Data science exam 3

What are pivot tables? And how is data stored to be analyzed in a pivot table?

Must be stored in a structure, rows and columns format (a flat file or database table) 

Pivot tables: a table of statistics that summarizes the data of a more extensive table (databases, spreadsheets etc). This summary might include sums, averages, or other statistics which the pivot table groups together in a meaningful way.”

• Uses a flat file structure 

• All related data must be in the same table to be pivoted

Structured data? with examples

• Structured data are recorded as well-defined fields that correspond to distinct variables

• google sheets, microsoft excel files

• Can be displayed in rows and column and relational databases

• Numbers, data and strings 

• Easier to manage and protect with legacy solution 

Unstructured data

• natural languages writing, consist of a mishmash of semantic entities that can differ from an observation to another and it may not be clear what constitutes a separate observation in unstructured data

• email, text files, social media posts, video, images, audio, sensor data etc

• Cannot be displayed in rows and column and relational databases

• Images, audio, video, word processing files, e-emails, spreadsheets, requires more storage

What is sentiment analysis? How does it work?

Sentiment analysis categorizes whether a statement is positive or negative and assigns it a score accordingly 

• Structured data 

• A form of predictive analytics, it predicts a sentiment score that a human elevator would likely give to the statement 

• What is analytics? How is analytics related to Big Data?

Analytics is about extracting information from data by discovering meaningful patterns, but analytics information can have different status with respect to our actions.

Analytics relates to Big Data by providing the tools and techniques (like Apache Hadoop or Spark) to process massive, high-velocity, diverse datasets (structured/unstructured) that are too complex for traditional methods, unlocking insights such as customer behavior, operational efficiency, and future forecasts. 

 What is the difference between descriptive, predictive, and prescriptive analytics?

▪ Give examples of each.

o What are the uses of forecasting? Give an example.

Descriptive analytics summarizes and helps understand past data Descriptive analytics

Predictive analytics predicts values for data points we do not have, if these data points are in the future we call this forecasting Insight

Prescriptive analytics facilitate a decision-making directly by suggesting an action  Foresight

• What is machine learning?

Machine learning is a broad category of techniques to learn model parameters from data so that the model can be used to predict values or classify items, this can be called traditional or discriminative AI

 What is pivot table analysis?

• A data summarization technique that quick;y reorganizes, aggregates and analyzes large datasets in spreadsheets 

 What is an interactive dashboard?

A dynamic data visualization tool that allows users to actively explore, filter, and manipulate data in real time to gain insights.