Analytics 2011 Conference


The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.

Conference Details

October 24-25, 2011
Grande Lakes Resort
Orlando, FL

Analytics 2011 topic areas include:

Updated Interview Elissa Fink -VP Tableau Software

Here is an interview with Elissa Fink, VP Marketing of that new wonderful software called Tableau that makes data visualization so nice and easy to learn and work with.

Elissa Fink, VP, Marketing

Ajay-  Describe your career journey from high school to over 20 plus years in marketing. What are the various trends that you have seen come and go in marketing.

Elissa- I studied literature and linguistics in college and didn’t discover analytics until my first job selling advertising for the Wall Street Journal. Oddly enough, the study of linguistics is not that far from decision analytics: they both are about taking a structured view of information and trying to see and understand common patterns. At the Journal, I was completely captivated analyzing and comparing readership data. At the same time, the idea of using computers in marketing was becoming more common. I knew that the intersection of technology and marketing was going to radically change things – how we understand consumers, how we market and sell products, and how we engage with customers. So from that point on, I’ve always been focused on technology and marketing, whether it’s working as a marketer at technology companies or applying technology to marketing problems for other types of companies.  There have been so many interesting trends. Taking a long view, a key trend I’ve noticed is how marketers work to understand, influence and motivate consumer behavior. We’ve moved marketing from where it was primarily unpredictable, qualitative and aimed at talking to mass audiences, where the advertising agency was king. Now it’s a discipline that is more data-driven, quantitative and aimed at conversations with individuals, where the best analytics wins. As with any trend, the pendulum swings far too much to either side causing backlashes but overall, I think we are in a great place now. We are using data-driven analytics to understand consumer behavior. But pure analytics is not the be-all, end-all; good marketing has to rely on understanding human emotions, intuition and gut feel – consumers are far from rational so taking only a rational or analytical view of them will never explain everything we need to know.

Ajay- Do you think technology companies are still predominantly dominated by men . How have you seen diversity evolve over the years. What initiatives has Tableau taken for both hiring and retaining great talent.

Elissa- The thing I love about the technology industry is that its key success metrics – inventing new products that rapidly gain mass adoption in pursuit of making profit – are fairly objective. There’s little subjective nature to the counting of dollars collected selling a product and dollars spent building a product. So if a female can deliver a better product and bigger profits faster and better, then that female is going to get the resources, jobs, power and authority to do exactly that. That’s not to say that the technology industry is gender-blind, race-blind, etc. It isn’t – technology is far from perfect. For example, the industry doesn’t have enough diversity in positions of power. But I think overall, in comparison to a lot of other industries, it’s pretty darn good at giving people with great ideas the opportunities to realize their visions regardless of their backgrounds or characteristics.

At Tableau, we are very serious about bringing in and developing talented people – they are the key to our growth and success. Hiring is our #1 initiative so we’ve spent a lot of time and energy both on finding great candidates and on making Tableau a place that they want to work. This includes things like special recruiting events, employee referral programs, a flexible work environment, fun social events, and the rewards of working for a start-up. Probably our biggest advantage is the company itself – working with people you respect on amazing, cutting-edge products that delight customers and are changing the world is all too rare in the industry but a reality at Tableau. One of our senior software developers put it best when he wrote “The emphasis is on working smarter rather than longer: family and friends are why we work, not the other way around. Tableau is all about happy, energized employees executing at the highest level and delivering a highly usable, high quality, useful product to our customers.” People who want to be at a place like that should check out our openings at

Ajay- What are most notable features in tableau’s latest edition. What are the principal software that competes with Tableau Software products and how would you say Tableau compares with them.

Elissa- Tableau 6.1 will be out in July and we are really excited about it for 3 reasons.

First, we’re introducing our mobile business intelligence capabilities. Our customers can have Tableau anywhere they need it. When someone creates an interactive dashboard or analytical application with Tableau and it’s viewed on a mobile device, an iPad in particular, the viewer will have a native, touch-optimized experience. No trying to get your fingertips to act like a mouse. And the author didn’t have to create anything special for the iPad; she just creates her analytics the usual way in Tableau. Tableau knows the dashboard is being viewed on an iPad and presents an optimized experience.

