Big Data, Business users and opportunities
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© 2014 IBM Corporation Craig Statchuk Architecture and Strategy, IBM Business Analytics Office of the CTO November 2014 GeoSpatial Analytics for Business Rev B
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Transcript of Big Data, Business users and opportunities
© 2014 IBM Corporation
Craig StatchukArchitecture and Strategy, IBM Business Analytics Office of the CTO
November 2014
GeoSpatial Analytics for Business
Rev B
2About Me
Cognos / IBM technical strategy
Geospatial business evangelist
Big data, cloud, search, modeling
Craig [email protected]@statchuk
3Agenda
Enterprise Analytics
The Data Driven Business
Top 5 Business Priorities for GIS
4Quality, Relevance and Flexibility
Data Analytics
Results
5Quality, Relevance and Flexibility
Data Analytics
Results
Relevance
Quality Flexibility
6Mobile Imperatives
Business Analytics Content
UserRole &
Context
Irresistible Mobile Value
7Mobile Imperatives
Business Analytics Content
UserRole &
Context
Irresistible Mobile Value
3 Clicks
10 Seconds
PredictiveWorkflow
8
80% Enterprise Data is Unstructured
Finding Greater Value
9Finding Greater Value
99%95% Across Business Silos
From Government
Structured Data
10First Normal Form (1NF)
1NF Data in columns
Unique keys
Customer Store Product Amount
Beth NYC Sunglasses $89
Ginny Atlanta Tent $323
Beth Toronto Shoes $123
11Third Normal Form (3NF)
Customer Store Product Amount
456 S434 10023 $89
123 S331 40032 $323
456 S416 30014 $123
1NF Data in columns
Unique keys
3NF Dependent keys
No extra data
Cust# Name Phone …
123 Ginny 516-443-5645
456 Beth 816-433-2232
Store# Location Phone …
S331 Atlanta 516-432-3231
S416 Toronto 888-416-2535
S434 NYC 888-231-2222
Prod# Name Cost …
10023 Sunglasses $65
30014 Shoes $55
40032 Tent $223
12New Normal Form (NNF)
Name Phone Customer Location Store Name Product Amount
Ginny 516-443-5645 456 Atlanta S434 Sunglasses 10023 $89
Beth 816-433-2232 123 Toronto S331 Shoes 40032 $323
Ginny 516-443-5645 456 NYC S416 Tent 30014 $123
NNF Lots of rows, columns values and extra data
Lots of duplication (x & y)
13Why NNF matters
• Second guess past assumptions
• More self-serve data preparation
• Data quality is built-in
14Leverage Better Data
Latitude: 45.467836 Longitude: -75.708618
Geospatial attributes expensive to leverage
Small changes = big variations
almost impossible
15Leverage Better Data
Latitude: 45.467836 Longitude: -75.708618
Geospatial attributes expensive to leverage
Small changes = big variations
almost impossible
Context: home, work, commuting
Clients: Hilton, Walmart, Boeing
Time periods: fiscal year, next release
16
Improving
Hospitals
17Not as Smart as we Thought
Ability to process
AvailableData
The gap is what we don’t know
Time
Volu
me
18
Enterprise Quality Data
Uncertain Data
Not as much Quality as we Need
Time
Volu
me
19Get it Right Early
Correct Assertion
Incorrect Assertion
Time
Pro
cess
ing
Watson Plays Jeopardy
Watson: “What is Toronto?”
Category: US CitiesAnswer “Its largest airport was named for a World War II hero; its second largest, for a World War II battle.”
NLP/POS: City where largest airport was named for a World War II hero; City where second largest airport is named for a World War II battle
Strategy: Low Weight on Category since it could be play on words or pun.
Ontology: University of Toronto is member of American Association of Universities; Toronto Blue Jays in the American Baseball League
22
Context: Sales rep driving from SeaTac airport
Metadata Drivers
Launched by Calendar, Email, SMS or Geo-fence Event
Ends in analytics (Customers, History, Issues)or related app (Contacts, maps, email)
23Context driven entry points (Customers)
ContactsMaps, Driving Directions…
Boeing
Sales RepsChat, Connections…
ProductsHistory, licenses…
CompetitiveProducts, Web…
Prospectsdemos, issues…
In the NewsStories, blogs…
Customer
24Metadata Drivers Select Data and Application
CategoriesRevenue, Plans, ChannelsProducts
SupportComments, APARS…
CompetitiveFeatures, Field feedback
Field Resourcesdemos, guides
In the NewsCustomers, Reviews
Boeing
25
Days to close
FY 2014
Num
ber o
f C
alls
Q1 Q2
22 days
Severity
L H
100
200
Q3 Forecast
6 days
20 days
8 days
App, data and formatare different for every customer
Mobile context requires higher flexibility and precision
Support Calls
28 days
26Business Top 55 More CONNECTIONS (existing data)
4 Exploration and DISCOVERY (new data)
3 High value GEOSPATIAL data (leverage)
2 Getting it right EARLY (close the gap)
1 KNOW what I want BEFORE I ask (everywhere)
27
Thank You!
