B01 Unstructured Data Analytics

Question 1

Define Structured Data

Answer 1

Data that is organized and
stored in a pre-defined
format. Examples include
relational databases,
tabular data (csv or xls),
etc.

Question 2

Define Semi-Structured Data

Answer 2

Data that has a selfdescribing
structure
(usually with tags) but also
doesn’t follow a predefined
format. Examples
include HTML, XML, JSON,
etc.

Question 3

Define Unstructured Data

Answer 3

Data that does not have a
pre-defined data model
and/or format. Examples
include images, text,
audio, video, sensor data,
etc.

Question 4

What is Unstructured Data Analytics?

Answer 4

“Unstructured data
analytics are a set of
techniques focused on
the extraction of useful
insights from data with
unpredictable or
inconsistent form.”

Question 5

Define the Unstructured Analytics approaches we will cover

• Text Analytics

Answer 5

Text Analytics is the process
of extracting high quality
insights from textual data. It
is sometimes referred to as
text mining.

Question 6

Define the Unstructured Analytics approaches we will cover

• Sentiment Analysis

Answer 6

Extracting an author’s emotional

intent from text.

Question 7

Define the Unstructured Analytics approaches we will cover

• Topic Modelling

Answer 7

Discovering the abstract “topics”
that occur in a collection of
documents.

Question 8

Define the Unstructured Analytics approaches we will cover

-Naïve Bayes

Answer 8

Quantifying the probability of
events and how those probabilities
should be revised in the light of
additional information.

Question 9

Define the Unstructured Analytics approaches we will cover

-Support Vector Machines

Answer 9

Separating categories of data by
representing the data as points in
multi-dimensional space.

Question 10

Define the Unstructured Analytics approaches we will cover

-Neural Networks

Answer 10

Recognizing patterns in data by
using a method that loosely models
the neurons in a biological brain.