Tag: enterprise

Interview James Dixon Pentaho

Here is an interview with James Dixon the founder of Pentaho, self confessed Chief Geek and CTO. Pentaho has been growing very rapidly and it makes open source Business Intelligence solutions- basically the biggest chunk of enterprise software market currently.

Ajay-  How would you describe Pentaho as a BI product for someone who is completely used to traditional BI vendors (read non open source). Do the Oracle lawsuits over Java bother you from a business perspective?

James-

Pentaho has a full suite of BI software:

* ETL: Pentaho Data Integration

* Reporting: Pentaho Reporting for desktop and web-based reporting

* OLAP: Mondrian ROLAP engine, and Analyzer or Jpivot for web-based OLAP client

* Dashboards: CDF and Dashboard Designer

* Predictive Analytics: Weka

* Server: Pentaho BI Server, handles web-access, security, scheduling, sharing, report bursting etc

We have all of the standard BI functionality.

The Oracle/Java issue does not bother me much. There are a lot of software companies dependent on Java. If Oracle abandons Java a lot resources will suddenly focus on OpenJDK. It would be good for OpenJDK and might be the best thing for Java in the long term.

Ajay-  What parts of Pentaho’s technology do you personally like the best as having an advantage over other similar proprietary packages.

Describe the latest Pentaho for Hadoop offering and Hadoop/HIVE ‘s advantage over say Map Reduce and SQL.

James- The coolest thing is that everything is pluggable:

* ETL: New data transformation steps can be added. New orchestration controls (job entries) can be added. New perspectives can be added to the design UI. New data sources and destinations can be added.

* Reporting: New content types and report objects can be added. New data sources can be added.

* BI Server: Every factory, engine, and layer can be extended or swapped out via configuration. BI components can be added. New visualizations can be added.

This means it is very easy for Pentaho, partners, customers, and community member to extend our software to do new things.

In addition every engine and component can be fully embedded into a desktop or web-based application. I made a youtube video about our philosophy: http://www.youtube.com/watch?v=uMyR-In5nKE

Our Hadoop offerings allow ETL developers to work in a familiar graphical design environment, instead of having to code MapReduce jobs in Java or Python.

90% of the Hadoop use cases we hear about are transformation/reporting/analysis of structured/semi-structured data, so an ETL tool is perfect for these situations.

Using Pentaho Data Integration reduces implementation and maintenance costs significantly. The fact that our ETL engine is Java and is embeddable means that we can deploy the engine to the Hadoop data nodes and transform the data within the nodes.

Ajay-  Do you think the combination of recession, outsourcing,cost cutting, and unemployment are a suitable environment for companies to cut technology costs by going out of their usual vendor lists and try open source for a change /test projects.

Jamie- Absolutely. Pentaho grew (downloads, installations, revenue) throughout the recession. We are on target to do 250% of what we did last year, while the established vendors are flat in terms of new license revenue.

Ajay-  How would you compare the user interface of reports using Pentaho versus other reporting software. Please feel free to be as specific.

James- We have all of the everyday, standard reporting features covered.

Over the years the old tools, like Crystal Reports, have become bloated and complicated.

We don’t aim to have 100% of their features, because we’d end us just as complicated.

The 80:20 rule applies here. 80% of the time people only use 20% of their features.

We aim for 80% feature parity, which should cover 95-99% of typical use cases.

Ajay-  Could you describe the Pentaho integration with R as well as your relationship with Weka. Jaspersoft already has a partnership with Revolution Analytics for RevoDeployR (R on a web server)-

Any  R plans for Pentaho as well?

James- The feature set of R and Weka overlap to a small extent – both of them include basic statistical functions. Weka is focused on predictive models and machine learning, whereas R is focused on a full suite of statistical models. The creator and main Weka developer is a Pentaho employee. We have integrated R into our ETL tool. (makes me happy 🙂 )

(probably not a good time to ask if SAS integration is done as well for a big chunk of legacy base SAS/ WPS users)

About-

As “Chief Geek” (CTO) at Pentaho, James Dixon is responsible for Pentaho’s architecture and technology roadmap. James has over 15 years of professional experience in software architecture, development and systems consulting. Prior to Pentaho, James held key technical roles at AppSource Corporation (acquired by Arbor Software which later merged into Hyperion Solutions) and Keyola (acquired by Lawson Software). Earlier in his career, James was a technology consultant working with large and small firms to deliver the benefits of innovative technology in real-world environments.

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Data Visualization using Tableau

Image representing Tableau Software as depicte...
Image via CrunchBase

Here is a great piece of software for data visualization– the public version is free.

And you can use it for Desktop Analytics as well as BI /server versions at very low cost.

