Democratization of Business Analytics Dashboards

I am super impressed with the following visual dashboard from IPL T20 tournament - IPL 2013 in Numbers.  For those of you not so familiar with cricket or IPL, IPL is the biggest, the most extravagant and the most lucrative cricket tournament in the world.  I like the way IPL is bringing sports analytics to the common masses.

What is impressive is that each metric (runs, wickets, or tweets) is live so these numbers get updated automatically, pretty cool for IPL and cricket fans.  Also, each metric is clickable so one can drill down to his or her heart's content.  This is a common roll-up analysis but the visualization and the real time updates make this dashboard pretty appealing.  IPL team, thanks for not putting any dials on this dashboard (LOL).

I have been influencing and now building analytics products that power these sports and various other dashboards/reports for many years.  The most fascinating thing is that these dashboards (or lets call it analytics in general) are reaching the masses like never before.  Everyone has heard of terms like democratization of data and humanization of analytics.  This is it!  The data revolution is underway.  

Now, there are many new frontiers to go after and the existing ones need to be reinvented.  Yes, the analytics market is ready for massive disruption.  This is what keeps me excited about Business Analytics space.

Happy Analyzing and Happy Friday!

Agile BI, Simple BI, Self-Serve BI - Okay, What the Hell This Thing is?

In layman's terms, anyone, including my mom, who is suffering from information overload should be able to analyze any data using simple and easy to use data visualization tools, get insights (like growth in milk usage at our home) and then share the results with my dad who should cut feeding expensive organic milk to his two cats.

Wow, that sounds pretty simple, isn't it? Yes, and precisely for that reason IDC says that this phenomenon presents a big market opportunity:

“We are at the forefront of an evolutionary market that is fraught with opportunity for innovative tools and solutions that can help users handle the information overload plaguing every major organization around the globe.” IDC Market Analysis, Worldwide Interactive Data Visualization Tools Forecast

How big of a market opportunity? $1 Billion big by 2013 and $1.6 Billion by 2015 says Gartner. See this graphics:

So someone asked me few weeks ago, how would you define simple, self-serve BI and I gave him the following definition -

Agile BI is a simple yet power-packed solution which is easy-to-use, cost-effective and offers full 360 degree experience and above all my mom should be able to use it without bugging me...

And here is my definition of a power-packed solution:

There are ZERO products that fulfill this vision today.  Products like QlikTech, Spotfire and Tableau do a pretty good job and therefore enjoy more that 70% of the market share. Where are the big guys?

"Agile" and "Big" doesn't go together I guess!

Here is how I contrasted Qlik against a large enterprise BI player:



This story is universal and gives competitive advantage to younger more agile players over their older and aging brethren because they have offered one single self-serve BI tool that could serve to many personas!





Qlik and Tableau have seen pretty solid growth over the past few years as a result of keeping their strategy simple.  Here is an older blog on Qlik showing its amazing growth: http://goo.gl/cyV7a


The most recent evidence of double digit growth in the Agile BI market was seen in Tableau's 2011 earnings: (http://apandre.wordpress.com/)

• sales doubled year over year to $72M in 2011
•  104% growth in bookings in Q4’11 and 94% growth YoY,
• WW customer base grew by 40% in 2011
•  more than 7,000 organizations use its analytics product
•  big growth with customers in Europe, where base grew by 67 percent

2011 was the year of Agile (Simple) BI and the momentum is gaining further strength. Do you know now what Agile BI a.k.a Simple BI a.k.a self-serve BI is defined as?

Happy Simplifying!

Updated Sentiment Analysis and a Word Cloud for Netflix - The R Way!

The Netflix investors must be happy and cheerful as the stock is up more than 78% since the beginning of the year (YES, 78%, Source: Yahoo Finance!).  I am not going to talk about what turned the stock around after a much talked/hyped about Netflix debacle of the late 2011 that earned Reed Hastings quite a few UNWANTED title and every one demanded his resignation from the top post.  Not so fast, Mr. Bear!  Reed Hastings must be smiling!  After a stellar performance this year including carefully released stats on viewership, streaming hours as well as a solid Q4'11 earnings, Netflix is back and most importantly viewers are back!

