Cisco SocialMiner

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A new product from Cisco to mine social media for analytics on sentiment-

http://www.cisco.com/en/US/products/ps11349/index.html

Cisco SocialMiner is a social media customer care solution that can help you proactively respond to customers and prospects communicating through public social media networks like Twitter, Facebook, or other public forums or blogging sites. By providing social media monitoring, queuing, and workflow to organize customer posts on social media networks and deliver them to your social media customer care team, your company can respond to customers in real time using the same social network they are using.

Cisco SocialMiner provides:

  • The ability to configure multiple campaigns to search for customer postings on the public social web about your company’s products, services, or area of expertise
  • Filtering of social contacts based on preconfigured campaign filters to focus campaign searches
  • Routing of social contacts to skilled customer care representatives in the contact center or to experts in the enterprise–multiple people can work together to handle responses to customer postings through shared work queues
  • Detailed metrics for social media customer care activities, campaign reports, and team reports

With Cisco SocialMiner, your company can listen and respond to customer conversations originating in the social web. Being proactive can help your company enhance its service, improve customer loyalty, garner new customers, and protect your brand.

Table 1. Features and Benefits of Cisco SocialMiner 8.5

Feature Benefits
Product Baseline Features
Social media feeds

• Feeds are configurable sources to capture public social contacts that contain specific words, terms, or phrases.

• Feeds enable you to search for information on the public social web about your company’s products, services, or area of expertise.

• Cisco SocialMiner supports the following types of feeds:

• Facebook

• Twitter
Campaign management

• Groups feeds into campaigns to organize all posting activity related to a product category or business objective

• Produces metrics on campaign activity

• Provides the ability to configure multiple campaigns to search for customer postings on specific products or services

• Groups social contacts for handling by the social media customer care team

• Enables filtering of social contacts based on preconfigured campaign filters to focus campaign searches
Route and queue social contacts

• Enables routing of social contacts to skilled customer care representatives in the contact center

• Draws on expertise in the enterprise by allowing multiple people in the enterprise to work together to handle responses to customer postings through shared work queues

• Enables automated distribution of work to improve efficiency and effectiveness of social media engagement
Tagging

• Allows work to be routed to the appropriate team by grouping each post or social contact into different categories; for example, a post can be marked with the “customer_support” tag; this post will then appear on a customer support agent’s queue for processing
Social media customer care metrics

• Provides detailed metrics on social media customer care activities, campaign reports, and team reports

• Measures work and results

• Manages to service-level goals

• Supports brand management

• Optimizes staffing

• Includes dashboarding of social media posting activity when Cisco Unified Intelligence Center is used
Reporting for social contacts

• Provides a reporting database that can be accessed using any reporting tool, including Cisco Unified Intelligence Center

• Enables customer care management to accurately report on and track social media interactions by the contact center
OpenSocial-compliant gadgets

Representational State Transfer (REST) application programming interfaces (APIs)

• Provides flexible user interface options

• Enables extensive opportunities for customization
Optional integration with full suite of Cisco Collaboration tools

• Allows you to take advantage of the full suite of Cisco Collaboration tools, including Cisco Quad, Cisco Show and Share, and Cisco Pulse technology, to help your social media customer care team quickly find answers to help customers efficiently and effectively

• Easy to maintain with existing IT personnel
Operating Environment
Cisco Unified Computing System(UCS) C-Series or B-Series Servers

• Requires a Cisco UCS C-Series or B-Series Server.

• Server consolidation means lower cost per server with Cisco UCS Servers.
Architecture
Scalability

• One server supports up to 30 simultaneous social media customer care users and 10,000 social contacts per hour.
Management
Cisco Unified Real-Time Monitoring Tool (RTMT)

• Operational management is enhanced through integration with the Cisco Unified RTMT, providing consistent application monitoring across Cisco Unified Communications Solutions.
Simple Network Management Protocol (SNMP)

• SNMP with an associated MIB is supported through the Cisco Voice Operating System (VOS).
Reporting
Cisco Unified Intelligence Center

• Create customizable reports of social media customer care events using Cisco Unified Intelligence Center (purchased separately).

 

 

Is 21 st century cloud computing same as 1960's time sharing

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and yes Prof Goodnight, cloud computing is not time sharing. (Dr J was on a roll there- bashing open source AND cloud computing in the SAME interview at http://www.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal)

What was time sharing? In the 1960’s when people had longer hair, listened to the Beatles and IBM actually owned ALL computers-

http://en.wikipedia.org/wiki/Time-sharing

or is it?

