10 Ways We will miss Steve Jobs

I am not an Apple fanboy.In fact I dont use a Mac (because Linux works well for me at much cheaper rates)

I am going to miss Steve Jobs like I miss …… still.

1) The Original Pirate – I liked Steve Jobs ever since I saw Pirates of Silicon Valley, I wanted to be like the Jobs who created jobs http://en.wikipedia.org/wiki/Pirates_of_Silicon_Valley

Artists steal. Yeah baby!

2) Music -Itunes Improbably the man who came up with the idea of music @ 99 cents helped more artists earn money in the era of Napster. Music piracy is not dead, but at 99 cents you CAN afford the songs

3) Aesthetics- and Design- as competitive barriers. It was all about the interface. People care about interfaces. Shoody software wont sell.

4) Portable Music- yes I once wrote a poem on my first Ipod. http://www.decisionstats.com/ode-to-an-ipod/ No , it doesnot rank as the top ten poems on Ipod in SERP

Walkman ‘s evolution was the Ipod – and it was everywhere.

5) Big Phones can be cool too- I loved my IPhone and so did everyone. But thats because making cool phones before that was all about making the tiniest thinnest phone. Using Videochat on Iphone and webs surfing were way much cooler than anything before or since.

6) Apps for Money for Geeks. Yes the Apps marketplace was more enriching to the geek universe than all open source put together.

7) Turtleneck Steve- You know when Steve Jobs was about to make a presentation because one week before and one week later the whole tech media behaved like either a fanboy or we are too cool to be an Apple fanboy but we will report it still. The man who wrote no code sold more technology than everyone else using just a turtleneck and presentations.

8) Pixar toons- Yes Pixar toons made sure cartoons were pieces of art and not just funny stuff anymore. This one makes me choke up

9) Kicking Microsoft butt- Who else but Steve can borrow money from MS and then beat it in every product it wanted to.

10) Not being evil. Steve Jobs made more money for more geeks than anyone. and he made it look good! The original DONT BE EVIL guy who never needed to say it aloud

Take a bow Steve Jobs (or touch the first Apple product that comes to your hand after reading this!)

The article was first written on Aug 25,2011 on Steve Jobs resignation news.It has been updated to note his departing from this planet as of yesterday.

 

 

 

 

Using Google Fusion Tables from #rstats

But after all that- I was quite happy to see Google Fusion Tables within Google Docs. Databases as a service ? Not quite but still quite good, and lets see how it goes.

https://www.google.com/fusiontables/DataSource?dsrcid=implicit&hl=en_US&pli=1

http://googlesystem.blogspot.com/2011/09/fusion-tables-new-google-docs-app.html

 

But what interests me more is

http://code.google.com/apis/fusiontables/docs/developers_guide.html

The Google Fusion Tables API is a set of statements that you can use to search for and retrieve Google Fusion Tables data, insert new data, update existing data, and delete data. The API statements are sent to the Google Fusion Tables server using HTTP GET requests (for queries) and POST requests (for inserts, updates, and deletes) from a Web client application. The API is language agnostic: you can write your program in any language you prefer, as long as it provides some way to embed the API calls in HTTP requests.

The Google Fusion Tables API does not provide the mechanism for submitting the GET and POST requests. Typically, you will use an existing code library that provides such functionality; for example, the code libraries that have been developed for the Google GData API. You can also write your own code to implement GET and POST requests.

Also see http://code.google.com/apis/fusiontables/docs/sample_code.html

 

Google Fusion Tables API Sample Code

Libraries

SQL API

Language Library Public repository Samples
Python Fusion Tables Python Client Library fusion-tables-client-python/ Samples
PHP Fusion Tables PHP Client Library fusion-tables-client-php/ Samples

Featured Samples

An easy way to learn how to use an API can be to look at sample code. The table above provides links to some basic samples for each of the languages shown. This section highlights particularly interesting samples for the Fusion Tables API.

SQL API

Language Featured samples API version
cURL
  • Hello, cURLA simple example showing how to use curl to access Fusion Tables.
SQL API
Google Apps Script SQL API
Java
  • Hello, WorldA simple walkthrough that shows how the Google Fusion Tables API statements work.
  • OAuth example on fusion-tables-apiThe Google Fusion Tables team shows how OAuth authorization enables you to use the Google Fusion Tables API from a foreign web server with delegated authorization.
SQL API
Python
  • Docs List ExampleDemonstrates how to:
    • List tables
    • Set permissions on tables
    • Move a table to a folder
Docs List API
Android (Java)
  • Basic Sample ApplicationDemo application shows how to create a crowd-sourcing application that allows users to report potholes and save the data to a Fusion Table.
SQL API
JavaScript – FusionTablesLayer Using the FusionTablesLayer, you can display data on a Google Map

Also check out FusionTablesLayer Builder, which generates all the code necessary to include a Google Map with a Fusion Table Layer on your own website.

