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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

23
Q

Example for programming language for Analysing Marketing Data

A

Java
phython
R

24
Example for programming tools for Analysing Marketing Data
SPSS R STUDIO KNIME
25
Relational Database Management Systems (RDBMS)
A relational database refers to a database that stores data in a structured format, using rows and column (essentially a set of tables)
26
All RDBMS use the same programming language: WHAT IS IT ?
SQL (Structured Query Language)
27
Relational database management system makes it easy to locate and access specific values within the database by using what ?
unique key
28
SQL is useful for what type of data
structured data
29
Feature of SQL
Lightweight, declarative language, relatively easy to learn
30
Advantages of SQL
High Speed No Coding Required:
31
Disadvantages of SQL
Difficulty in Interfacing More Features Implemented in Proprietary Way
32
Most Popular Relational Databases Using SQL
ORCALE DATABASE Microsoft SQL SERVER POSRGRE SQL MY SQL
33
ORCALE DATABASE
* Most common * Expensive, full-service option * Runs across 9 different operating systems * Supports over 25+ programming languages * Used by large corporations
34
Microsoft SQL SERVER
* Only available on Windows computers * Highly sophisticated queries * Enterprise-level database
35
My SQL
* Less complex * Open-source * Used for smaller operations and tasks * Excellent for CMS sites and blogs
36
Postgre SQL
* Open source * Uses other programming languages (e.g., Python) in addition to SQL * Default database for macOS Server
37
Benefits of RDBMS & SQL for Marketers
● 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
Relational vs non relational database
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
NoSQL Databases: Benefits for Marketers
* Flexibility * Relatively inexpensive * Affordability * Accessibility * Scope * Effort
40
NoSQL Databases: Benefits for Marketers
* Flexibility * Relatively inexpensive * Affordability * Accessibility * Scope * Effort
41
Types of No-SQL Databases
Key-Value Stores Document Database Wide Column Database Graph Database
42
Key-Value Stores (Advantages and Disadvantages)
Advantages * Scalability, reliability, simplicity, speed Disadvantages * Not adequate for complex applications
43
Document Databases (Advantages and Disadvantages)
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
Wide Column Stores
Advantages: * Very efficient in data compression, scalability, fast load & queries Disadvantages: * Moderate flexibility, low complexity Dr Ilias Danatzis
45
Graph Databases
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
Specific Programming Languages & Tools: Python, Advantages and Disadvantages
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
Specific Programming Languages & Tools: R & RStudio Advantages and Disadvantages
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
Specific Programming Languages & Tools: SPSS Advantages and Disadvatages
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
Specific Programming Languages & Tools: KNIME (Advantages and Disadvatages)
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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