Second, we’ve take our in-memory analytics engine up yet another level. Speed and performance are faster and now people can update data incrementally rapidly. Introduced in 6.0, our data engine makes any data fast in just a few clicks. We don’t run out of memory like other applications. So if I build an incredible dashboard on my 8-gig RAM PC and you try to use it on your 2-gig RAM laptop, no problem.

And, third, we’re introducing more features for the international markets – including French and German versions of Tableau Desktop along with more international mapping options.  It’s because we are constantly innovating particularly around user experience that we can compete so well in the market despite our relatively small size. Gartner’s seminal research study about the Business Intelligence market reported a massive market shift earlier this year: for the first time, the ease-of-use of a business intelligence platform was more important than depth of functionality. In other words, functionality that lots of people can actually use is more important than having sophisticated functionality that only specialists can use. Since we focus so heavily on making easy-to-use products that help people rapidly see and understand their data, this is good news for our customers and for us.

Ajay-  Cloud computing is the next big thing with everyone having a cloud version of their software. So how would you run Cloud versions of Tableau Server (say deploying it on an Amazon Ec2  or a private cloud)

Elissa- In addition to the usual benefits espoused about Cloud computing, the thing I love best is that it makes data and information more easily accessible to more people. Easy accessibility and scalability are completely aligned with Tableau’s mission. Our free product Tableau Public and our product for commercial websites Tableau Digital are two Cloud-based products that deliver data and interactive analytics anywhere. People often talk about large business intelligence deployments as having thousands of users. With Tableau Public and Tableau Digital, we literally have millions of users. We’re serving up tens of thousands of visualizations simultaneously – talk about accessibility and scalability!  We have lots of customers connecting to databases in the Cloud and running Tableau Server in the Cloud. It’s actually not complex to set up. In fact, we focus a lot of resources on making installation and deployment easy and fast, whether it’s in the cloud, on premise or what have you. We don’t want people to have spend weeks or months on massive roll-out projects. We want it to be minutes, hours, maybe a day or 2. With the Cloud, we see that people can get started and get results faster and easier than ever before. And that’s what we’re about.

Ajay- Describe some of the latest awards that Tableau has been wining. Also how is Tableau helping universities help address the shortage of Business Intelligence and Big Data professionals.

Elissa-Tableau has been very fortunate. Lately, we’ve been acknowledged by both Gartner and IDC as the fastest growing business intelligence software vendor in the world. In addition, our customers and Tableau have won multiple distinctions including InfoWorld Technology Leadership awards, Inc 500, Deloitte Fast 500, SQL Server Magazine Editors’ Choice and Community Choice awards, Data Hero awards, CODiEs, American Business Awards among others. One area we’re very passionate about is academia, participating with professors, students and universities to help build a new generation of professionals who understand how to use data. Data analysis should not be exclusively for specialists. Everyone should be able to see and understand data, whatever their background. We come from academic roots, having been spun out of a Stanford research project. Consequently, we strongly believe in supporting universities worldwide and offer 2 academic programs. The first is Tableau For Teaching, where any professor can request free term-length licenses of Tableau for academic instruction during his or her courses. And, we offer a low-cost Student Edition of Tableau so that students can choose to use Tableau in any of their courses at any time.

Elissa Fink, VP Marketing,Tableau Software


Elissa Fink is Tableau Software’s Vice President of Marketing. With 20+ years helping companies improve their marketing operations through applied data analysis, Elissa has held executive positions in marketing, business strategy, product management, and product development. Prior to Tableau, Elissa was EVP Marketing at IXI Corporation, now owned by Equifax. She has also served in executive positions at Tele Atlas (acquired by TomTom), TopTier Software (acquired by SAP), and Nielsen/Claritas. Elissa also sold national advertising for the Wall Street Journal. She’s a frequent speaker and has spoken at conferences including the DMA, the NCDM, Location Intelligence, the AIR National Forum and others. Elissa is a graduate of Santa Clara University and holds an MBA in Marketing and Decision Systems from the University of Southern California.

Elissa first discovered Tableau late one afternoon at her previous company. Three hours later, she was still “at play” with her data. “After just a few minutes using the product, I was getting answers to questions that were taking my company’s programmers weeks to create. It was instantly obvious that Tableau was on a special mission with something unique to offer the world. I just had to be a part of it.”