The Internet has brought the general concept of time-sharing back into popularity. Expensive corporate server farms costing millions can host thousands of customers all sharing the same common resources. As with the early serial terminals, websites operate primarily in bursts of activity followed by periods of idle time. This bursting nature permits the service to be used by many website customers at once, and none of them notice any delays in communications until the servers start to get very busy.

What is 21 st century cloud computing? Well… they are still writing papers to define it BUT http://en.wikipedia.org/wiki/Cloud_computing

Cloud computing is Web-based processing, whereby shared resources, software, and information are provided to computers and other devices (such as smartphones) on demand over the Internet.

 

 

Is 21 st century cloud computing same as 1960’s time sharing

Diagram showing three main types of cloud comp...
Image via Wikipedia

and yes Prof Goodnight, cloud computing is not time sharing. (Dr J was on a roll there- bashing open source AND cloud computing in the SAME interview at http://www.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal)

What was time sharing? In the 1960’s when people had longer hair, listened to the Beatles and IBM actually owned ALL computers-

http://en.wikipedia.org/wiki/Time-sharing

or is it?

The Internet has brought the general concept of time-sharing back into popularity. Expensive corporate server farms costing millions can host thousands of customers all sharing the same common resources. As with the early serial terminals, websites operate primarily in bursts of activity followed by periods of idle time. This bursting nature permits the service to be used by many website customers at once, and none of them notice any delays in communications until the servers start to get very busy.

What is 21 st century cloud computing? Well… they are still writing papers to define it BUT http://en.wikipedia.org/wiki/Cloud_computing

Cloud computing is Web-based processing, whereby shared resources, software, and information are provided to computers and other devices (such as smartphones) on demand over the Internet.

 

 

Open Source's worst enemy is itself not Microsoft/SAS/SAP/Oracle

The decision of quality open source makers to offer their software at bargain basement prices even to enterprise customers who are used to pay prices many times more-pricing is the reason open source software is taking a long time to command respect in enterprise software.

I hate to be the messenger who brings the bad news to my open source brethren-

but their worst nightmare is not the actions of their proprietary competitors like Oracle, SAP, SAS, Microsoft ( they hate each other even more than open source )

nor the collective marketing tactics which are textbook like (but referred as Fear Uncertainty Doubt by those outside that golden quartet)- it is their own communities and their own cheap pricing.

It is community action which prevents them from offering their software by ridiculously low bargain basement prices. James Dixon, head geek and founder at Pentaho has a point when he says traditional metrics like revenue need o be adjusted for this impact in his article at http://jamesdixon.wordpress.com/2010/11/02/comparing-open-source-and-proprietary-software-markets/

But James, why offer software to enterprise customers at one tenth the next competitor- one reason is open source companies more often than not compete more with their free community version software than with big proprietary packages.

Communities including academics are used to free- hey how about paying say 1$ for each download.

There are two million R users- if say even 50 % of them  paid 1 $ as a lifetime license fee- you could sponsor enough new packages than twenty years of Google Summer of Code does right now.

Secondly, this pricing can easily be adjusted by shifting the licensing to say free for businesses less than 2 people (even for the enhanced corporate software version not just the plain vanilla community software thus further increasing the spread of the plain vanilla versions)- for businesses from 10 to 20 people offer a six month trial rather than one month trial.

– but adjust the pricing to much more realistic levels compared to competing software. Make enterprise software pay a real value.

That’s the only way to earn respect. as well as a few dollars more.

As for SAS, it is time it started ridiculing Python now that it has accepted R.