FusionTablesLayer, Google Maps API
JavaScript – Google Chart Tools Using the Google Chart Tools, you can request data from Fusion Tables to use in visualizations or to display directly in an HTML page. Note: responses are limited to 500 rows of data.

Google Chart Tools

External Resources

Google Fusion Tables is dedicated to providing code examples that illustrate typical uses, best practices, and really cool tricks. If you do something with the Google Fusion Tables API that you think would be interesting to others, please contact us at googletables-feedback@google.com about adding your code to our Examples page.

  • Shape EscapeA tool for uploading shape files to Fusion Tables.
  • GDALOGR Simple Feature Library has incorporated Fusion Tables as a supported format.
  • Arc2CloudArc2Earth has included support for upload to Fusion Tables via Arc2Cloud.
  • Java and Google App EngineODK Aggregate is an AppEngine application by the Open Data Kit team, uses Google Fusion Tables to store survey data that is collected through input forms on Android mobile phones. Notable code:
  • R packageAndrei Lopatenko has written an R interface to Fusion Tables so Fusion Tables can be used as the data store for R.
  • RubySimon Tokumine has written a Ruby gem for access to Fusion Tables from Ruby.

 

Updated-You can use Google Fusion Tables from within R from http://andrei.lopatenko.com/rstat/fusion-tables.R

 

ft.connect <- function(username, password) {
  url = "https://www.google.com/accounts/ClientLogin";
  params = list(Email = username, Passwd = password, accountType="GOOGLE", service= "fusiontables", source = "R_client_API")
 connection = postForm(uri = url, .params = params)
 if (length(grep("error", connection, ignore.case = TRUE))) {
 	stop("The wrong username or password")
 	return ("")
 }
 authn = strsplit(connection, "\nAuth=")[[c(1,2)]]
 auth = strsplit(authn, "\n")[[c(1,1)]]
 return (auth)
}

ft.disconnect <- function(connection) {
}

ft.executestatement <- function(auth, statement) {
      url = "http://tables.googlelabs.com/api/query"
      params = list( sql = statement)
      connection.string = paste("GoogleLogin auth=", auth, sep="")
      opts = list( httpheader = c("Authorization" = connection.string))
      result = postForm(uri = url, .params = params, .opts = opts)
      if (length(grep("<HTML>\n<HEAD>\n<TITLE>Parse error", result, ignore.case = TRUE))) {
      	stop(paste("incorrect sql statement:", statement))
      }
      return (result)
}

ft.showtables <- function(auth) {
   url = "http://tables.googlelabs.com/api/query"
   params = list( sql = "SHOW TABLES")
   connection.string = paste("GoogleLogin auth=", auth, sep="")
   opts = list( httpheader = c("Authorization" = connection.string))
   result = getForm(uri = url, .params = params, .opts = opts)
   tables = strsplit(result, "\n")
   tableid = c()
   tablename = c()
   for (i in 2:length(tables[[1]])) {
     	str = tables[[c(1,i)]]
   	    tnames = strsplit(str,",")
   	    tableid[i-1] = tnames[[c(1,1)]]
   	    tablename[i-1] = tnames[[c(1,2)]]
   	}
   	tables = data.frame( ids = tableid, names = tablename)
    return (tables)
}

ft.describetablebyid <- function(auth, tid) {
   url = "http://tables.googlelabs.com/api/query"
   params = list( sql = paste("DESCRIBE", tid))
   connection.string = paste("GoogleLogin auth=", auth, sep="")
   opts = list( httpheader = c("Authorization" = connection.string))
   result = getForm(uri = url, .params = params, .opts = opts)
   columns = strsplit(result,"\n")
   colid = c()
   colname = c()
   coltype = c()
   for (i in 2:length(columns[[1]])) {
     	str = columns[[c(1,i)]]
   	    cnames = strsplit(str,",")
   	    colid[i-1] = cnames[[c(1,1)]]
   	    colname[i-1] = cnames[[c(1,2)]]
   	    coltype[i-1] = cnames[[c(1,3)]]
   	}
   	cols = data.frame(ids = colid, names = colname, types = coltype)
    return (cols)
}

ft.describetable <- function (auth, table_name) {
   table_id = ft.idfromtablename(auth, table_name)
   result = ft.describetablebyid(auth, table_id)
   return (result)
}