To know more – read at

and existing data viz at

Storm seasons: measuring and tracking key indicators
What’s happening with local real estate prices?
How are sales opportunities shaping up?
Identify your best performing products
Applying user-defined parameters to provide context
Not all tech companies are rocket ships
What’s really driving the economy?
Considering factors and industry influencers
The complete orbit along the inside, or around a fixed circle
How early do you have to be at the airport?
What happens if sales grow but so does customer churn?
What are the trends for new retail locations?
How have student choices changed?
Do patients who disclose their HIV status recover better?
Closer look at where gas prices swing in areas of the U.S.
U.S. Census data shows more women of greater age
Where do students come from and how does it affect their grades?
Tracking customer service effectiveness
Comparing national and local test scores
What factors correlate with high overall satisfaction ratings?
Fund inflows largely outweighed outflows well after the bubble
Which programs are competing for federal stimulus dollars?
Oil prices and volatility
A classic candlestick chart
How do oil, gold and CPI relate to the GDP growth rate?


#Rstats for Business Intelligence

This is a short list of several known as well as lesser known R ( #rstats) language codes, packages and tricks to build a business intelligence application. It will be slightly Messy (and not Messi) but I hope to refine it someday when the cows come home.

It assumes that BI is basically-

a Database, a Document Database, a Report creation/Dashboard pulling software as well unique R packages for business intelligence.

What is business intelligence?

Seamless dissemination of data in the organization. In short let it flow- from raw transactional data to aggregate dashboards, to control and test experiments, to new and legacy data mining models- a business intelligence enabled organization allows information to flow easily AND capture insights and feedback for further action.

BI software has lately meant to be just reporting software- and Business Analytics has meant to be primarily predictive analytics. the terms are interchangeable in my opinion -as BI reports can also be called descriptive aggregated statistics or descriptive analytics, and predictive analytics is useless and incomplete unless you measure the effect in dashboards and summary reports.

Data Mining- is a bit more than predictive analytics- it includes pattern recognizability as well as black box machine learning algorithms. To further aggravate these divides, students mostly learn data mining in computer science, predictive analytics (if at all) in business departments and statistics, and no one teaches metrics , dashboards, reporting  in mainstream academia even though a large number of graduates will end up fiddling with spreadsheets or dashboards in real careers.

Using R with

1) Databases-

I created a short list of database connectivity with R here at but R has released 3 new versions since then.

The RODBC package remains the package of choice for connecting to SQL Databases.

Details on creating DSN and connecting to Databases are given at

For document databases like MongoDB and CouchDB

( what is the difference between traditional RDBMS and NoSQL if you ever need to explain it in a cocktail conversation

Basically dispensing with the relational setup, with primary and foreign keys, and with the additional overhead involved in keeping transactional safety, often gives you extreme increases in performance

NoSQL is a kind of database that doesn’t have a fixed schema like a traditional RDBMS does. With the NoSQL databases the schema is defined by the developer at run time. They don’t write normal SQL statements against the database, but instead use an API to get the data that they need.

instead relating data in one table to another you store things as key value pairs and there is no database schema, it is handled instead in code.)

I believe any corporation with data driven decision making would need to both have atleast one RDBMS and one NoSQL for unstructured data-Ajay. This is a sweeping generic statement 😉 , and is an opinion on future technologies.

  • Use RMongo


Connecting to a MongoDB database from R using Java

Also see a nice basic analysis using R Mongo from

For CouchDB

please see and

  • First install RCurl and RJSONIO. You’ll have to download the tar.gz’s if you’re on a Mac. For the second part, we’ll need to installR4CouchDB,

2) External Report Creating Software-

Jaspersoft- It has good integration with R and is a certified Revolution Analytics partner (who seem to be the only ones with a coherent #Rstats go to market strategy- which begs the question – why is the freest and finest stats software having only ONE vendor- if it was so great lots of companies would make exclusive products for it – (and some do -see and


we see

RevoConnectR for JasperReports Server

RevoConnectR for JasperReports Server RevoConnectR for JasperReports Server is a Java library interface between JasperReports Server and Revolution R Enterprise’s RevoDeployR, a standardized collection of web services that integrates security, APIs, scripts and libraries for R into a single server. JasperReports Server dashboards can retrieve R charts and result sets from RevoDeployR.


