I love this website from Stitchfix.com, it goes to show how much innovation is behind something as simple as a shipping department to the complexities of a recommendation engine in todays technology driven world.
Category: Research
Hacking SAP HANA Websockets
Disclaimer: This is not a production or documented feature – its also more of a hijack than a hack 🙂
I have been hoping for the inclusion of Websocket support on the HANA DB platform for a while now, and I was a little disappointed it was not packaged in the SPS08 release. My goal when building apps (or products) is to make use of the core platform its running on as much as possible, I firmly believe that when convincing an IT department, or company, to implement a product or app, the first question is: “How much infrastructure does this need?”. This can often be a deal breaker and why I am such a big proponent of the HANA’s DB + XS App Server integration – it consolidates the requirements into a single investment. Having a Websocket technology built directly in XS can be an additional selling point which developers are starting to expect these days.
SAP Netweaver Gateway – A product powering innovation at SAP
While SAP Netweaver Gateway is a product not often discussed at keynotes, events and in the media, it is a integral part of the innovative products being launched at SAP and is core component of SAP Fiori. If you are interested in taking advantage of some of the new free Fiori applications to drive value with your ERP investment, understanding SAP Netweaver Gateway is not optional, but rather a requirement.
In a summary, Netweaver Gateway is a ABAP developed add-on powering applications like SAP Fiori, SAP Mobility Platform (SMP), and even Duet Enterprise. This small, but very important component gives your company the ability to turn your monolithic, big and heavy backend systems into lightweight, simple, consumable web services.
Practical Big Data Use Cases
Background
Source:
https://www.kaggle.com/wiki/DataScienceUseCases
For each type of analysis think about:
- What problem does it solve and for who?
- How is it being solved today?
- What are the data inputs and where do they come from?
- What are the outputs and how are they consumed- (online algo, static report, etc)
- Is this a revenue leakage (“saves us money”) or a revenue growth (“makes us money”) problem?
Use Cases By Function
Marketing
- Predicting Lifetime Value (LTV)
- what for: if you can predict the characteristics of high LTV customers, this supports customer segmentation, identifies upsell opportunties and supports other marketing initiatives
- usage: can be both an online algorithm and a static report showing the characteristics of high LTV customers
- working out the proportion of a customer’s spend in a category accrues to a company allows that company to identify upsell and cross-sell opportunities
- usage: can be both an online algorithm and a static report showing the characteristics of low wallet share customers
- Churn
- working out the characteristics of churners allows a company to product adjustments and an online algorithm allows them to reach out to churners
- usage: can be both an online algorithm and a statistic report showing the characteristics of likely churners
- Customer segmentation
- If you can understand qualitatively different customer groups, then we can give them different treatments (perhaps even by different groups in the company). Answers questions like: what makes people buy, stop buying etc
- usage: static report
- Product mix
- What mix of products offers the lowest churn? eg. Giving a combined policy discount for home + auto = low churn
- usage: online algorithm and static report
- Cross selling/Recommendation algorithms/
- Given a customer’s past browsing history, purchase history and other characteristics, what are they likely to want to purchase in the future?
- usage: online algorithm
- Up selling
- Given a customer’s characteristics, what is the likelihood that they’ll upgrade in the future?
- usage: online algorithm and static report
- Channel optimization
- what is the optimal way to reach a customer with cetain characteristics?
- usage: online algorithm and static report
Discount targeting – What is the probability of inducing the desired behavior with a discount – usage: online algorithm and static report
- Reactivation likelihood
- What is the reactivation likelihood for a given customer
- usage: online algorithm and static report
- calculating the right price for different keywords/ad slots
Sales
- Lead prioritization
- What is a given lead’s likelihood of closing
- revenue impact: supports growth
- usage: online algorithm and static report
Logistics
- Demand forecasting
- How many of what thing do you need and where will we need them? (Enables lean inventory and prevents out of stock situations.)
- revenue impact: supports growth and militates against revenue leakage
- usage: online algorithm and static report
Risk
- Credit risk
- Treasury or currency risk
- How much capital do we need on hand to meet these requirements?
- predicting whether or not a transaction should be blocked because it involves some kind of fraud (eg credit card fraud)
- Predicting the probably a liability can be recovered given the characteristics of the borrower and the loan
- Using machine learning and fuzzy matching to detect transactions that contradict AML legislation (such as the OFAC list)
Customer support
- Call centers
- Call routing (ie determining wait times) based on caller id history, time of day, call volumes, products owned, churn risk, LTV, etc.
- Putting the right data on the operator’s screen
- predicting call volume for the purposes of staff rostering
Human Resources
- Resume screening
- scores resumes based on the outcomes of past job interviews and hires
- predicts which employees are most likely to leave
- recommends specific training based of performance review data
- looking at objective measures of employee success
Use Cases By Vertical
Healthcare
- Claims review prioritization
- payers picking which claims should be reviewed by manual auditors
- Tackled at the claims processors, EDS is the biggest & uses proprietary tech
- Hospital operations management
- Optimize/predict operating theatre & bed occupancy based on initial patient visits
- Embedded devices (productized algos)
- Exogenous data from devices to create diagnostic reports for doctors
- Predicting who won’t comply with their prescriptions
- Hospitals want to retain Drs who have admitting privileges in multiple hospitals
- Analyse survival statistics for different patient attributes (age, blood type, gender, etc) and treatments
- Analyse effects of admitting different types and dosage of medication for a disease
- Predict risk of re-admittance based on patient attributes, medical history, diagnose & treatment
Consumer Financial
- Credit card fraud
- Banks need to prevent, and vendors need to prevent
Retail (FMCG – Fast-moving consumer goods)
- Pricing
- Optimize per time period, per item, per store
- Was dominated by Retek, but got purchased by Oracle in 2005. Now Oracle Retail.
- JDA is also a player (supply chain software)
- Pioneerd by Tesco
- Dominated by Buxton
- This is called “plan-o-gramming”
- when to start stocking & discontinuing product lines
- In particular, perishable goods
- Theft analytics/prevention (http://www.internetretailer.com/2004/12/17/retailers-cutting-inventory-shrink-with-spss-predictive-analytic)
- Rates of failure for different components And what are the drivers or parts?
- What types of customers buying what types of products are likely to actually redeem a warranty?
Insurance
- Claims prediction
- Might have telemetry data
Construction
- Contractor performance
- Identifying contractors who are regularly involved in poor performing products
- Predicting that a construction project is likely to have issues as early as possible
Life Sciences
- Identifying biomarkers for boxed warnings on marketed products
- Drug/chemical discovery & analysis
- Crunching study results
- Identifying negative responses (monitor social networks for early problems with drugs)
- Diagnostic test development
- Hardware devices
- Software
Hospitality/Service
- Inventory management/dynamic pricing
- Promos/upgrades/offers
- Table management & reservations
- Workforce management (also applies to lots of verticals)
Electrical grid distribution
- Keep AC frequency as constant as possible
- Seems like a very “online” algorithm
Manufacturing
- Sensor data to look at failures
- Quality management
- Identifying out-of-bounds manufacturing Visual inspection/computer vision
- Optimal run speeds
Travel
- Aircraft scheduling
- Seat mgmt, gate mgmt
- Air crew scheduling
- Dynamic pricing
- Customer complain resolution (give points in exchange)
- Call center stuff
- Maintenance optimization
- Tourism forecasting
Agriculture