About Tableau Software–

http://www.tableausoftware.com/press_release/tableau-massive-growth-hiring-q3-2010

Tableau was named by Software Magazine as the fastest growing software company in the $10 million to $30 million range in the world, and the second fastest growing software company worldwide overall. The ranking stems from the publication’s 28th annual Software 500 ranking of the world’s largest software service providers.

“We’re growing fast because the market is starving for easy-to-use products that deliver rapid-fire business intelligence to everyone. Our customers want ways to unlock their databases and produce engaging reports and dashboards,” said Christian Chabot CEO and co-founder of Tableau.

http://www.tableausoftware.com/about/who-we-are

History in the Making

Put together an Academy-Award winning professor from the nation’s most prestigious university, a savvy business leader with a passion for data, and a brilliant computer scientist. Add in one of the most challenging problems in software – making databases and spreadsheets understandable to ordinary people. You have just recreated the fundamental ingredients for Tableau.

The catalyst? A Department of Defense (DOD) project aimed at increasing people’s ability to analyze information and brought to famed Stanford professor, Pat Hanrahan. A founding member of Pixar and later its chief architect for RenderMan, Pat invented the technology that changed the world of animated film. If you know Buzz and Woody of “Toy Story”, you have Pat to thank.

Under Pat’s leadership, a team of Stanford Ph.D.s got together just down the hall from the Google folks. Pat and Chris Stolte, the brilliant computer scientist, realized that data visualization could produce large gains in people’s ability to understand information. Rather than analyzing data in text form and then creating visualizations of those findings, Pat and Chris invented a technology called VizQL™ by which visualization is part of the journey and not just the destination. Fast analytics and visualization for everyone was born.

While satisfying the DOD project, Pat and Chris met Christian Chabot, a former data analyst who turned into Jello when he saw what had been invented. The three formed a company and spun out of Stanford like so many before them (Yahoo, Google, VMWare, SUN). With Christian on board as CEO, Tableau rapidly hit one success after another: its first customer (now Tableau’s VP, Operations, Tom Walker), an OEM deal with Hyperion (now Oracle), funding from New Enterprise Associates, a PC Magazine award for “Product of the Year” just one year after launch, and now over 50,000 people in 50+ countries benefiting from the breakthrough.

also see http://www.tableausoftware.com/about/leadership

http://www.tableausoftware.com/about/board

—————————————————————————-

and now  a demo I ran on the Kaggle contest data (it is a csv dataset with 95000 rows)

I found Tableau works extremely good at pivoting data and visualizing it -almost like Excel on  Steroids. Download the free version here ( I dont know about an academic program (see links below) but software is not expensive at all)

http://buy.tableausoftware.com/

Desktop Personal Edition

The Personal Edition is a visual analysis and reporting solution for data stored in Excel, MS Access or Text Files. Available via download.

Product Information
$999*

Desktop Professional Edition

The Professional Edition is a visual analysis and reporting solution for data stored in MS SQL Server, MS Analysis Services, Oracle, IBM DB2, Netezza, Hyperion Essbase, Teradata, Vertica, MySQL, PostgreSQL, Firebird, Excel, MS Access or Text Files. Available via download.

Product Information
$1800*

Tableau Server

Tableau Server enables users of Tableau Desktop Professional to publish workbooks and visualizations to a server where users with web browsers can access and interact with the results. Available via download.

Product Information
Contact Us

* Price is per Named User and includes one year of maintenance (upgrades and support). Products are made available as a download immediately after purchase. You may revisit the download site at any time during your current maintenance period to access the latest releases.

 

 

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Stuff I like to Read to Kush: Kush's Blog

RSS
Image via Wikipedia

I am putting together a list of top 500 Blogs on –

 

Some additional points-

  • I like YCombinator‘s Hacker News– so the auto parsed links are like that on main page. They lead to original websites.
  • Comments are disabled, feed is jumbled, only 40 word excerpts are shown.
  • Intent is also to show open source blogs and enterprise blogs at same time (regardless of advertising by vendors 😉 )
  • If your blog feed is there, I will keep it there – either dont write or dont use RSS if you dont want to share
  • If your blog feed is not there, it is probably not there for a reason.
  • No ads will be shown NOW or FOREVER on that site.

And after all that noise- you can see Kush’s Blog –http://www.kushohri.com/

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R Apache – The next frontier of R Computing

I am currently playing/ trying out RApache- one more excellent R product from Vanderbilt’s excellent Dept of Biostatistics and it’s prodigious coder Jeff Horner.

The big ninja himself

I really liked the virtual machine idea- you can download a virtual image of Rapache and play with it- .vmx is easy to create and great to share-

http://rapache.net/vm.html

Basically using R Apache (with an EC2 on backend) can help you create customized dashboards, BI apps, etc all using R’s graphical and statistical capabilities.

