DAY 1 - chp.1 Flashcards
(26 cards)
Define CRISP-DM
Cross-industry Standard Process for Data Mining
Define Business/data Analytics
Using data to enable decision making
Importance of Business/data analytics
Decision makers can get valuable insight that help them make better & more informed decisions by analyzing historical and current (real time) data
What’s the systematic approach to CRISP-DM
business understanding –> Data understanding –> Data preparation –> modeling –> evaluation –> communication
what are the learning objectives of CRISP-DM
frame business problem as a decision/question (identify required data elements). Develop an understanding of the data in a stimulated situation to describe the data and perform simple statistical analysis. building a spreadsheet/R model to solve a business problem. evaluate and communicate your analysis results (applying CRISP-DM + visualization principles)
What are the Data Analytics stages/types (name in higher proactive decisions making + analytics sophistication)
- Data Management
- Descriptive analytics
- Diagnostic analytics
- predictive analysis
- prescriptive analytics
Define Data management
process of collecting, organizing, storing, and ensuring the quality + security of data. it forms essential groundwork for effective data analytics
Define Descriptive analytics
The initial stage of data analysis that focuses on summarizing + presenting historical data to provide insights into what has happened in the past. (mean, average, medians).
Define Diagnostic Analytics
Data analysis that focuses on understanding why certain events/trends occurred in the past. it helps uncover the root causes behind pattern/trends in financial data.
Define Predictive Analytics
Data analysis technique that uses historical data + statistical algorithm to estimate events’ probabilities + predict future outcomes. (what may happen in the future)
Define Prescriptive analytics
advanced form of data analysis that predicts future outcomes + recommends specific actions/decision to achieve the desired financial/business objective.
What is CRISP-DM used for?
It is a process that data analysts/scientists use to approach data analytics problems
Define business understanding in CRISP-DM
business wants to understand/gain insight on their customers for a specific area (eg. customer satisfaction)
Define Data understanding in CRISP-DM
Explore/comprehend available data and use that to identify an limitations/issues that need to be addressed
Define Data preparation in CRISP-DM
Clean data by removing irrelevant info, standardizing text formats, + handling missing values (if any). May categorize data into specific topics/themes for easier analysis.
Define Data analysis/modeling in CRISP-DM
apply descriptive anlytic techniques on the prepared data - Calculating summary stats, sentiment analysis, topic analysis.- create different models to answer different questions of the business
Define evaluation in CRISP-DM
check between each model to see which model answers the business problems most satisfactorily.
Define communication in CRISP-DM
analyze results and interpret them in context of the business’s objectives. identify strength/weakness. prepare visualizations/reports to present the findings.
Define summary statistics
calculating average, frequency, distribution
Define Sentiment analysis
using natural language processing techniques to determine sentiments of customer comments (pos/neg/neutral)
Define topic analysis
employ techniques (text mining/clustering) to identify common themes/topics.
Define a circular reference
a cell that directly, or via a chain of other references, refers to itself.
how to force plain text in a cell on sheets
use ‘ or ‘=
Define relative reference in excel
references to values in cells, e.g. A1. The value changes when the referred cell changes.
