Data Analytics

Descriptive analytics

uncovers trends in data sets by asking questions about what happened.

predictive analytics

uses probability analysis techniques and data mining, statistical modeling, machine learning, and deep learning to predict future outcomes given certain conditions.

Prescriptive analytics

predict what, when, and why a given scenario might occur.

sensing, collection, wrangling, analysis, storage

what are the 5 steps of the data project life cycle (in order)?

sensing

first step in the data project life cycle, involves identifying the meaningful data to be collected.

collection

second step in the data project life cycle, involves gathering data.

wrangling

third step in the data project life cycle, involves converting raw data into a user-friendly format.

analysis

fourth step in the data project life cycle, involves examining and analyzing the data.

storage

fifth and last step in the data project life cycle, involves securing and maintaining data for access.

Ask, Prepare, Process, Share, Act

what are the 6-step processes of DDDM (including what is involved with each step?

SQL stands for structured query language. Allows the user to query data contained in a database, filter for specific data and track correlated pieces of data

what does SQL stand for, and what does it allow users to do?

syntax

refers to a set of rules and guidelines that define a specific computer language.

SELECT, FROM, WHERE

--re components of SQL: the most common SQL terms used in queries include?

select, from, where

re Extracting Data from Multiple Fields and Adding Comments to a SQL Query: in order to extract information from multiple tables, the _______________ SQL command is used to indicate multiple fields in conjunction with ______________ and ___________________ to narrow the search and get specific results

Explore data sets for patterns, plan for visuals, create the visuals

what are the three steps used in the data visualization process?

Data anonymization is the process of removing or altering personal information so that the data cannot be traced back to an individual.

PII (Personally Identifiable Information) is any data that can identify a specific person.

Examples: name, address, phone number, email, Social Security number, date of birth.

These are PII elements that have been stripped of identifying details:

Replacing names with ID numbers

Removing addresses or changing them to general regions

Masking phone numbers (e.g., --1234)

Generalizing dates of birth (e.g., “1990s” instead of exact date)

Aggregating data (e.g., “age group 20–30” instead of age 22)

what is data anonymization, and what is PII? --what are common examples of anonymized PII data?

Open Data — criteria to be considered open

For data to be considered open, it must:

Be freely available for anyone to use

Be accessible in a usable, machine-readable format

Allow reuse and redistribution

Have no restrictive licenses, or use an open license (like Creative Commons)

re open data: in order to be considered open, what criteria must data meet?

the process of changing data from one format or structure into another so it can be analyzed, stored, or used properly.

what is data transformation?