%
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In the Lab
Software installation and basic queries (I)
Basic queries (II)
Display queries – Hw 1
SQL Joins – Hw 2
Subqueries – Hw 3
Set Operators
Oracle & Data Warehouse
Data cleaning, SAS EG Features – Project
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In the Lectures
Database Systems and Data Models (Ch 1, 2)
Relational DB Model & ER Modelling (Ch 3, 4)
Advanced Data Modeling (Ch 5)
Normalization of Data Tables (Ch 6)
Business Intelligence & Data Warehousing (Ch 13)
Database security (Guest lecture)
Distributed database management (Ch 12)
Big Data and NoSQL (Ch 14)
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Ch 3: Relational DB
That relations are logical constructs composed of rows (tuples) and columns (attributes)
Keys: super key, candidate key, primary key, foreign key, secondary key
Integrity rules (entity integrity, referential integrity)
Relationships – 1:1, 1:M, & M:N
Changing a M:N relationship to two 1:M relationships
Control data redundancy through the use of foreign keys
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Ch 4: ER Modeling
ERD components: entities (tables), attributes (columns), relationships (association between tables)
Attributes: composite attribute, simple attribute, single-valued attribute, multivalued attribute, and derived attribute
Relationship: Connectivity and Cardinality
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Ch 5: EER Modeling
Specialization Hierarchy: entity subtype and supertype
Desirable Primary Key Characteristics
Maintaining History of Time-Variant Data (historical data stored in another table)
Fan trap
Tradeoff of redundancy
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Ch 6: Normalization
About the normal forms 1NF, 2NF, 3NF, BCNF,
and 4NF
How normal forms can be transformed from lower normal forms to higher normal forms
That some situations require denormalization to generate information efficiently
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Ch 13: Business Intelligence
BI is the old BA
From operational data to decision support data.
The evolution of BI
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Ch 13: Data Warehouse
What star schemas are and how they are constructed
Normalize fact tables, denormalize dimension tables.
Use partition, replication, and periodicity to improve the performance of star schemas.
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Database Security
CIA Triad: Confidentiality, Integrity, and Availability
Risk Management – mitigation, avoidance, transference, acceptance
Database security: to protect (i) data in databases, (ii) database management system, (iii) all applications connected to database, and (iv) database server and associated infrastructure
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Ch 12: Distributed Database
Data and processing functions are distributed among several sites
Advantages: data is near the site of demand; faster data access; faster data processing; growth facilitation; improved communication; reduced operating costs; user-friendly interface; and higher reliability of single-point failure
Distributed database design: data fragmentation, data replication, and data allocation
CAP Theorem: consistency, availability, and partition tolerance
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Ch 14: Big Data & NoSQL
3Vs of big data: volume, variety, velocity
Solution for scaling out – distributed storage
Hadoop framework: Hadoop distributed file system and MapReduce
Four categories of NoSQL products:
Key-value (KV) databases
Document databases
Column-oriented databases
Graph databases
Take-Home Final Exam
Final exam: 9 am on Saturday 27 Nov 2021
Duration: 24 hours, open book
Two essay questions (No SQL coding)
Lecture (including the guest lecture; for the guest lecture, read lecture slides; for other lecture topics, read the textbook & slides)
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Final Exam Consultation
Final Exam Consultation Hours:
Email
Meeting via Teams:
Tu and Fri: 2:00 – 3:00 pm (please email in advance)
Or by appointment
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Top Soft Skills for Programmers
Communication
Organizational skills
Teamwork
Punctuality
Critical thinking
Social skills
Creativity
Interpersonal communication
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Adaptability
Growth mindset
Friendly personality
Proper rapport
Good Luck to Your Final Exam
Before you leave…
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Step 1: Take out your device, phone or laptop
Step 2: look for your email from
or find the link from Moodle
or login directly to dashboard
http://myexperience.unsw.edu.au
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