Well, is is not coincidental that the sentiment for Netflix is also improving, 68% of the tweets now have positive sentiment.  See the table below:

Total	Positive	Negative	Average	Total	Sentiment
Tweets  Fetched	Tweets	Tweets	Score	Tweets
499	171	80	0.281	251	68%

*Make sure you understand and interpret this analysis correctly. This analysis is not based on NLP. 

I updated the sentiment analysis that I did last year, http://goo.gl/fkfPy ,  (I was then just beginning to play with Twitter and Text Mining packages in R) and used advanced packages like "TM" and  "WordCloud".  The new analysis is based on more than 6,800 words which are most commonly prescribed in various sentiment analysis blogs/books. (Check out Hu and Liu http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html)

I came across this excellent blog by Jeffrey Bean, @JeffreyBean, (http://goo.gl/RPkFX) and his tutorial. Thank you Mr. Bean!  Please follow the instructions from Bean's slides and the R code listed there as well as the R code here:

Here is the updated R code snippets -
#Populate the list of sentiment words from Hu and Liu (http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html)

huliu.pwords <- scan('opinion-lexicon/positive-words.txt', what='character', comment.char=';')

huliu.nwords <- scan('opinion-lexicon/negative-words.txt', what='character', comment.char=';')

# Add some words

huliu.nwords <- c(huliu.nwords,'wtf','wait','waiting','epicfail', 'crash', 'bug', 'bugy', 'bugs', 'slow', 'lie')

#Remove some words

huliu.nwords <- huliu.nwords[!huliu.nwords=='sap']

huliu.nwords <- huliu.nwords[!huliu.nwords=='cloud']

#which('sap' %in% huliu.nwords)

twitterTag <- "@Netflix"

# Get 1500 tweets - an individual is only allowed to get 1500 tweets

 tweets <- searchTwitter(tag, n=1500)

  tweets.text <- laply(tweets,function(t)t$getText())

  sentimentScoreDF <- getSentimentScore(tweets.text)

  sentimentScoreDF$TwitterTag <- twitterTag

# Get rid of tweets that have zero score and seperate +ve from -ve tweets

sentimentScoreDF$posTweets <- as.numeric(sentimentScoreDF$SentimentScore >=1)

sentimentScoreDF$negTweets <- as.numeric(sentimentScoreDF$SentimentScore <=-1)

#Summarize finidings

summaryDF <- ddply(sentimentScoreDF,"TwitterTag", summarise, 

                 TotalTweetsFetched=length(SentimentScore),

                 PositiveTweets=sum(posTweets), NegativeTweets=sum(negTweets), 

                 AverageScore=round(mean(SentimentScore),3))

summaryDF$TotalTweets <- summaryDF$PositiveTweets + summaryDF$NegativeTweets

#Get Sentiment Score

summaryDF$Sentiment  <- round(summaryDF$PositiveTweets/summaryDF$TotalTweets, 2)

Saving the best for the last, here is a word cloud (also called tag cloud) for Netflix built in R-

I will be putting the R code up here for building a word cloud after scrubbing it.

Happy Analyzing!

Geocode your data using, R, JSON and Google Maps' Geocoding API

First and foremost, I absolutely love the topic of Location Analytics (Geo-Spatial Analysis) and see tremendous business potential in not so distant future.  I would go out on a limb to predict that the Location Analytics will soon go viral in the enterprise space because it has the capability to WOW us. Look no further than your iPhone or an Android phone and count how many location aware apps you have. We all have at lease one app - Google Maps.  Mobile is one of the strongest catalyst for enterprise adoption of Location aware apps. All right, enough of business talk, let's get dirty with the code.


Over the last year and half, I have faced numerous challenges with geocoding the data that I have used to showcase my passion for location analytics.  In 2012, I decided to take thing in my control and turned to R.  Here, I am sharing a simple R script that I wrote to geo-code my data whenever I needed it, even BIG Data.


To geocode my data, I use Google's Geocoding service which returns the geocoded data in a JSON. I will recommend that you register with Google Maps API and get a key if you have large amount of data and would do repeated geo coding.