ft.idfromtablename <- function(auth, table_name) {
    tables = ft.showtables(auth)
	tableid = tables$ids[tables$names == table_name]
	return (tableid)
}

ft.importdata <- function(auth, table_name) {
	tableid = ft.idfromtablename(auth, table_name)
	columns = ft.describetablebyid(auth, tableid)
	column_spec = ""
	for (i in 1:length(columns)) {
		column_spec = paste(column_spec, columns[i, 2])
		if (i < length(columns)) {
			column_spec = paste(column_spec, ",", sep="")
		}
	}
	mdata = matrix(columns$names,
	              nrow = 1, ncol = length(columns),
	              dimnames(list(c("dummy"), columns$names)), byrow=TRUE)
	select = paste("SELECT", column_spec)
	select = paste(select, "FROM")
	select = paste(select, tableid)
	result = ft.executestatement(auth, select)
    numcols = length(columns)
    rows = strsplit(result, "\n")
    for (i in 3:length(rows[[1]])) {
    	row = strsplit(rows[[c(1,i)]], ",")
    	mdata = rbind(mdata, row[[1]])
   	}
   	output.frame = data.frame(mdata[2:length(mdata[,1]), 1])
   	for (i in 2:ncol(mdata)) {
   		output.frame = cbind(output.frame, mdata[2:length(mdata[,i]),i])
   	}
   	colnames(output.frame) = columns$names
    return (output.frame)
}

quote_value <- function(value, to_quote = FALSE, quote = "'") {
	 ret_value = ""
     if (to_quote) {
     	ret_value = paste(quote, paste(value, quote, sep=""), sep="")
     } else {
     	ret_value = value
     }
     return (ret_value)
}

converttostring <- function(arr, separator = ", ", column_types) {
	con_string = ""
	for (i in 1:(length(arr) - 1)) {
		value = quote_value(arr[i], column_types[i] != "number")
		con_string = paste(con_string, value)
	    con_string = paste(con_string, separator, sep="")
	}

    if (length(arr) >= 1) {
    	value = quote_value(arr[length(arr)], column_types[length(arr)] != "NUMBER")
    	con_string = paste(con_string, value)
    }
}

ft.exportdata <- function(auth, input_frame, table_name, create_table) {
	if (create_table) {
       create.table = "CREATE TABLE "
       create.table = paste(create.table, table_name)
       create.table = paste(create.table, "(")
       cnames = colnames(input_frame)
       for (columnname in cnames) {
         create.table = paste(create.table, columnname)
    	 create.table = paste(create.table, ":string", sep="")
    	   if (columnname != cnames[length(cnames)]){
    		  create.table = paste(create.table, ",", sep="")
           }
       }
      create.table = paste(create.table, ")")
      result = ft.executestatement(auth, create.table)
    }
    if (length(input_frame[,1]) > 0) {
    	tableid = ft.idfromtablename(auth, table_name)
	    columns = ft.describetablebyid(auth, tableid)
	    column_spec = ""
	    for (i in 1:length(columns$names)) {
		   column_spec = paste(column_spec, columns[i, 2])
		   if (i < length(columns$names)) {
			  column_spec = paste(column_spec, ",", sep="")
		   }
	    }
    	insert_prefix = "INSERT INTO "
    	insert_prefix = paste(insert_prefix, tableid)
    	insert_prefix = paste(insert_prefix, "(")
    	insert_prefix = paste(insert_prefix, column_spec)
    	insert_prefix = paste(insert_prefix, ") values (")
    	insert_suffix = ");"
    	insert_sql_big = ""
    	for (i in 1:length(input_frame[,1])) {
    		data = unlist(input_frame[i,])
    		values = converttostring(data, column_types  = columns$types)
    		insert_sql = paste(insert_prefix, values)
    		insert_sql = paste(insert_sql, insert_suffix) ;
    		insert_sql_big = paste(insert_sql_big, insert_sql)
    		if (i %% 500 == 0) {
    			ft.executestatement(auth, insert_sql_big)
    			insert_sql_big = ""
    		}
    	}
        ft.executestatement(auth, insert_sql_big)
    }
}

US-CERT Incident Reporting System

Here are some resources if your cyber resources have been breached. Note the form doesnot use CAPTCHA at all

US-CERT Incident Reporting System (their head Randy Vickers quit last week)

https://forms.us-cert.gov/report/

Using the US-CERT Incident Reporting SystemIn order for us to respond appropriately, please answer the questions as completely and accurately as possible. Questions that must be answered are labeled “Required”. As always, we will protect your sensitive information. This web site uses Secure Sockets Layer (SSL) to provide secure communications. Your browser must allow at least 40-bit encryption. This method of communication is much more secure than unencrypted email.  Continue reading “US-CERT Incident Reporting System”

Interview Mike Boyarski Jaspersoft

Here is an interview with Mike Boyarski , Director Product Marketing at Jaspersoft

.

