MIS Chapter 5 Databases

How is Big Data different than “a really big data set”?

Big Data includes the 3 Vs (volume, velocity, and variety). A big data set may only involve a large volume.

What are the 3 Vs

volume, velocity, variety

Volume

sheer amount of data being generated stored (petabytes of clickstreams)

Velocity

speed @ which data is produced, transmitted, processed (social media posts per second)

Variety

diversity of data types of formats, from structured tables to unstructured text, images, videos, etc.

What is Business Intelligence?

foundation; collecting & organizing historical info, dashboard, reports, visualizations, KPIs, more descriptive & retrospective

What is Business Analyst?

next level up; statistical analysis & modeling, identification of patterns & trends, data mining, machine learning, forecasting, recommending, more predictive & prescriptive

How is Business Intelligence similar to Business Analytics?

both use data to support decision-making

How is Business Intelligence different from Business Analytics?

BI explains what happened, BA explains what might happen and what should be done

Why might data lie dormant in an organization?

inaccessible, incompatible, otherwise interpreted (lost, unknown, unaddressed)

How else might data fail to provide a sustainable competitive advantage?

competitors can access & copy same data, algorithms & formulas. data also can’t predict every market trend change in consumer behavior.

What are some common sources of data in an org?

transaction processing systems and/or apps, enterprise software, surveys, external sources

What are some disadvantages of file processing?

program data dependence, data redundancy/inconsistency, limited sharing & analysis, long development times, excessive program maintenance

program data dependence

each application must maintain its own data formats, metadata, and processing routines
program data independence: the DBMS manages metadata & data access, so applications do not need to handle these details themselves

data redundancy

multiple systems keep separate copies of the same data, wasting storage
minimizes unnecessary duplications

data inconsistency

separate copies may not be updated together, compromising data integrity
centralized, controlled data improves consistency & integrity

limited sharing & analysis

data is stored in seperate files and formats, making it difficult to share and analyze
a central repository allows different users to access shared data through different views

long development times

programmers must design their own file formats and data processing routines
standardized data management improves application development producitvity

excessive program maintenance

changes to file formats or data require changes to individual programs
DBMS manages data access & formats, reducing maintenance work

what costs are associated w/ database approach?

up-front costs: installation, conversion & org conflict
on going costs: specialized personnel backup/ recovery resources

entities / tables/ files (categories)

list of data, arranged in columns (field) & row (record) (ex: students)

instances / records/rows (individual entries)

single instance of whatever the table keeps track of (ex: Peter)

attributes / fields/columns (characteristics)

each category of data contained in a record

primary key

attribute or attributes that uniquely identify individual instances or an entity type

simple key (primary key)

single attribute that identifies a unique record

composite key (primary key)

combo of attributes that collectively identifies a unique record

candidate key

any attribute that could be a primary key

relationships

link between 2 entities

relationships 1:1

one record relates to one record

relationships 1:M

one record relates to multiple records

relationships M:M

multiple records relate to multiple records; requires an associative entity

mandatory relationships

relationship must exist (minimum 1)

optional relationships

relationship doesn’t have to exist (minimum 0)

What is an associative entity?

both entities (i.e they have attributes) and relationship (i.e they link entities together)

Entity-Relationship Diagram

simultaneously depicts the tables, attributes, relationships & relationship cardinality of an org database

Beyond databases, what sorts of data structures/assets are necessary to harness Big Data?

data warehouses, data mart, data lake, data cloud

data warehouses

set of databases designed to support decision making in an org

data mart

databases focused on addressing concerns of a specific prop or BU

data lake

catch all term storage & access technologies used in Big Data, allow for storage of data in both structured as well as raw or unfiltered formats

data cloud

provision of any of the above as a service via an online platform