Overview of Data Repositories

Question 1

Definition of Data Repository

Answer 1

-general term used to refer to data that has been collected, organized, and isolated
-isolate data, make reporting and analytics more efficient and credible, and serve as a data archive

Question 2

Databases

Answer 2

collection of data (or information) designed for the input, storage, search and retrieval, and modification of data

Question 3

Database Management System (DBMS)

Answer 3

-set of programs that creates and maintains the database
-allows you to store, modify, and extract information from the database using a function called querying

Question 4

Different types of databases determined by (5)

Answer 4

-data type and structure
-querying mechanisms
-latency requirements
-transaction speeds
-intended use of data

Question 5

Relational Databases (RDBMSes) vs flat files

Answer 5

-data organized in tabular format (rows and columns) following a well-defined structure and schema (similar to flat files)
-RDBMSes are optimized for data operations and query involving many tables and much larger data volumes (unlike flat files)

Question 6

Structured Query Language (SQL)

Answer 6

standard querying language for relational databases

Question 7

Non-relational Databases (NoSQL or “Not only SQL”)

Answer 7

-used to process big data
-stores data in a schema-less or free-form fashion

Question 8

3 V’s of Big Data

Answer 8

Volume, Velocity, and Variety (aka scale, speed, and flexibility)

Question 9

Big Data

Answer 9

-cloud computing
-Internet of Things (IoT)
-social media proliferation

Question 10

Data Repository is comprised of

Answer 10

-a small or large database infrastructure with one or more databases that collect, manage, and store data sets

Question 11

Data Repository uses

Answer 11

-used in business operations or mined for reporting and data analysis

Question 12

Data Warehouse

Answer 12

works as a central repository that merges information coming from disparate sources and consolidates it through the ETL process into one comprehensive database for analytics and business intelligence

Question 13

ETL process

Answer 13

-the extract, transform, and load process
Extract data from different data sources
Transform data into a clean and usable state
Load data into enterprise’s data repository

Question 14

Data Warehousing and Data Marts were historically

Answer 14

relational as much of traditional enterprise data resided in RDBMes

Question 15

However, Data Warehousing and Data Marts are now

Answer 15

now include non-relational data repositories (with emergence of NoSQL technologies and new data sources)

Question 16

Big Data Stores

Answer 16

-data repository that includes distributed computational and storage infrastructure to store, scale, and process very large data sets