Here is function that can be called repeatedly by other functions:

getGeoCode <- function(gcStr)

{

  library("RJSONIO") #Load Library

  gcStr <- gsub(' ','%20',gcStr) #Encode URL Parameters

 #Open Connection

 connectStr <- paste('http://maps.google.com/maps/api/geocode/json?sensor=false&address=',gcStr, sep="") 

  con <- url(connectStr)

  data.json <- fromJSON(paste(readLines(con), collapse=""))

  close(con)

#Flatten the received JSON

  data.json <- unlist(data.json)

  lat <- data.json["results.geometry.location.lat"]

  lng <- data.json["results.geometry.location.lng"]

  gcodes <- c(lat, lng)

  names(gcodes) <- c("Lat", "Lng")

  return (gcodes)

}

Let's put this function to test:

geoCodes <- getGeoCode("Palo Alto,California")

> geoCodes
           Lat            Lng 
  "37.4418834" "-122.1430195" 

You can run this on the entire column of a data frame or a data table:

Here  is my sample data frame with three columns - Opposition, Ground.Country and Toss. Two of the columns, you guessed it right, need geocoding.

> head(shortDS,10)

     Opposition              Ground.Country Toss

1      Pakistan            Karachi,Pakistan  won

2      Pakistan         Faisalabad,Pakistan lost

3      Pakistan             Lahore,Pakistan  won

4      Pakistan            Sialkot,Pakistan lost

5   New Zealand    Christchurch,New Zealand lost

6   New Zealand          Napier,New Zealand  won

7   New Zealand        Auckland,New Zealand  won

8       England              Lord's,England  won

9       England          Manchester,England lost

10      England            The Oval,England  won

To geo code this, here is a simple one liner I execute:

shortDS <- with(shortDS, data.frame(Opposition, Ground.Country, Toss,

                  laply(Ground.Country, function(val){getGeoCode(val)})))

> head(shortDS, 10)
    Opposition           Ground.Country Toss  Ground.Lat  Ground.Lng
1     Pakistan         Karachi,Pakistan  won   24.893379   67.028061
2     Pakistan      Faisalabad,Pakistan lost   31.408951   73.083458
3     Pakistan          Lahore,Pakistan  won    31.54505   74.340683
4     Pakistan         Sialkot,Pakistan lost  32.4972222  74.5361111
5  New Zealand Christchurch,New Zealand lost -43.5320544 172.6362254
6  New Zealand       Napier,New Zealand  won -39.4928444 176.9120178
7  New Zealand     Auckland,New Zealand  won -36.8484597 174.7633315
8      England           Lord's,England  won     51.5294     -0.1727
9      England       Manchester,England lost   53.479251   -2.247926
10     England         The Oval,England  won   51.369037   -2.378269

Happy Demoing and Coding!

Enterprise Software Spending to Slow Down - Business Analytics to the Rescue?

Few months ago, I floated this hypothesis that the software spending generally has a lag of 1-2 quarters to hardware spending and given that hardware spending is slowing down now with Cisco, Juniper, Brocade, EMC, NetApp, (and chip companies prior to that) all coming out with revenue and EPS warnings, software spending could slow as well further down the road.

Now, if ORCL’s  warnings from last night and following quote from an analyst were to be taken seriously, this hypothesis is unfortunately is coming true.  

                   Jason Maynard, an analyst at Wells Fargo Securities, said in a Dec. 19 report that corporate spending on hardware and software may fall 8 percent in the first quarter, a steeper drop than the average 7.3 percent average decline during the quarter in the past 10 years. (Source: Business Week )

The Enterprise Software Industry has enjoyed 12-13 quarters of continuous growth and it is a well-known fact that the spending is cyclical in nature.  May be, the industry should prepare for couple of quarters of slow growth (or no growth.) 

I am off the opinion that a full blown contraction in software spending will not occur. There is a pent up demand and those demand dollars are shifting to the cloud for SaaS, PaaS, IaaS and all other types of aaS as these XaaS become a preferred choice. That is precisely what may have caused the bloody hiccups (the reaction on Oracle's stock in financial markets) at Oracle.

This may be just an aberration for the tech industry and it may require new economy companies to prove that is just an aberration and not a trend . (Please see this blog - Oracle earnings - an aberration or a trend? )

Coming to the Analytics topic - in good times or bad times, more so in bad times, business analytics has become a tool of necessity, a must-have weapon to understand what levers to pull to run the business more effectively, more efficiently and identify the right resources to be delivered to grow and optimize the business in tough times.  