Python is even MORE powerful than R in some use cases for stat computing

Dixon’s Pentaho and the Jaspersoft/ Revolution combo are nice _ I tested both Jasper and Pentaho thanks to these remarks this week 🙂  (see slides at http://www.jaspersoft.com/sites/default/files/downloads/events/Analytics%20-Jaspersoft-SEP2010.pdf or http://www.revolutionanalytics.com/news-events/free-webinars/2010/deploying-r/index.php )

Pentaho and Jasper do give good great graphics in BI (Graphical display in BI is not a SAS forte though probably I dont know how much they cross sell JMP to BI customers- probably too much JMP is another division syndrome there)

Jim Goodnight on Open Source- and why he is right -sigh

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Jim Goodnight – grand old man and Godfather of the Cosa Nostra of the BI/Database Analytics software industry said recently on open source in BI (btw R is generally termed in business analytics and NOT business intelligence software so these remarks were more apt to Pentaho and Jaspersoft )

Asked whether open source BI and data integration software from the likes of Jaspersoft, Pentaho and Talend is a growing threat, [Goodnight] said: “We haven’t noticed that a lot. Most of our companies need industrial strength software that has been tested, put through every possible scenario or failure to make sure everything works correctly.”

quotes from Jim Goodnight are courtesy Jason’s  story here:
http://www.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal

and the Pentaho follow-up reaction is here

http://bi.cbronline.com/news/pentaho-fires-back-across-sas-bows-over-limited-open-source-appeal

 

 

While you can rage and screech- here is the reality in terms of market share-

From Merv Adrian-‘s excellent article on market shares in BI

http://www.enterpriseirregulars.com/22444/decoding-bi-market-share-numbers-%E2%80%93-play-sudoku-with-analysts/

The first, labeled BI Platforms, is drawn fromGartner Market Share Analysis: Business Intelligence, Analytics and Performance Management Software, Worldwide, 2009, published May 2010 , and Gartner Dataquest Market Share: Business Intelligence, Analytics and Performance Management Software, Worldwide, 2009.

and

Advanced Analytics category.

and 

so whats the performance of Talend, Pentaho and Jaspersoft

From http://www.dbms2.com/category/products-and-vendors/talend/

It seems that Talend’s revenue was somewhat shy of $10 million in 2008.

and Talend itself says

http://www.talend.com/press/Talend-Announces-Record-2009-and-Continues-Growth-in-the-New-Year.php

Additional 2009 highlights include:

  • Achieved record revenue, more then doubling from 2008. The fourth quarter of 2009 was Talend’s tenth consecutive quarter of growth.
  • Grew customer base by 140% to over 1,000 customers, up from 420 at the end of 2008. Of these new customers, over 50% are Fortune 1000 companies.
  • Total downloads reached seven million, with over 300,000 users of the open source products.
  • Talend doubled its staff, increasing to 200 global employees. Continuing this trend, Talend has already hired 15 people in 2010 to support its rapid growth.

now for Jaspersoft numbers

http://www.dbms2.com/2008/09/14/jaspersoft-numbers/

Highlights include:

  • Revenue run rate in the double-digit millions.
  • 40% sequential growth most recent quarter. (I didn’t ask whether there was any reason to suspect seasonality.)
  • 130% annual revenue growth run rate.
  • “Not quite” profitable.
  • Several hundred commercial subscribers, at an average of $25K annually per, including >100 in Europe.
  • 9,000 paying customers of some kind.
  • 100,000+ total deployments, “very conservatively,” counting OEMs as one deployment each and not double-counting for OEMs’ customers. (Nick said Business Objects quotes 45,000 deployments by the same standards.)
  • 70% of revenue from the mid-market, defined as $100 million – $1 billion revenue. 30% from bigger enterprises. (Hmm. That begs a couple of questions, such as where OEM revenue comes in, and whether <$100 million enterprises were truly a negligible part of revenue.)

and for Pentaho numbers-

http://www.dbms2.com/2009/01/27/introduction-to-pentaho/

and http://www.monash.com/uploads/Pentaho-January-2009.pdf

suggests there are far far away from the top 5-6 vendors in BI

and a special mention  for postgreSQL– which is a non Profit but is seriously denting Oracle/MySQL

http://www.postgresql.org/about/

Limit Value
Maximum Database Size Unlimited
Maximum Table Size 32 TB
Maximum Row Size 1.6 TB
Maximum Field Size 1 GB
Maximum Rows per Table Unlimited
Maximum Columns per Table 250 – 1600 depending on column types
Maximum Indexes per Table Unlimited

and leading vendor is EnterpriseDB which is again IBM-partnering as well as IBM funded

http://www.sramanamitra.com/2009/05/18/enterprise-db/

and

http://www.enterprisedb.com/company/news_events/press_releases/2010_21.do

suggest it is still in early stages.

————————————————————–

So what do we conclude-

1) There is a complete lack of transparency in open source BI market shares as almost all these companies are privately held and do not disclose revenues.

