Data Mining (DM)Matthew StanleyCynthia Denise WilliamsCianti Williams

Agenda

• Background information• Real World Case 4- Applebee’s

Travelocity, and Others: Data Mining for Business Decisions

• Questions• Analysis• Final Remarks• References

Background information

DM Encompasses•Statistics•Ability of systems to learn•Artificial Neural Networks Databases•Expert Systems•Data Visualization

Background information

DM Past and Present• DM can be traced back to the late

1980’s

• Early 1990’s DM recognized as a sub-application of KDD (Knowledge Discovery Database)

• Notoriety greatly increased in the 1990 ’s• Secondary to advances in technology

• DM process continue to increase

• Will expand related to desire to collect electronic data

Background information

DM Main Goals1. Analyze2. Predict future behaviors3. Gain competitive advantages4. Find patterns

a) Associationsb) Relationships

5. Summarize6. Increase revenue, cut cost

Real World Case 4• Analyzes three companies:

Applebee’s, Travelocity, and VistaPrint uses of Data Mining

• Applebee’s: restaurant• Analyzed operations at their restaurants• Used data to calculate how much time a

customer spends in the restaurant (from time of order, to food service, to payment)

• Result: Improved customer service

Real World Case 4

• Travelocity: Online travel agency• Using text analytics software (natural language

engine) from Attensity• Identifies facts, opinions, trends, etc…

• Result: effectively identifies trends which allows the company to prevent problems or anticipate customer needs more efficiently.

• VistaPrint: online graphic design services• Improved their ability to retrieve trend

information• Installed new technology->retrieved 1% of

information• Result: Able to improve customer interaction

with the website

Advantages vs. Disadvantages Creating business data warehousing

ADVANTAGES DISADVANTAGES

• Predict Future Behaviors

• Gain Competitive • Advantages• Find Patterns• Summarize• Increase revenue,

cut cost

• Requires experience instatistics, domainknowledge

• Random fluctuations can be misinterpreted

• Privacy concerns

The Bandwagon effect Why not jump on the data mining bandwagon?

• Not for every business• Must be open minded• Need access to all phases of data for

complete picture• Individual privacy• Data integrity

Applebee’sOther uses/questions while analyzing data

• Total time to prepare meals and wait times

• Compare drink choices with sport events

• Zip codes on credit cards to create new locations• Blog content mining advertise specialties in area using Smartphone technology

Applebee’sOther uses/questions while analyzing data

YES NO

Innovative Thinking Does data mining stifle creativity?

• Encourages innovation

• Support for radical ideas

• Undo bad choices FasterUtilize technology such as a Creativity Engine

• Become too heartless

• All about numbers

Creativity Machine• Brings together libraries that were never intended to work together

• Users become infinitely flexible with the ability to transform data.

Innovative Thinking Does data mining stifle creativity? (no)

Learning Points

• Data mining continuing to grow• More art than numbers

Is this still a problem?

• Becoming more standardized• Diversified not centralized

Other examples in IT used for this case study

Amazon.com: example of company using data mining well. • Offers customized experience• Remember previous interests and display

relevant items • Displays items that are popular and related• Shows items that were commonly

purchased together

Final Remarks

• DM processes increased greatly over past ten years

• DM will expand related to desire to collect electronic data

References

Coenen, F., (2011). Data mining: past, present, future. The Knowledge Engineering Review:25 th Anniversary Issue, 26(1), 25-29. doi: 2259819321.

Mining the Blogosphere to Generate Cuisine Hotspot Maps. (2010). Journal of Digital Information Management, 8(6), 396-401. Retrieved from EBSCOhost.

Shonle, M., & Yuen, T. T. (2010). Compose & Conquer: Modularity for End-Users. ICSE:

International Conference on Software Engineering, 191-194. Retrieved from EBSCOhost.

Thank you!