Data is a strategic asset and Business Analytics provides tactical tools to exploit that asset, companies will mine data even deeper with more sophisticated tools to get even more deeper insights if the signs of slow down loom on the horizon.

It is yet to be seen that the business spending on analytics will slow as well.  I will take a different stance here and will form another hypothesis that the spending will likely increase over the next couple of quarters.

Mobile Analytics - A Game Changer!

Mobile Analytics (a.ka. Mobile BI) has been the hottest strategic topic and a top focus for many enterprise software organizations as customers, small and large, grapple with the big data onslaught and throw everything at it to become even more efficient, both on top-line growth and bottom-line optimization, in an economy struggling to grow and a continent unable to stop a contagion from spreading and once again threatening the global economy.  

Customer's perennial struggle and in-turn a cost-saving approach translates into big analytics opportunity for enterprise software companies to shift customers from traditional analytics solutions to Mobile and Cloud based analytics solutions.

On the premise explained above, I did a business case about 9 months ago to develop a FULL picture of Mobile Analytics market.  I used a ton of research and analyst reports and interviews and invested upwards of hundreds of hours to develop and present a complete story on Mobile Analytics including developing my own proprietary models related to assessing the size of this opportunity. 

I am summarizing my findings at a very high level in following bullet points and have made available the synthesis slides on slideshare (link is printed below).

• Big Data - According to IDC, data is doubling every two years and is expected to reach 1.8 ZB (a trillion GB) in 2011.
• Eight mobility related mega trends are locked in a virtuous cycle and will be the bedrock for growth and adoption of Mobile BI solutions and for  the overall Enterprise Mobility.
• Mobile BI market could grow at 20% plus CAGR over the next 5 years and could likely become over a $2 billion market by 2015.
• According to Gartner, more than 33% of Analytics will be consumed using mobile devices, a prediction well supported by the 8 mobility related mega trends discussed here.
• Therefore, by 2015 more than 15% of Analytics revenues could come from Mobile Analytics solutions. This should be a serious strategic priority for every Analytics vendor if not already.
• Advanced Analytics including geo-spatial for  Mobile Consumers is growing as computing power and form factor of mobile devices change rapidly. 
• Shift to “active production model” from a “passive consumption model”  is expected to happen allowing mobile business users to assemble dashboards and produce/edit reports on the go.

Download slides from Slideshrae - Mobile Analytics (Mobile BI) - A Game Changer

Special thanks goes to Gartner, IDC, Boris Evelson of Forrester, Cindy Howson of BI Scorecard, and Howard Dresner of Dresner Advisory Services for producing excellent research on this topic and answering all my questions and to all my colleagues and friends across the world. 

Upcoming blog on Agile Analytics

Closing the loop on Pervasive Location Analytics - an enlightening personal journey for sure!

When I started working on Google Maps deal at SAP in February of this year, I had no clue where it will end and what is next once the deal is done. I fell in love with this Location Analytics/Geo Data Visualization topic, and turned it into an opportunity to discuss this topic and also generate excitement in various different camps along the way.

Five sessions spread across three continents, 200+ attendees,1000 views and numerous downloads later, this topic became more than just a personal interest. I met great people along the way and worked with very smart and driven people to co-present from the likes of Ryan from Centigon Solutions, Nimish from FreshDirect and Brendan from ThinkSmart Technologies. (See links to slides and session evaluation below)

A proud moment arrived this morning when an alert from SlideShare popped up indicating that this topic is hot on Facebook and as a result this topic is being put on SlideShare home page. Wow!


Pervasive Location Analytics: The Next Frontier to Fall in The Enterprise Software?

Session Evaluations Results

Thank you - my next two blogs will be presenting my thoughts on Moblie Analytics and Agile BI - two topics I have spent significant amount of time from strategy, market, customer, competition and product point of view.

Sentiment Analysis, the R way, on Netflix's September 18th Announcement

Did Netflix make a bad move or a bold move, only time will tell but for now here is a simple sentiment analysis using R and TwitteR package on tweets involving Netflix for you to consume...

So aftermath of #netflix supposedly bad strategic move, I thought that it will be little fun to do a little sentiment analysis using a sample of tweets from the past few days. I turned to my favorite "R" and discovered a new package called "TwitteR" and 4 lines of code later, I had the following outcome:

788 of the 1500 tweets, that is 52.5% of the tweets, over the last three days had words bad, suck, terrible or :( with #netflix...