2) What may be a pure play open source company may actually be a company funded by a big BI vendor (like Revolution Analytics is funded among others by Intel-Microsoft) and EnterpriseDB has IBM as an investor.MySQL and Sun of course are bought by Oracle

The degree of control by proprietary vendors on open source vendors is still not disclosed- whether they are holding a stake for strategic reasons or otherwise.

3) None of the Open Source Vendors are even close to a 1 Billion dollar revenue number.

Jim Goodnight is pointing out market reality when he says he has not seen much impact (in terms of market share). As for the rest of his remarks, well he’s got a job to do as CEO and thats talk up his company and trash the competition- which he as been doing for 3 decades and unlikely to change now unless there is severe market share impact. Unless you expect him to notice companies less than 5% of his size in revenue.

http://www.cbronline.com/news/sas-ceo-says-cep-open-source-and-cloud-bi-have-limited-appeal

http://bi.cbronline.com/news/pentaho-fires-back-across-sas-bows-over-limited-open-source-appeal

 

Using PostgreSQL and MySQL databases in R 2.12 for Windows

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If you use Windows for your stats computing and your data is in a database (probably true for almost all corporate business analysts) R 2.12 has provided a unique procedural hitch for you NO BINARIES for packages used till now to read from these databases.

The Readme notes of the release say-

Packages related to many database system must be linked to the exact
version of the database system the user has installed, hence it does
not make sense to provide binaries for packages
	RMySQL, ROracle, ROracleUI, RPostgreSQL
although it is possible to install such packages from sources by
	install.packages('packagename', type='source')
after reading the manual 'R Installation and Administration'.

So how to connect to Databases if the Windows Binary is not available-

So how to connect to PostgreSQL and MySQL databases.

For Postgres databases-

You can update your PostgreSQL databases here-

http://www.postgresql.org/download/windows

Fortunately the RpgSQL package is still available for PostgreSQL

  • Using the RpgSQL package

library(RpgSQL)

#creating a connection
con <- dbConnect(pgSQL(), user = "postgres", password = "XXXX",dbname="postgres")

#writing a table from a R Dataset
dbWriteTable(con, "BOD", BOD)

# table names are lower cased unless double quoted. Here we write a Select SQL query
dbGetQuery(con, 'select * from "BOD"')

#disconnecting the connection
dbDisconnect(con)

You can also use RODBC package for connecting to your PostgreSQL database but you need to configure your ODBC connections in

Windows Start Panel-

Settings-Control Panel-

Administrative Tools-Data Sources (ODBC)

You should probably see something like this screenshot.

Coming back to R and noting the name of my PostgreSQL DSN from above screenshot-( If not there just click on add-scroll to appropriate database -here PostgreSQL and click on Finish- add in the default values for your database or your own created database values-see screenshot for help with other configuring- and remember to click Test below to check if username and password are working, port is correct etc.

so once the DSN is probably setup in the ODBC (frightening terminology is part of databases)- you can go to R to connect using RODBC package


#loading RODBC

library(RODBC)

#creating a Database connection
# for username,password,database name and DSN name

chan=odbcConnect("PostgreSQL35W","postgres;Password=X;Database=postgres")

#to list all table names

sqlTables(chan)

TABLE_QUALIFIER TABLE_OWNER TABLE_NAME TABLE_TYPE REMARKS
1       postgres      public        bod      TABLE      
 2        postgres      public  database1      TABLE      
 3        postgres      public         tt      TABLE

Now for MySQL databases it is exactly the same code except we download and install the ODBC driver from http://www.mysql.com/downloads/connector/odbc/

and then we run the same configuring DSN as we did for postgreSQL.

After that we use RODBC in pretty much the same way except changing for the default username and password for MySQL and changing the DSN name for the previous step.

channel <- odbcConnect("mysql","jasperdb;Password=XXX;Database=Test")
test2=sqlQuery(channel,"select * from jiuser")
test2
 id  username tenantId   fullname emailAddress  password externallyDefined enabled previousPasswordChangeTime1  1   jasperadmin        1 Jasper Administrator           NA 349AFAADD5C5A2BD477309618DC              NA    01                       
2  2       joe1ser        1             Joe User           NA                 4DD8128D07A               NA    01
odbcClose(channel)
While using RODBC for all databases is a welcome step, perhaps the change release notes for Window Users of R may need to be more substantiative than one given for R 2.12.2

Scoring SAS and SPSS Models in the cloud

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An announcement from Zementis and Predixion Software– about using cloud computing for scoring models using PMML. Note R has a PMML package as well which is used by Rattle, data mining GUI for exporting models.

