Data Analytics Quiz 1

Quiz 1 Reviewer for DA

Analytics

The extraction of useful business patterns or mathematical decision models from a preprocessed data set.

Data Analytics

The utilization of data to provide timely

Big Data Analytics

Enables new avenues of investigation with potentially richer results and deeper insights by integrating structured and unstructured data with real-time feeds and queries.

Data Stores

Repositories and tools used to manage large volumes of enterprise information

Data Devices

Sources such as smartphones

Data Collectors

Entities (e.g.

Data Aggregators

Organizations that compile and transform data from multiple sources into usable products for analysis or sale.

Data Users and Buyers

Groups (e.g.

Volume (4Vs of Data)

The challenge of storing and processing the enormous quantity of data collected.

Variety (4Vs of Data)

The diversity of data types and structures that analytics tools must process.

Velocity (4Vs of Data)

The increasing speed at which data is generated

Veracity (4Vs of Data)

The reliability and accuracy of data

Target Marketing

Using data mining to segment markets and customize promotional campaigns.

Credit Risk Management

Applying data models to predict a borrower’s ability to repay debt based on demographic and personal data.

Fraud Detection

Using data models to flag anomalous transactions and prevent fraudulent activity.

Healthcare Analytics

Predicting patient health risks using demographic

Sentiment Analysis

Analyzing social media or textual data to gauge public opinion on a topic.

Recommender Systems

Systems that suggest products/services based on consumer behavior data.

Spam Filtering

Using data mining to identify and block malicious messages.

Educational Analytics

Predicting student behavior and improving teaching strategies using data.

Criminal Investigation

Applying data mining to detect crimes and analyze criminal relationships.