You be the judge whether Netflix customers are unhappy and whether it was a bad (or bold) strategic move...

>  library("twitteR")

> searchNF <- searchTwitter("#netflix bad OR suck OR terrible OR disaster OR :(", n=1500, since=as.character(Sys.Date()-3))

> negativeTweets <- length(searchNF)

> negativeSentiment <- negativeTweets/1500

And yes, I enjoy coding :)

Best quotes from Forbes Article SAP-Google Maps Partnership

SAP Partnership with Google Maps Indicates a New Openness

"SAP is overcoming a legacy of an insular engineering culture that could accurately be accused of suffering from a “not invented here” complex in the past."


"The only problem with SAP’s pride in its history is that it has sometimes shut the company’s eyes to new ways of creating software. It appears that this announcement may mark a turning point to increased awareness and use of outside components. If SAP becomes truly open to using more and more outside components, and learns how to use them to create stable, reliable software, SAP could accelerate the pace of change, keeping the stable parts of its applications, but adding the best of what has newly arrived."


There is something more at stake for Google than money - it is likely that Google Maps will be adapted by Google to better meet the needs of enterprise applications.


"What’s next? What other cloud components will SAP start to incorporate? The second is: Is a bigger partnership possible? Google’s mission is “to organize the world’s information and make it universally accessible and useful.” Much of the information that runs the world is in SAP. Why aren’t Google and SAP working together to make it more universally accessible and useful?"

Pervasive Location Analytics − The Next Frontier to Fall In the Enterprise Software?

Geo-location and spatial intelligence is the strategic turning point for business analytics and BI. Location has become an essential part of the enterprise data and increasing number of enterprises have geo-coded their location data to build location-aware application to drive location-aware decisions. For example, by overlaying the foreclosure data, income data, and the data from its mortgage portfolio on a geo-chart, a regional mortgage bank assesses the risk of its mortgage portfolio and decides to take corrective actions. A fast food company uses the demographics data, the latest census data, and the historical sales of its stores to determine the location of its new restaurant. 

Slides from SAP TechEd 2011 Las Vegas - http://goo.gl/etkvI

Google Maps - SAP - The press is humming...

Thanks to my friends in marketing...

SAP Now Allows Businesses To Layer Big Data With Google Maps And Earth

Leena Rao, TechCrunch

July 27, 2011

http://techcrunch.com/2011/07/27/sap-now-allows-businesses-to-layer-big-data-with-google-maps-and-earth/

Also seen in: The Washington Post, The Wall Street Journal, NewsFactor, The Business Insider, 21^st Century Networker, Maine Social Networking, Data Centers Canada

(385 tweets)

SAP Tying Analytics to Google Maps, Earth

Chris Kanaracus, IDG News

July 27, 2011

http://news.idg.no/cw/art.cfm?id=2F653071-1A64-67EA-E4C824717009C50D

Also seen in: PCWorld, CIO, Network World, Wall Street Journal, Computerworld, PC Advisor, InfoWorld, Albuquerque Express, CFO World, ARNnet, ITworld, Good Gear Guide, Techworld, Computerworld Australia, Computerworld UK, ITBusiness.ca

(114 tweets)

Google Deal Lets SAP Customers Map Data

Doug Henschen, InformationWeek

July 27, 2011

http://www.informationweek.com/news/software/bi/231002767   

(28 tweets)

 

Google and SAP Team-Up to Help You Visualize Big Data

Klint Finley, ReadWriteWeb

July 27, 2011

http://www.readwriteweb.com/enterprise/2011/07/google-and-sap-team-up-to-help.php

(128 tweets)

SAP, Google expand collaboration partnership, eye enterprise mashups

Larry Dignan, ZDNet

July 27, 2011

http://www.zdnet.com/blog/btl/sap-google-expand-collaboration-partnership-eye-enterprise-mashups/53275

(39 tweets)

SAP and Google Maps Team Up to Visualize Corporate Data

Todd R. Weiss, CIO blog: Deciphering Enterprise Apps

July 27, 2011

http://blogs.cio.com/business-intelligence/16424/sap-and-google-maps-team-visualize-corporate-data

(3 tweets)

 