Using R and Pentaho
Extending Pentaho with R analytics”R” is a popular open source statistical and analytical language that academics and commercial organizations alike have used for years to get maximum insight out of information using advanced analytic techniques. In this twelve-minute video, David Reinke from Pentaho Certified Partner OpenBI provides an overview of R, as well as a demonstration of integration between R and Pentaho.
and from
R and BI – Integrating R with Open Source Business
Intelligence Platforms Pentaho and Jaspersoft
David Reinke, Steve Miller
Keywords: business intelligence
Increasingly, R is becoming the tool of choice for statistical analysis, optimization, machine learning and
visualization in the business world. This trend will only escalate as more R analysts transition to business
from academia. But whereas in academia R is often the central tool for analytics, in business R must coexist
with and enhance mainstream business intelligence (BI) technologies. A modern BI portfolio already includes
relational databeses, data integration (extract, transform, load – ETL), query and reporting, online analytical
processing (OLAP), dashboards, and advanced visualization. The opportunity to extend traditional BI with
R analytics revolves on the introduction of advanced statistical modeling and visualizations native to R. The
challenge is to seamlessly integrate R capabilities within the existing BI space. This presentation will explain
and demo an initial approach to integrating R with two comprehensive open source BI (OSBI) platforms –
Pentaho and Jaspersoft. Our efforts will be successful if we stimulate additional progress, transparency and
innovation by combining the R and BI worlds.
The demonstration will show how we integrated the OSBI platforms with R through use of RServe and
its Java API. The BI platforms provide an end user web application which include application security,
data provisioning and BI functionality. Our integration will demonstrate a process by which BI components
can be created that prompt the user for parameters, acquire data from a relational database and pass into
RServer, invoke R commands for processing, and display the resulting R generated statistics and/or graphs
within the BI platform. Discussion will include concepts related to creating a reusable java class library of
commonly used processes to speed additional development.

If you know Java- try


and I like this list by two venerable powerhouses of the BI Open Source Movement

Open Source BI as disruptive technology

Open Source Punditry

Commercial Open Source BI Redux Dave Reinke & Steve Miller An review and update on the predictions made in our 2007 article focused on the current state of the commercial open source BI market. Also included is a brief analysis of potential options for commercial open source business models and our take on their applicability.
Open Source BI as Disruptive Technology Dave Reinke & Steve Miller Reprint of May 2007 DM Review article explaining how and why Commercial Open Source BI (COSBI) will disrupt the traditional proprietary market.

Spotlight on R

R You Ready for Open Source Statistics? Steve Miller R has become the “lingua franca” for academic statistical analysis and modeling, and is now rapidly gaining exposure in the commercial world. Steve examines the R technology and community and its relevancy to mainstream BI.
R and BI (Part 1): Data Analysis with R Steve Miller An introduction to R and its myriad statistical graphing techniques.
R and BI (Part 2): A Statistical Look at Detail Data Steve Miller The usage of R’s graphical building blocks – dotplots, stripplots and xyplots – to create dashboards which require little ink yet tell a big story.
R and BI (Part 3): The Grooming of Box and Whiskers Steve Miller Boxplots and variants (e.g. Violin Plot) are explored as an essential graphical technique to summarize data distributions by categories and dimensions of other attributes.
R and BI (Part 4): Embellishing Graphs Steve Miller Lattices and logarithmic data transformations are used to illuminate data density and distribution and find patterns otherwise missed using classic charting techniques.
R and BI (Part 5): Predictive Modelling Steve Miller An introduction to basic predictive modelling terminology and techniques with graphical examples created using R.
R and BI (Part 6) :
Re-expressing Data
Steve Miller How do you deal with highly skewed data distributions? Standard charting techniques on this “deviant” data often fail to illuminate relationships. This article explains techniques to re-express skewed data so that it is more understandable.
The Stock Market, 2007 Steve Miller R-based dashboards are presented to demonstrate the return performance of various asset classes during 2007.
Bootstrapping for Portfolio Returns: The Practice of Statistical Analysis Steve Miller Steve uses the R open source stats package and Monte Carlo simulations to examine alternative investment portfolio returns…a good example of applied statistics using R.
Statistical Graphs for Portfolio Returns Steve Miller Steve uses the R open source stats package to analyze market returns by asset class with some very provocative embedded trellis charts.
Frank Harrell, Iowa State and useR!2007 Steve Miller In August, Steve attended the 2007 Internation R User conference (useR!2007). This article details his experiences, including his meeting with long-time R community expert, Frank Harrell.
An Open Source Statistical “Dashboard” for Investment Performance Steve Miller The newly launched Dashboard Insight web site is focused on the most useful of BI tools: dashboards. With this article discussing the use of R and trellis graphics, OpenBI brings the realm of open source to this forum.
Unsexy Graphics for Business Intelligence Steve Miller Utilizing Tufte’s philosophy of maximizing the data to ink ratio of graphics, Steve demonstrates the value in dot plot diagramming. The R open source statistical/analytics software is showcased.
I think that the report generation package Brew would also qualify as a BI package, but large scale implementation remains to be seen in
a commercial business environment
  • brew: Creating Repetitive Reports
 brew: Templating Framework for Report Generation