What’s R Apache?

As  per

http://biostat.mc.vanderbilt.edu/wiki/Main/RapacheWebServicesReport

Rapache embeds the R interpreter inside the Apache 2 web server. By doing this, Rapache realizes the full potential of R and its facilities over the web. R programmers configure appache by mapping Universal Resource Locaters (URL’s) to either R scripts or R functions. The R code relies on CGI variables to read a client request and R’s input/output facilities to write the response.

One advantage to Rapache’s architecture is robust multi-process management by Apache. In contrast to Rserve and RSOAP, Rapache is a pre-fork server utilizing HTTP as the communications protocol. Another advantage is a clear separation, a loose coupling, of R code from client code. With Rserve and RSOAP, the client must send data and R commands to be executed on the server. With Rapache the only client requirements are the ability to communicate via HTTP. Additionally, Rapache gains significant authentication, authorization, and encryption mechanism by virtue of being embedded in Apache.

Existing Demos of Architechture based on R Apache-

  1. http://rweb.stat.ucla.edu/ggplot2/ An interactive web dashboard for plotting graphics based on csv or Google Spreadsheet Data
  2. http://labs.dataspora.com/gameday/ A demo visualization of a web based dashboard system of baseball pitches by pitcher by player 

 

 

 

 

 

 

 

3. http://data.vanderbilt.edu/rapache/bbplot For baseball results – a demo of a query based web dashboard system- very good BI feel.

Whats coming next in R Apache?

You can  download version 1.1.10 of rApache now. There
are only two significant changes and you don’t have to edit your
apache config or change any code (just recompile rApache and
reinstall):

1) Error reporting should be more informative. both when you
accidentally introduce errors in the Apache config, and when your code
introduces warnings and errors from web requests.

I’ve struggled with this one for awhile, not really knowing what
strategy would be best. Basically, rApache hooks into the R I/O layer
at such a low level that it’s hard to capture all warnings and errors
as they occur and introduce them to the user in a sane manner. In
prior releases, when ROutputErrors was in effect (either the apache
directive or the R function) one would typically see a bunch of grey
boxes with a red outline with a title of RApache Warning/Error!!!.
Unfortunately those grey boxes could contain empty lines, one line of
error, or a few that relate to the lines in previously displayed
boxes. Really a big uninformative mess.

The new approach is to print just one warning box with the title
“”Oops!!! <b>rApache</b> has something to tell you. View source and
read the HTML comments at the end.” and then as the title implies you
can read the HTML comment located at the end of the file… after the
closing html. That way, you’re actually reading how R would present
the warnings and errors to you as if you executed the code at the R
command prompt. And if you don’t use ROutputErrors, the warning/error
messages are printed in the Apache log file, just as they were before,
but nicer 😉

2) Code dispatching has changed so please let me know if I’ve
introduced any strange behavior.

This was necessary to enhance error reporting. Prior to this release,
rApache would use R’s C API exclusively to build up the call to your
code that is then passed to R’s evaluation engine. The advantage to
this approach is that it’s much more efficient as there is no parsing
involved, however all information about parse errors, files which
produced errors, etc. were lost. The new approach uses R’s built-in
parse function to build up the call and then passes it of to R. A
slight overhead, but it should be negligible. So, if you feel that
this approach is too slow OR I’ve introduced bugs or strange behavior,
please let me know.

FUTURE PLANS

I’m gaining more experience building Debian/Ubuntu packages each day,
so hopefully by some time in 2011 you can rely on binary releases for
these distributions and not install rApache from source! Fingers
crossed!

Development on the rApache 1.1 branch will be winding down (save bug
fix releases) as I transition to the 1.2 branch. This will involve
taking out a small chunk of code that defines the rApache development
environment (all the CGI variables and the functions such as
setHeader, setCookie, etc) and placing it in its own R package…
unnamed as of yet. This is to facilitate my development of the ralite
R package, a small single user cross-platform web server.

The goal for ralite is to speed up development of R web applications,
take out a bit of friction in the development process by not having to
run the full rApache server. Plus it would allow users to develop in
the rApache enronment while on windows and later deploy on more
capable server environments. The secondary goal for ralite is it’s use
in other web server environments (nginx and IIS come to mind) as a
persistent per-client process.

And finally, wiki.rapache.net will be the new www.rapache.net once I
translate the manual over… any day now.

From –http://biostat.mc.vanderbilt.edu/wiki/Main/JeffreyHorner

 

 

Not convinced ?- try the demos above.

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Cisco SocialMiner

A highly simplified version of the RSS feed ic...
Image via Wikipedia

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).

 

 

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)

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