SAP Geo-tagging Business Analytics Data with Google Maps

Clint Boulton, eWEEK

July 27, 2011

http://www.eweek.com/c/a/Enterprise-Applications/SAP-Geotagging-Business-Analytics-Data-with-Google-Maps-274375/

Also seen in: eWEEK Europe

(19 tweets)

SAP Invokes Google Maps to Put Data in Context

Mike Vizard, IT Business Edge

July 27, 2011

http://www.itbusinessedge.com/cm/blogs/vizard/sap-invokes-google-maps-to-put-data-in-context/?cs=48023

(2 tweets)

 

Google Plus SAP Deepen Ties, Deliver More Enterprise Integration

Courtney Bjorlin, ASUG News

July 27, 2011

http://www.asugnews.com/2011/07/27/google-plus-sap-deepen-ties-deliver-more-enterprise-integration/

(14 tweets)

Photos: Google Maps gives SAP's business intelligence a new direction

Tim Ferguson, Silicon.com

July 27, 2011

http://www.silicon.com/technology/software/2011/07/27/photos-google-maps-gives-saps-business-intelligence-a-new-direction-39747745/

(6 tweets)

SAP and Google Put Business Analytics on the Map

Justin Kern, Information Management

July 27, 2011

http://www.information-management.com/news/business_intelligence_analytics_data_geospatial-10020840-1.html

Also seen in: Insurance Networking News

(10 tweets)

SAP and Google Partner for Geospatial Business Intelligence

Paul Shread, EnterpriseAppsToday

July 27, 2011

http://www.enterpriseappstoday.com/business-intelligence/sap-google-geospatial-business-intelligence.html

(7 tweets)

SAP, Google and geospatial analytics

Todd Morrison, SearchSAP

July 27, 2011

http://itknowledgeexchange.techtarget.com/sap-watch/sap-google-and-geospatial-analytics/

(3 tweets)

 

SAP and Google team up to mash up analytics and maps

Matt Hartley, Financial Post

July 27, 2011

http://business.financialpost.com/2011/07/27/sap-and-google-team-up-to-mash-up-analytics-and-maps/

(4 tweets)

 

The “Where” Dimension of Business Intelligence

Adrian Gonzalez, Logistics Viewpoints

July 27, 2011

http://logisticsviewpoints.com/2011/07/27/the-where-dimension-of-business-intelligence/

(15 tweets)

SAP, Google team up to tie-in business analytics to Google Map

Brad Lemaire, Proactive Investors USA & Canada

July 27, 2011

http://www.proactiveinvestors.com/companies/news/16704/sap-google-team-up-to-tie-in-business-analytics-to-google-maps-16704.html

(4 tweets)

Google and SAP Partner on Geo-Mapping

Chris Crum, WebProNews

July 27, 2011

http://www.webpronews.com/google-and-sap-partner-on-geo-mapping-2011-07

(23 tweets)

Google and SAP Team Up for Geovisualization of Business Analytics

Matt Ball, Spatial Sustain

July 27, 2011

http://www.vector1media.com/spatialsustain/google-and-sap-team-up-for-business-analytics.html

(5 tweets)

SAP Partnership With Google Allows Data Mapping on Google Maps

TechGadgetsWeb.com

July 27, 2011

http://www.techgadgetsweb.com/3412/sap-partnership-google-data-mapping-google-maps

(5 tweets)

Street Fight Daily: 07.27.11

David Hirschman, Street Fight Daily: Inside the Business of Hyperlocal

July 27, 2011

http://streetfightmag.com/2011/07/27/street-fight-daily-07-27-11/

(0 tweets)

Media and Blogger Coverage – Headlines & Links Select Global Coverage

EMEA

Germany

Geo-Dienste: SAP verbündet sich mit Google

Sibylle Gassner, Silicon.de

July 27, 2011

http://www.silicon.de/technologie/software/0,39044013,41554999,00/geo_dienste_sap_verbuendet_sich_mit_google.htm

(4 tweets)

SAP und Google wollen gemeinsam Geodaten sammeln

Jens Hartmann, Silicon.de

July 27, 2011

http://www.welt.de/wirtschaft/webwelt/article13510999/SAP-und-Google-wollen-gemeinsam-Geodaten-sammeln.html

(10 tweets)