brew implements a templating framework for mixing text and R code for report generation. brew template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module.
  • Yarr- creating reports in R
to be continued ( when I have more time and the temperature goes down from 110F in Delhi, India)

What is a White Paper?

Christine and Jimmy Wales
Image via Wikipedia

As per Jimmy Wales and his merry band at Wiki (pedia not leaky-ah)- The emphasis is mine

What is the best white paper you have read in the past 15 years.

Categories are-

  • Business benefits: Makes a business case for a certain technology or methodology.
  • Technical: Describes how a certain technology works.
  • Hybrid: Combines business benefits with technical details in a single document.
  • Policy: Makes a case for a certain political solution to a societal or economic challenge.

white paper is an authoritative report or guide that helps solve a problem. White papers are used to educate readers and help people make decisions, and are often requested and used in politics, policy, business, and technical fields. In commercial use, the term has also come to refer to documents used by businesses as a marketing or sales tool. Policy makers frequently request white papers from universities or academic personnel to inform policy developments with expert opinions or relevant research.

Government white papers

In the Commonwealth of Nations, “white paper” is an informal name for a parliamentary paper enunciating government policy; in the United Kingdom these are mostly issued as “Command papers“. White papers are issued by the government and lay out policy, or proposed action, on a topic of current concern. Although a white paper may on occasion be a consultation as to the details of new legislation, it does signify a clear intention on the part of a government to pass new law. White Papers are a “…. tool of participatory democracy … not [an] unalterable policy commitment.[1] “White Papers have tried to perform the dual role of presenting firm government policies while at the same time inviting opinions upon them.” [2]

In Canada, a white paper “is considered to be a policy document, approved by Cabinet, tabled in the House of Commons and made available to the general public.”[3] A Canadian author notes that the “provision of policy information through the use of white and green papers can help to create an awareness of policy issues among parliamentarians and the public and to encourage an exchange of information and analysis. They can also serve as educational techniques”.[4]

“White Papers are used as a means of presenting government policy preferences prior to the introduction of legislation”; as such, the “publication of a White Paper serves to test the climate of public opinion regarding a controversial policy issue and enables the government to gauge its probable impact”.[5]

By contrast, green papers, which are issued much more frequently, are more open ended. These green papers, also known as consultation documents, may merely propose a strategy to be implemented in the details of other legislation or they may set out proposals on which the government wishes to obtain public views and opinion.

White papers published by the European Commission are documents containing proposals for European Union action in a specific area. They sometimes follow a green paper released to launch a public consultation process.

For examples see the following:

 Commercial white papers

Since the early 1990s, the term white paper has also come to refer to documents used by businesses and so-called think tanks as marketing or sales tools. White papers of this sort argue that the benefits of a particular technologyproduct or policy are superior for solving a specific problem.

These types of white papers are almost always marketing communications documents designed to promote a specific company’s or group’s solutions or products. As a marketing tool, these papers will highlight information favorable to the company authorizing or sponsoring the paper. Such white papers are often used to generate sales leads, establish thought leadership, make a business case, or to educate customers or voters.

