Data Analytics Week 1

This set of vocabulary flashcards covers essential terms and concepts related to advanced data analytics, as discussed in the introductory lecture.

Big Data

High volume, high velocity, and high variety information asset that requires new forms of processing to enable enhanced decision making.

Structured Data

Data that has a predefined data model and follows a specific schema, such as relational databases.

Unstructured Data

Data that does not have a predefined data model; includes formats like text, images, and videos.

Semi-Structured Data

Data that does not reside in a relational database but has some organizational properties, such as JSON or XML.

Data Warehouse

A centralized repository that stores large amounts of structured data for analytics and reporting.

NoSQL Databases

Non-relational databases designed to handle unstructured and semi-structured data.

Hadoop

An open-source framework for distributed storage and processing of large datasets.

Azure

A cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services.

IoT (Internet of Things)

A system of interrelated devices that can collect and exchange data over the internet.

Cloud Computing

The on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user.

Real-Time Data

Data that is delivered immediately after collection without delay.

Data Analytics

The science of analyzing raw data to make conclusions about that information.

Batch Processing

A processing method where data is collected over a period of time and then processed together.

Data Mining

The process of discovering patterns and knowledge from large amounts of data.

Data Visualization

The graphical representation of information and data.

Data Governance

The overall management of data availability, usability, integrity, and security in an organization.

Machine Learning

A subset of artificial intelligence that focuses on building systems that learn from and make decisions based on data.

Analytics Ecosystem

A combination of data sources, data tools, and analytical processes that organizations use to derive insights.

Privacy Concerns

Issues that arise regarding the protection and proper use of personal data.

Midterm Exam

An examination administered midway through an academic course.

Final Exam

The concluding examination at the end of an academic term.

Quizzes

Short assessments that help students review and reinforce learning.

Collaborative Projects

Group projects that require students to work together to achieve a common goal.

Data Clusters

Groups of computers that work together to process and analyze large datasets.

Data Pipelines

A series of data processing steps that move data from one system to another for analysis.

Business Intelligence (BI)

Technologies and strategies used by enterprises for data analysis of business information.

Azure Stream Analytics

A real-time analytics service that helps process streaming data from various sources.

Transactional Data

Data that is generated from transactions and is typically associated with business operations.

Non-Transactional Data

Data that does not arise from transactions and can be processed at a later time.

Sub-Transactional Data

Data related to actions that don't require immediate action and can be processed later.

Cloud Analytics

The analysis of data that is stored in the cloud, leveraging cloud computing resources.

Scalability

The capability of a system to handle a growing amount of work or its potential to accommodate growth.

Data Integration

The process of combining data from different sources into a unified view.

Data Cleaning

The process of correcting or removing incorrect, corrupted, or irrelevant data.