SAP und Google rücken zusammen

Corrina Visser, Der Tagesspiegel

July 27, 2011

http://www.tagesspiegel.de/wirtschaft/sap-und-google-ruecken-zusammen/4439242.html

(1 tweet)

Netherlands

SAP, Google team up to pair enterprise apps with LBS tools

Telecompaper

July 27, 2011                 

http://www.telecompaper.com/news/sap-google-team-up-to-pair-enterprise-apps-with-lbs-tools

(2 tweets)

Switzerland

Big Data: SAP married with Google Maps and Google Earth/ Big Data: SAP verheiratet sich mit Google Maps und Google Eart

Inside-it.ch

July 27, 2011

http://www.inside-it.ch/frontend/insideit?_d=_article&site=ii&news.id=25851

(0 tweets)

UK

SAP's Google partnership adds mapping data to business intelligence

Phil Muncaster, V3.co.uk

July 27, 2011

http://www.v3.co.uk/v3-uk/news/2097376/saps-google-partnership-mapping-business-intelligence

(0 tweets)

SAP and Google plan ‘big data’ Maps

Tom Brewster, ITPro

July 27, 2011

http://www.itpro.co.uk/635227/sap-and-google-plan-big-data-maps

(13 tweets)

SAP & Google Partner For Enhanced Location-Based Analytics

ITProPortal

July 27, 2011

http://www.itproportal.com/2011/07/27/sap-google-partner-enhanced-location-based-analytics/?utm_source=dlvr.it&utm_medium=twitter&utm_campaign=itproportal

(5 tweets)

SAP sees double-digit growth in software sales

Computing.co.uk

July 27, 2011

http://www.computing.co.uk/ctg/news/2097311/sap-double-digit-growth-software-sales

(1 tweets)

APJ 

India

SAP teams-up with Google to manage big data

CIOL India

July 27, 2011

http://www.ciol.com/Storage/Data-Storage/News-Reports/SAP-teams-up-with-Google-to-manage-big-data/152768/0/

(0 tweets)

SAP and Google Maps - Putting "Where" in the "What-When-Where" equation!

Organizations are looking for that x-factor to get competitive advantage. Could geo/location-enabled solutions offer the promise to deliver that x-factor?  I think so.  

Lets use couple of examples to understand this deal - where should Chipotle open its next franchise or where should BP drill its next well...  Geo-enabled solutions could help answer those questions. Yes, this is already happening and some of these companies have very sophisticated software to do this. But, these software solutions should be available for the masses - 

Here is my business explanation for this deal- 

•         A large part of the world’s enterprise data resides in the SAP systems;
•         And according to some estimates more than 80% of that enterprise data has a space dimension to it; 
•     Increasing amount of organizations demand geo-spatial lenses to engage with the space dimension of their data; 
•     Hence, this collaboration between the #1 enterprise software company and the #1 consumer Internet company to bring location-aware solutions to the market.

Go SAP-Google Maps!

The Era of Big Data is Upon us!

No kidding - if you didn't know this already, read this article from The Economist - Data, data everywhere.

Here are some mind boggling stats from that article:

• Wal-Mart handles more than 1m customer transactions every hour, feeding databases estimated at more than 2.5 petabytes—the equivalent of 167 times the books in America’s Library of Congress.
• Facebook is home to 40 billion photos.
• Decoding the human genome involves analysing 3 billion base pairs—which took ten years the first time it was done, in 2003, but can now be achieved in one week. (May be few hours now with SAP's HANA)

Another interesting insight The Economist:

Only 5% of the information that is created is “structured”, meaning it comes in a standard format of words or numbers that can be read by computers. The rest are things like photos and phone calls which are less easily retrievable and usable. But this is changing as content on the web is increasingly “tagged”, and facial-recognition and voice-recognition software can identify people and words in digital files.

So, what does this all mean? Opportunity for incumbent companies which offer software tools to analyze world's structured and unstructured data. Companies like SAP, IBM, Oracle, Informatica of the world find themselves in the eye of the storm. This is the decade of big data and enterprise mobility that means big opportunity for lot of software and hardware companies.

I will be publishing blogs on the topic of Enterprise Mobility and Mobile Business Analytics going forward and will be looking forward to collaborating with other visionaries out there to spread the word on Mobile Business Analytics.

So Long!