ASUG @ Cubs 07102015 - D+A - Social Media Sentiment
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Transcript of ASUG @ Cubs 07102015 - D+A - Social Media Sentiment
Social Media Sentiment through SAP HANA and SAP BusinessObjects Analytics
Brandon M LageDickinson + Associates
Focus: Delivery of quality SAP ERP, BI/Analytics, Mobility
consulting services to customers across North America,
Europe, and Asia.
Our People: A team of 140+ full-time SAP professionals reflects the
ideal mix of years of relevant business knowledge, very
strong SAP credentials, and solid communication skills.
Our team has an average of 16 years SAP and 19 years
business experience.
Offices: Chicago, IL (Headquarters)
Satellites: New York, NY | Scottsdale, AZ | Cincinnati,
OH
SAP Gold Channel Partner
SAP Services Partner
SAP All-in-One Certified Solutions
SAP-Qualified Partner for RDS
Business Objects
Sybase Partner
SuccessFactors Partner
S A P Q u a l i f i e d P a r t n e rR A P I D D E P L O Y M E N T S O L U T I O N S
Agenda
Data Epidemic / Structured vs. Unstructured Data
Social Listening
SAP HANA Text Analysis
Example: Sentiment Analysis – “Voice of the Customer” Apple Watch #Cubs #CrosstownClassic
Best Practices
Key Learnings
Data Epidemic
90% global data created in last 3 years 2011 - 2014
10% of all data ever created
Structured vs. Unstructured Data
Structured Data
Data that resides in a fixed
field within a record or file
Ex: data in a database table
Easy to enter, store, and
analyze
Unstructured Data
Does not reside in a traditional
database
Ex: e-mail, videos, audio files,
web pages, presentations
Difficult and costly to analyze
Structured vs. Unstructured Data
Data in Organizations
80%+ is unstructured
Data about organization is
now in the hands of the
consumer via social media
Harnessing this data is the
key to uncovering insights
about your organization
Social Listening
Process of identifying and assessing what is being said about a company,
individual, product or brand via social media
Becoming increasingly popular across organizations geared at tackling
the growing data explosion
Consumer ACME Foods Customer Service Rep
1. Offer refund2. Find out
details3. Send swag4. Do nothing
This candy tastes horrible! #ACMEFOODS
Social Media Monitoring
SAP HANA Text AnalysisU
nst
ruct
ure
d
Data
1. Extract meaning2. Transform into
structured data for analysis
Structured Data
Now able to query, analyze, visualize, report against, etc.
Process of analyzing unstructured text, extracting relevant information and then
transforming that information structured that can be leveraged in different ways.
With the help of text analysis we can model and structure the information content
for the purpose of business analysis, research and investigation.
SAP HANA Text Analysis
Example: Voice of Customer Text Analysis
ID Text Lang
1 Bob likes working at SAP EN
2 The innovation from SAP is amazing EN
3 I can’t wait to implement SAP HANA! EN
SAP HANA Linguistics Processor
Bob likes working at SAP
Weak Positive
Sentiment
Person Topic Organization / Commercial
Simple Text Analysis in SAP HANA
3. Turn On – Text Analysis
2. Turn On – Twitter Streaming API and store Tweets
1. Create HANA Table
4. Connect HANA to Lumira + Visualize
Simple Text Analysis in SAP HANA
1. Create HANA Table
Simple Text Analysis in SAP HANA
2. Turn On – Twitter Streaming API and store Tweets
Twitter API App Node.JS HANA Destination Table
Simple Text Analysis in SAP HANA
3. Turn On – Text Analysis
Simple Text Analysis in SAP HANA
4. Connect HANA to Lumira + Visualize
Simple Text Analysis in SAP HANA
#AppleWatch
Simple Text Analysis in SAP HANA
#AppleWatch
Simple Text Analysis in SAP HANA
#AppleWatch
Simple Text Analysis in SAP HANA
#AppleWatch
Simple Text Analysis in SAP HANA
#AppleWatch
Simple Text Analysis in SAP HANA
#AppleWatch
Simple Text Analysis in SAP HANA
#Cubs - TOPICS
Simple Text Analysis in SAP HANA
#Cubs - Persons
Simple Text Analysis in SAP HANA
#Cubs – Sports Organizations
Simple Text Analysis in SAP HANA
#Cubs – Major Problems
Simple Text Analysis in SAP HANA
#Cubs – Facility/Building Grounds
Simple Text Analysis in SAP HANA
#CrosstownClassic
Simple Text Analysis in SAP HANA
#CrosstownClassic
Simple Text Analysis in SAP HANA
#CrosstownClassic
Best Practices
Utilize the out-of-box system dictionaries to simplify user experience, enhance after organization understands usage of entity types.
Case-sensitivity can skew results, work towards converting strings to upper-case if necessary.
Key Learnings
Introducing SAP HANA Text Analysis into your organization requires a change in culture to realize its benefits.
The SAP HANA Text Analysis engine is continuously evolving, slang and tone should be evaluated when making decisions from the information.
SAP HANA Text Analysis is extremely simple to implement.
Social Media isn’t the only unstructured text that can be analyzed, this can extend to any type of text (email, blog, electronic documents, etc.)
THANK YOU
Let’s Go Cubs!