 

the largest BI community with over 14 million downloads, nearly 230,000 registered members, representing over 175,000 production deployments, 14,000 customers, across 100 countries.

Ajay- Describe your career in science from Biology to marketing great software.
Mike- I studied Biology with the assumption I’d pursue a career in medicine. It took about 2 weeks during an internship at a Los Angeles hospital to determine I should do something else.  I enjoyed learning about life science, but the whole health care environment was not for me.  I was initially introduced to enterprise-level software while at Applied Materials within their Microcontamination group.  I was able to assist with an internal application used to collect contamination data.  I later joined Oracle to work on an Oracle Forms application used to automate the production of software kits (back when documentation and CDs had to be physically shipped to recognize revenue). This gave me hands on experience with Oracle 7, web application servers, and the software development process.
I then transitioned to product management for various products including application servers, software appliances, and Oracle’s first generation SaaS based software infrastructure. In 2006, with the Siebel and PeopleSoft acquisitions underway, I moved on to Ingres to help re-invigorate their solid yet antiquated technology. This introduced me to commercial open source software and the broader Business Intelligence market.  From Ingres I joined Jaspersoft, one of the first and most popular open source Business Intelligence vendors, serving as head of product marketing since mid 2009.
Ajay- Describe some of the new features in Jaspersoft 4.1 that help differentiate it from the rest of the crowd. What are the exciting product features we can expect from Jaspersoft down the next couple of years.
Mike- Jaspersoft 4.1 was an exciting release for our customers because we were able to extend the latest UI advancements in our ad hoc report designer to the data analysis environment. Now customers can use a unified intuitive web-based interface to perform several powerful and interactive analytic functions across any data source, whether its relational, non-relational, or a Big Data source.
 The reality is that most (roughly 70%) of todays BI adoption is in the form of reports and dashboards. These tools are used to drive and measure an organizations business, however, data analysis presents the most strategic opportunity for companies because it can identify new opportunities, efficiencies, and competitive differentiation.  As more data comes online, the difference between those companies that are successful and those that are not will likely be attributed to their ability to harness data analysis techniques to drive and improve business performance. Thus, with Jaspersoft 4.1, and our improved ad hoc reporting and analysis UI we can effectively address a broader set of BI requirements for organizations of all sizes.
Ajay-  What do you think is a good metric to measure influence of an open source software product – is it revenue or is it number of downloads or number of users. How does Jaspersoft do by these counts.
Mike- History has shown that open source software is successful as a “bottoms up” disrupter within IT or the developer market.  Today, many new software projects and startup ventures are birthed on open source software, often initiated with little to no budget. As the organization achieves success with a particular project, the next initiative tends to be larger and more strategic, often displacing what was historically solved with a proprietary solution. These larger deployments strengthen the technology over time.
Thus, the more proven and battle tested an open source solution is, often measured via downloads, deployments, community size, and community activity, usually equates to its long term success. Linux, Tomcat, and MySQL have plenty of statistics to model this lifecycle. This model is no different for open source BI.
The success to date of Jaspersoft is directly tied to its solid proven technology and the vibrancy of the community.  We proudly and openly claim to have the largest BI community with over 14 million downloads, nearly 230,000 registered members, representing over 175,000 production deployments, 14,000 customers, across 100 countries.  Every day, 30,000 developers are using Jaspersoft to build BI applications.  Behind Excel, its hard to imagine a more widely used BI tool in the market.  Jaspersoft could not reach these kind of numbers with crippled or poorly architected software.
Ajay- What are your plans for leveraging cloud computing, mobile and tablet platforms and for making Jaspersoft more easy and global  to use.

Google Speed Test

Here is a new service in beta for helping test your website for speed. It is continuing series of initiatives for Google to help the internet (and their own computing resources)

If you want to request access to the limited beta

Request Access – Here

https://docs.google.com/spreadsheet/viewform?hl=en_US&formkey=dDdjcmNBZFZsX2c0SkJPQnR3aGdnd0E6MQ&ifq

 

Continue reading “Google Speed Test”

Web Analytics Certifications by Google

Google has a whole list of certifications for people wanting to be certified in analytics, and advertising related to internet.

Continue reading “Web Analytics Certifications by Google”