Chapter 17 DBMS

Is data a source of competitive advantage?

YES - under the condition that it’s VRIS.

• However, advantages based on capabilities and data that others can acquire easily will be short-lived

When might data not yield sustainable advantage?

• publicly available

• can be recreated

Are advantages based on analytics and modeling potentially sustainable? Why or why not?

YES - if they result in differentiation as opposed to just operational efficiency.

• Advantages based on capabilities others can acquire will be short-lived

Database

Single table or a collection of related tables

Serves many applications by centralizing data and controlling redundant data

DBMS

Software for creating, maintaining, and manipulating data

◦ Known as database software

• Interfaces between applications and physical data files

• separates logical and physical views of data

• solves problems of traditional file environment

  • controls redundancy

  • eliminates inconsistency

  • uncouples programs and data

  • enables organization to centrally manage data and data security

Data Hierarchy

BBFRFD

• bit

  • 0 and 1, up and down

• byte

  • Collection of 8 bits, make up every character, number, or symbol

• field

  • group of bytes

• record

  • collection of related fields

• file

  • collection of related records

• database

  • collection of related files

Data warehouse

• Stores current and historical data from many core operational transaction systems

• Consolidates and standardizes information for use across enterprise

  • data cannot be altered

• Data warehouse system will provide query, analysis, and reporting tools

Data marts

◦ Subset of data warehouse

◦ Summarized or highly focused portion of firm’s data for use by specific population of users

◦ Typically focuses on single subject or line of business

Relational DBMS

◦ Represent data as 2-D tables called relations or files

◦ Each table contains data on entity and attributes

Capabilities of DBMS

DDL, Dictionary and DML

What role do technology and timing play in realizing advantages from the data asset?

• moving early can be the difference between a dominating firm and an also-ran

  • if more data brings more accurate modeling

• advantages based on capabilities and data others can acquire will be short-lived

• technology that cannot be easily replicated or imitated is KEY is distinguishing operationally effective tech from those efforts that can yield true strategic positioning

Why would a firm use a loyalty card?

What is the incentive for the firm?

What is the incentive for consumers to opt in and use loyalty cards?

What kinds of strategic assets can these systems create?

• Loyalty card is a system that provides rewards and usage incentives

  • When customers use card, they give up info about themselves in exchange for a financial incentive

  • FIRM: collect personalized info about customer purchases and improve targeting

  • CUSTOMER: financial incentives; points or discounts

  • Switching costs

How can firms leverage customer data to better serve you and improve their performance?

• product purchase reminder

• new product/service availability

• coupons/other incentives

• product upgrades/offers

data security

be concerned

Big Data

Refers to the vast amount, volumes, and types of data that a company can collect and process using increasingly high-tech systems

• measured in zettabytes (2 raised to the 70th power)

V3 in big data

Volume

Variety

Velocity

—> leads to complexity

3 more big data sources

Complexity

• different standards, rules, and storage formats can exist with each asset type

Veracity

• messiness/trustworthiness of the data. big data = less control over quality and accuracy

  • data cleansing is an important component

Value

• unless we can turn big data into value, having access to it is useless

bottom line of big data

answers become a COMMODITY

• real value lies in asking good questions

Data Analytics

• using math and statistics to derive meanings from data in order to make better informed decisions

• combo of computer technology, management science techniques, and statistics to solve real problems

Descriptive analytics

Essentially, deals with analysis of historic data

Dashboard, scorecards, and alerts

• help summarize past events and tell us what happened (NOT why it happened or what might change)

Predictive analytics

use past data to model future outcomes

ex) predicting how customers will respond to a promotion event or advertising campaign

Descriptive analytics in excel

To summarize and organize data to make it easier to understand what has already occurred

• Data visualization

• Dashboards and scorecards

• Descriptive statistics

hindsight

Predictive analytics in excel

enablers:

• data mining

• text mining/web mining

• forecasting (ie. time series)

  • regression analysis

insight

Prescriptive analytics

Chooses techniques like optimization to help managers

• answers the Q: “What should we do today in order to achieve a specific purpose”

• ex) optimal allocation among stock investments to maximize ROI or minimize risk?

  • finds best possible decision

  • ex) excel solver; simulation

foresight

bottom line of data analytics

combining big data and effective analytics gives the company a key competitive advantage

table: grid of columns and rows

rows/tuples: records for different entities

fields/columns: defines data table can hold (attribute for entity)

primary key: field in table used to uniquely identify a table

foreign key: primary key used in second table as look-up field to identify records from original table

data definition language (DDL)

specifies structure of database content, used to create tables and define characteristics of fields

data dictionary

automated or manual file storing definitions of data elements and their characteristics

data manipulation language

used to add, change, delete, retrieve data from database

• SQL (structured query language)

• Microsoft Access uses tools for generation SQL

Many DBMS have report generation capabilities for creating polished reports

entity-relationship diagram

• used by database designers to document data model

• illustrates relationships between entities

one-to-one

each instance in the relationship will have exactly one related instance

ex) every employee is assigned to one parking space

one-to-many

an instance on one side of the relationship can have many related instances, but an instance on the other side will have a maximum of one related instance

ex) a product line can contain many products

many-to-many

Instances on both sides of the relationship can have many related instances on the other side

ex) many students register for many courses

• NOT ALLOWED bc redundancies

• To break a many-to-many entity, introduce a third entity between

text mining

extracts key elements from lagre unstructred data sets

ex) stored emails

data quality

Most data problems stem from faulty input (GIGO)

data quality audit

◦ Structured survey of the accuracy and level of completeness of the data in an information system

• Survey samples from data files, or

• Survey end users for perceptions of quality

data cleansing

• Software to detect and correct data that are incorrect, incomplete, improperly formatted, or redundant

• Enforces consistency among different sets of data from separate information systems

attribute

describes the entity

ex) attributes date or grade belong to entity COURSE

entity

person, place, thing on which we store data

field

group of characters as words or number

record

group of related fields

file

group of records of the same type

database

group of related files

data redundancy

presence of duplicate data in multiple files

data inconsistency

same attribute has different values

rows/tuples/records

records for different entities

fields/columns/attributes

defines data table can hold (attribute for entity)

primary key

field in table used to uniquely identify a table

foreign key

primary key used in second table as look-up field to identify records from original table

cardinality of relationships

Relation has to be BI-DIRECTIONAL to make sense (from A to B and B to A)

Before new database in place, need to

• identify and correct faulty data

• establish better routines for editing data once database in operation