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Marketing analytics > Week 2 - Introduction to Data Technologies & Analytical Tools > Flashcards

Week 2 - Introduction to Data Technologies & Analytical Tools Flashcards

1
Q

Structured data

A

easily searchable by basic algorithms

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2
Q

Unstructured data

A

no pre-defined data model or not organized in a pre-defined manner

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3
Q

Forms of unstructured data

A

Verbal data
* spoken(eg,acoustic characteristics)
* written(eg,text,symbols)
Non-verbal data
* human (eg, facial or gestural cues)
* non-human (eg, geographic)

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4
Q

Feature of data

A
  • Data is never entirely structured or unstructured
  • Should be rather understood as a continuum
  • Location of data unit on continuum determined by ease with which structure can be added to each data unit at the time of data collection.
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5
Q

Unstructured Analysis Methods

A

Highly unstructured data
- text mining
- social network analysis
- sentiment analysis
- machine learning

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6
Q

Structure data analysis method

A

Highly structure data
* Factor Analysis
* Cluster Analysis
* Linear & Logistic Regression
* Customer Lifetime Value Analysis
* RFM Analysis

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7
Q

Types of Analytical Tools

A

Dashboard Tools
Spreadsheet Tools
Programming Tools

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8
Q

true or false : Dashboard Tools are suitable for visualizing both structured & unstructured data

A

True

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9
Q

What is a Dashboard Tools

A

A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance”

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10
Q

Goal of Dashboard tool

A

Monitoring the health of a firm

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11
Q

Spreadsheet tools

A

Interactive software application for structuring transforming analysing and storing data in rows and columns

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12
Q

Dashboard Tools: Benefits

A
  • Help managers and staff make decisions
  • Reduce time spent on information retrieval & reports
  • Use a single tool to aggregate data from multiple sources
  • Reduced need for technical resources
  • Potential to supply data or information in real-time
  • Ability to implement statistical criteria
  • Ability to trigger alerts to individuals and share information
  • Immediacy of data analysis with ability to drill-down
  • Possibility of adding notes, events and corrective action
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13
Q

Popular Dashboard Tools for Marketing Purposes

A

Tableau
Google analytics
Bluekai
Power BI

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14
Q

True or False : spreadsheet is particularly suitable for rather unstructured data

A

False : it is suitable for structured data

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15
Q

True or false : Programming Tools suitable for both structured & unstructured data

A

true

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16
Q

Programming vs Statistical programming

A

Programming is the process of solving a given problem using executable computer algorithms, well-defined procedures for solving problems.

Statistical programming is the process of solving data-related problems using executable computer algorithms

One is for solving problem other is data related problem

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17
Q

Programming language

A

a formal set of instructions that can be used to produce various kinds of data output

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18
Q

Programming Tools

A

a software package that allows the execution of a programming language

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19
Q

Programming Code

A

statements written in a particular programming language

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19
Q

Programming Code

A

statements written in a particular programming language

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20
Q

Statistic Programme or Software

A

specialized computer programmes which allow for the collection, organisation, statistical analysis, and interpretation of data.

21
Q

Example of programming tool for accessing data

A

Relational database management systems:
MySQL
SQL server
Oracle Database

22
Q

Example of Programming Language for accessing data

A

SQL

23
Q

Example for programming language for Analysing Marketing Data

A

Java
phython
R

24
Q

Example for programming tools for Analysing Marketing Data

A

SPSS
R STUDIO
KNIME

25
Q

Relational Database Management Systems (RDBMS)

A

A relational database refers to a database that stores data in a structured format, using rows and column (essentially a set of tables)

26
Q

All RDBMS use the same programming language: WHAT IS IT ?

A

SQL (Structured Query Language)

27
Q

Relational database management system makes it easy to locate and access specific values within the database by using what ?

A

unique key

28
Q

SQL is useful for what type of data

A

structured data

29
Q

Feature of SQL

A

Lightweight, declarative language, relatively easy to learn

30
Q

Advantages of SQL

A

High Speed
No Coding Required:

31
Q

Disadvantages of SQL

A

Difficulty in Interfacing
More Features Implemented in Proprietary Way

32
Q

Most Popular Relational Databases Using SQL

A

ORCALE DATABASE
Microsoft SQL SERVER
POSRGRE SQL
MY SQL

33
Q

ORCALE DATABASE

A
  • Most common
  • Expensive, full-service option
  • Runs across 9 different operating systems
  • Supports over 25+ programming languages
  • Used by large corporations
34
Q

Microsoft SQL SERVER

A
  • Only available on Windows computers
  • Highly sophisticated queries
  • Enterprise-level database
35
Q