There are four main types of commercial white papers:

  • Business benefits: Makes a business case for a certain technology or methodology.
  • Technical: Describes how a certain technology works.
  • Hybrid: Combines business benefits with technical details in a single document.
  • Policy: Makes a case for a certain political solution to a societal or economic challenge.


  • Stelzner, Michael (2007). Writing White Papers: How to capture readers and keep them engaged. Poway, California: WhitePaperSource Publishing. pp. 214. ISBN 9780977716937.
  • Bly, Robert W. (2006). The White Paper Marketing Handbook. Florence, Kentucky: South-Western Educational Publishing. pp. 256. ISBN 9780324300826.
  • Kantor, Jonathan (2009). Crafting White Paper 2.0: Designing Information for Today’s Time and Attention Challenged Business Reader. Denver,Colorado: Lulu Publishing. pp. 167.ISBN 9780557163243.

Forecasting World Events Team

a large and diverse panel of forecasters, including substantial representation from government, academia, “think tanks,” and industry. Here are a few other details concerning your fellow participants:
  • At this time, over 600 people are being invited to participate. Please note that we expect that new participants will be joining the panel on a rolling basis for years to come.
  • Around 85% of these 600+ participants have at least a Bachelor’s degree, and over 60% of them have advanced degrees.
  • In terms of background training, participants represent a range of academic fields. Around 40% report a Social-Behavioral Science background, but there is also significant representation from those with backgrounds in Business (15%), the Humanities (13%), Engineering (12%), and the Natural Sciences (10%), among others.
  • The average participant age is 43 years-old, with a standard deviation of 15 years.
  • The panel’s gender composition is 75% men / 25% women, and this closely mirrors the gender ratio for all FWE registrants.
  • In addition to participation from individuals overseas, we are pleased to have eligible participants representing 44 of the 50 United States.
We are currently scheduled to begin the core forecasting study in late summer, a few months later than we initially anticipated. In the meantime, we will be readying our web-based forecasting environment and assembling our initial set of forecasting questions. As our formal launch date approaches, we will be contacting you with a link to the forecasting website and any other information you’ll need to get started. Between now and then we may reach out to you with other related announcements.
Finally, registration remains open, and we encourage you to “spread the word” by sharing our registration homepage link with your friends and colleagues.
Thanks once again for your interest in Forecasting World Events. We look forward to you joining us this summer.
The Forecasting World Events Team
E-mail is not a secure form of communication.

The confidentiality of this message cannot be guaranteed.

ps- above message was from this new contest. Enter at your initiative. Buyer Beware!.

Scholarships for students via #rstatsjobs and R-lings

A vector drawing of the University of York coa...
Image via Wikipedia

Outstandingly attractive scholarships are available for students willing to travel to Yorkshire. Thats where the Battle of Roses was fought by the British Royal Family.


Emphasis  and spaces in email above are made by me.

Message from Dr Top i   bell ow-

It is not New York but very old York, in the North of England.

The scholarships carry a tax-free stipend and financial assistance will be
given for travel expenses to and from York. Accommodation for successful
students is available on the University of York Campus.

For information about the tax-free stipend please write to

Continue reading “Scholarships for students via #rstatsjobs and R-lings”

Revolution releases R Windows for Academics for free

Logo for R
Image via Wikipedia

Based on the official email from them, God bless the merry coders at Revo-

Revolution Analytics has just released Revolution R Enterprise 4.3 for 32-bit and 64-bit Windows, a significant step forward in enterprise data analytics.  It features an updated RevoScaleR package for scalable, fast (multicore), and extensible data analysis with R. Revolution R Enterprise 4.3 for Windows also provides R 2.12.2, and includes an enhanced R Productivity Environment (RPE), a full-featured integrated development environment with visual debugging capabilities. Also available is an updated Windows release of our deployment server solution, RevoDeployR 1.2, designed to help you deliver R analytics via the Web.

As a registered user of the Academic version of Revolution R Enterprise for Windows, you can take advantage of these improvements by downloading and installing Revolution R Enterprise 4.3 today. You can install Revolution R Enterprise 4.3 side-by-side with your existing Revolution R Enterprise installations; there is no need to uninstall previous versions.


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