Lecture 1 Flashcards
Data management
Managing data as a valuable resource (mostly back-end)
Business Intelligence
Transforming data into meaningful information/knowledge to support business decision making (a.k.a. data-driven decision-making). Mostly front-end side.
Data
Items that are the most elementary descriptions of things, events, activities and transactions. Can be internal or external, structured or unstructured.
(un)structured data
Most data is unstructured. During the data preparation, you make unstructured data structured. More and more unstructured data is becoming available over time.
Information
Organised data that has meaning and value.
Knowledge
Processed data or information that is applicable to a business decision problem. It is possible that some companies see certain data as information, where other companies see it as knowledge.
Taxonomy of Business Intelligence
- Descriptive analytics
- Predictive analytics
- Prescriptive analytics
Descriptive analytics
Use data to understand past and present (SQL, OLAP)
Predictive analytics
Predict future behavior based on pas behavior. (Time series, clustering, decision trees, KNN)
Prescriptive analytics
Make decisions or recommendations to achieve the best performance. (Simulation, optimization, Ai)
Business Intelligence = Business Analytics
All decision support systems (DSS)
Business Intelligence (BI) (Process definition)
An umbrella term that combines processes, technologies, and tools needed to transform data into information, information into knowledge, and knowledge into plans that drive profitable business action.
Business Intelligence (BI) (Product definition)
Information and knowledge that enables business decision-making.
Objective of BI Product
Provide historical, current, and predictive views of business operations. Information/knowledge that could relate to:
- Understanding customer preferences.
- Coping with competition.
- Identifying with opportunities.
- Enhancing internal efficiency.
BI Solutions support the BI Process by utilizing BI Tools.
BI Tools & Techniques
- Data warehousing
- Knowledge management
- Query and reporting
- Online analytical processing
- Digital dashboards
- Data, process, and text mining
- Statistics
- Visualisation
Business Intelligence Architecture
Data flows through the veins of the organization.
Business Intelligence Architecture
- Data is ‘produced’ (Business Database)
- Data is assembled, and stored (ETL Staging Area to Data warehouse)
- Data is processed, analyzed and consumed (Dashboards)
OLAP Cubes (Online Analytical Processing)
Numeric (measures) data which can be put in different dimensions, product, time, and location.
Databases
Backbone of business information systems (ERP). Supports decision making at all levels of the organization. Every time you are asked to input data, you’re accessing a database.
Database
A collection of related tables, designed, maintained and utilized by multiple users, with software to update and query the data. Database system consists of:
- Data
- Software
- Hardware
- Users
Database is composed of objects and operations. Objects support operations.
Database management systems (DBMS)
Software that controls the data.
Database system possibilities
Allows users to:
- Organize (CREATE)
- Store (INSERT)
- Update (UPDATE)
- Delete (DELETE)
- Retrieve their data (SELECT)
Table
Structured list of data of a specific type. Each table has a name, and is divided into fields (columns) and records (rows).
Relational database possibilities
Relational databases allow:
- Data to be grouped into tables.
- Sets relationships between tables.
Join
Relationship between two tables using a common field. This is done with a primary key and a foreign key.
Primary key
Fields that uniquely identifies each record in a table.
It consists of one or more attributes that determine other attributes. Key’s role is based on determinations: A -> B, C, D.
- If you know A you can look up B, C and D.
- B, C, D are functionally dependent on A
Composite primary key
When a primary key contains multiple values.
Superkey
Any key that uniquely identifies each row (potential primary key).
Candidate key
Super key without unnecessary attributes.
Foreign key
Attribute whose value matched the primary key values in the related table.