Source- http://www.marketwatch.com/story/predixion-software-introduces-new-product-to-run-sas-and-spss-predictive-models-in-the-cloud-2010-10-19?reflink=MW_news_stmp

——————————————————————————————————–

ALISO VIEJO, Calif., Oct 19, 2010 (BUSINESS WIRE) — Predixion Software today introduced Predixion PMML Connexion(TM), an interface that provides Predixion Insight(TM), the company’s low-cost, self-service in the cloud predictive analytics solution, direct and seamless access to SAS, SPSS (IBM) and other predictive models for use by Predixion Insight customers. Predixion PMML Connexion enables companies to leverage their significant investments in legacy predictive analytics solutions at a fraction of the cost of conventional licensing and maintenance fees.

The announcement was made at the Predictive Analytics World conference in Washington, D.C. where Predixion also announced a strategic partnership with Zementis, Inc., a market leader in PMML-based solutions. Zementis is exhibiting in Booth #P2.

The Predictive Model Markup Language (PMML) standard allows for true interoperability, offering a mature standard for moving predictive models seamlessly between platforms. Predixion has fully integrated this PMML functionality into Predixion Insight, meaning Predixion Insight users can now effortlessly import PMML-based predictive models, enabling information workers to score the models in the cloud from anywhere and publish reports using Microsoft Excel(R) and SharePoint(R). In addition, models can also be written back into SAS, SPSS and other platforms for a truly collaborative, interoperable solution.

“Predixion’s investment in this PMML interface makes perfect business sense as the lion’s share of the models in existence today are created by the SAS and SPSS platforms, creating compelling opportunity to leverage existing investments in predictive and statistical models on a low-cost cloud predictive analytics platform that can be fed with enterprise, line of business and cloud-based data,” said Mike Ferguson, CEO of Intelligent Business Strategies, a leading analyst and consulting firm specializing in the areas of business intelligence and enterprise business integration. “In this economy, Predixion’s low-cost, self-service predictive analytics solutions might be welcome relief to IT organizations chartered with quickly adding additional applications while at the same time cutting costs and staffing.”

“We are pleased to be partnering with Zementis, truly a PMML market leader and innovator,” said Predixion CEO Simon Arkell. “To allow any SAS or SPSS customer to immediately score any of their predictive models in the cloud from within Predixion Insight, compare those models to those created by Predixion Insight, and share the results within Excel and Sharepoint is an exciting step forward for the industry. SAS and SPSS customers are fed up with the high prices they must pay for their business users just to access reports generated by highly skilled PhDs who are burdened by performing routine tasks and thus have become a massive bottleneck. That frustration is now a thing of the past because any information worker can now unlock the power of predictive analytics without relying on experts — for a fraction of the cost and from anywhere they can connect to the cloud,” Arkell said.

Dr. Michael Zeller, Zementis CEO, added, “Our mission is to significantly shorten the time-to-market for predictive models in any industry. We are excited to be contributing to Predixion’s self-service, cloud-based predictive analytics solution set.”

About Predixion Software

Predixion Software develops and markets collaborative predictive analytics solutions in the public and private cloud. Predixion enables self-service predictive analytics, allowing customers to use and analyze large amounts of data to make actionable decisions, all within the familiar environment of Excel and PowerPivot. Predixion customers are achieving immediate results across a multitude of industries including: retail, finance, healthcare, marketing, telecommunications and insurance/risk management.

Predixion Software is headquartered in Aliso Viejo, California with development offices in Redmond, Washington. The company has venture capital backing from established investors including DFJ Frontier, Miramar Venture Partners and Palomar Ventures. For more information please contact us at 949-330-6540, or visit us atwww.predixionsoftware.com.

About Zementis

Zementis, Inc. is a leading software company focused on the operational deployment and integration of predictive analytics and data mining solutions. Its ADAPA(R) decision engine successfully bridges the gap between science and engineering. ADAPA(R) was designed from the ground up to benefit from open standards and to significantly shorten the time-to-market for predictive models in any industry. For more information, please visit www.zementis.com.