My SQL

A
  • Less complex
  • Open-source
  • Used for smaller operations and tasks
  • Excellent for CMS sites and blogs
36
Q

Postgre SQL

A
  • Open source
  • Uses other programming languages (e.g., Python) in addition to SQL
  • Default database for macOS Server
37
Q

Benefits of RDBMS & SQL for Marketers

A

● RDBMS stores large amounts of structured data on customers (demographics, consumer behavior, etc.), products, and employees
● SQL helps to access, link, and retrieve valuable customer information to generate strategic insight
● Information in RDBMS can be easily transformed and enriched through SQL in real time
● This insights help firms to make data-driven decisions from the analysis of existing data (e.g., to support marketing campaigns, segment & target customers, monitor employee performance, etc.)

38
Q

Relational vs non relational database

A

NOSQL database : A non relaitonal database does not incorporate the table model. Instead data can be stored in a single document file (Resembles a folder). Suitable for semi structured and unstructured data.

SQL database : A relational data base organises data field into defined column. (Resembles a phonebook). Suitable for structured data

39
Q

NoSQL Databases: Benefits for Marketers

A
  • Flexibility
  • Relatively inexpensive
  • Affordability
  • Accessibility
  • Scope
  • Effort
40
Q

NoSQL Databases: Benefits for Marketers

A
  • Flexibility
  • Relatively inexpensive
  • Affordability
  • Accessibility
  • Scope
  • Effort
41
Q

Types of No-SQL Databases

A

Key-Value Stores
Document Database
Wide Column Database
Graph Database

42
Q

Key-Value Stores (Advantages and Disadvantages)

A

Advantages
* Scalability, reliability, simplicity, speed
Disadvantages
* Not adequate for complex applications

43
Q

Document Databases (Advantages and Disadvantages)

A

Advantages
* Documents can have data with different structures, fast write performance and fast queries
Disadvantages
* Most suitable for data that is document- oriented, but still somewhat structured

44
Q

Wide Column Stores

A

Advantages:
* Very efficient in data compression, scalability, fast load & queries
Disadvantages:
* Moderate flexibility, low complexity Dr Ilias Danatzis

45
Q

Graph Databases

A

Advantages:
* Completely flexible structure
* Saves the relationships (edges) that connects
data; particularly suitable for relationship- related queries (e.g., social media data)
Disadvantages:
* Variable performance & scalability

46
Q

Specific Programming Languages & Tools: Python, Advantages and Disadvantages

A

Advantages
* A growing community that includes computer science software engineers and programmers
* There are more opportunities to take advantage of artificial intelligence (i.e. machine learning)
* Flexibility; e.g.,data analysis can be integrated with website and mobile apps or a production database
* Ready for programming tasks besides analysing data

Disadvantages
Less efficient for statistical computations (it was original built for non-statistical purposes)
* Has less appealing data visualization built in
* Fewer packages

47
Q

Specific Programming Languages & Tools: R & RStudio Advantages and Disadvantages

A

Advantages

  • Made for data-oriented projects in general
  • Handles Big Data (very large datasets)
  • Large number of ready-made packages
  • Built-in ways to professionally visualize data
  • Developed by data scientists, important for marketing analytics
  • Large community that provides support through mailing lists, documentation and blogs
  • Supported by a well-established programming tool (a.k.a. integrated development environment) called RStudio for which there are no close competitors in R and for which Python has no comparative leader

Disadvantages
- Hard to learn, however steep learning curve
- Less efficient for general computations, sometimes due to inefficiently written package

48
Q

Specific Programming Languages & Tools: SPSS Advantages and Disadvatages

A

Advantages
* Very user-friendly
* Easy to learn
* No coding necessary to conduct complex statistical analysis
* In-depth statistical capabilities
* Very good for data manipulation & preparation
* It can easily recode variables and create new variables from existing information
* Can get output in an easy to read form
* Good visualisation of analysis output
* No debugging necessary
* Intuitive command names (mostly)

Disadvantages
* Less used in industry
* Proprietary programming tool (requires
annual licences)
* Less efficient for large datasets
* Limited analysis capabilities for unstructured data

49
Q

Specific Programming Languages & Tools: KNIME (Advantages and Disadvatages)

A

Advantages
* Open source
* Easy to use graphical interface
* Clear view and documentation of data processing across all steps
* Large range of statistical tools
* Suitable to analyse unstructured text data
* Integration of machine learning
* Can be extended through R and Python

Disadvantages
* Ability to handle large amounts of data and performance in processing could be better
* Data visualisation not as well developed as other programs

Marketing analytics (4 decks)

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