Eye Tracking & Applied ML: Soapbox Validations

Anyone who has read my blog (shameless self-plug: http://www.lauraedell.com) over the past 12 years will know, I am very passionate about drinking my own analytical cool-aid. Whether during my stints as a Programmer, BI Developer, BI Manager, Practice Lead / Consultant or Senior Data Scientist, I believe wholeheartedly in measuring my own success with advanced analytics.  Even my fantasy football success (more on that in a later post) can be attributed to Advanced Machine Learning…But you wouldn’t believe how often this type of measurement gets ignored.

Introducing you, dear reader, to my friend “Eye-Tracker” (ET). Daunting little set of machines in that image, right?! But ET is a bonafide bada$$ in the world of measurement systems; oh yeah, and ET isn’t a new tech trend – in fact, mainstream  ET systems are a staple of any PR, marketing or web designers’ tool  arsenal  as a stick to measure program efficacy between user intended behavior & actual outcomes/actions.

In my early 20’s, I had my own ET experience & have been a passionate advocate since, having witnessed what happens when you compound user inexperience with poorly designed search / e-commerce operator sites.  I was lucky enough to work for the now uber online travel company who shall go nameless (okay, here is a hint: remember a little ditty that ended with some hillbilly singing “dot commmm” & you will know to whom I refer). This company believed so wholeheartedly in the user experience that they allowed me, young ingénue of the workplace, to spend thousands on eye tracking studies against a series of balanced scorecards that I was developing for the senior leadership team. This is important because you can ASK someone whether a designed visualization is WHAT THEY WERE THINKING or WANTING, even if built iteratively with the requestor. Why, you ponder to yourself, would this be necessary when I can just ask/survey my customers about their online experiences with my company and saved beaucorp $$.

Well, here’s why: 9x out of 10, survey participants, in not wanting to offend, will nod ‘yes’  instead of being honest, employing conflict avoidance at its best. Note, this applies to most, but I can think of a few in my new role who are probably reading this and shaking their head in disagreement at this very moment.

Eye tracking studies are used to measure efficacy by tracking what content areas engage users’ brains vs. areas that fall flat, are lackluster, overdesigned &/or contribute to eye/brain fatigue. It measures this by “tracking” where & for how long your eyes dwell on a quadrant (aka visual / website content / widget on a dashboard) and by recording the path & movement of the eyes between different quadrants’ on a page. It’s amazing to watch these advanced, algorithmic-tuned systems, pick up even the smallest flick of one’s eyes, whether darting to or away from the “above-fold” content, in ‘near’ real-time. The intended audience being measured generates the validation statistics necessary to evaluate how well your model fit the data. In the real-world, receiving attaboys or “ya done a good job” high fives should be doled out only after validating efficacy: eg. if customers dwell time increases, you can determine randomness vs. intended actual; otherwise, go back to the proverbial drawing board until earn that ‘Atta boy’ outright.

What I also learned which seems a no-brainer now; people read from Left Top to Right Bottom (LURB). So, when I see anything that doesn’t at LEAST follow those two simple principles, I just shake my head and tisk tisk tisk, wondering if human evolution is shifting with our digital transformation journey or are we destined to be bucketed with the “that’s interesting to view once” crowd instead of raising to the levels of usefulness it was designed for.

Come on now, how hard is it to remember to stick the most important info in that top left quadrant and the least important in the bottom right, especially when creating visualizations for use in the corporate workplace by senior execs. They have even less time & attention these days to focus on even the most relevant KPIs, those they need to monitor to run their business & will get asked to update the CEO on each QTR, with all those fun distractions that come with the latest vernacular du-jour taking up all their brain space: “give me MACHINE LEARNING or give me death; the upstart that replaced mobile/cloud/big data/business intelligence (you fill in the blank).
But for so long, it was me against the hard reality that no one knew what I was blabbing on about, nor would they give me carte blanche to re-run those studies ever again , And lo and behold, my Laura-ism soapbox has now been vetted, in fact, quantified by a prestigious University professor from Carnegie, all possible because a little know hero named Edmond Huey, now near and dear to my heart, grandfather of the heatmap, followed up his color-friendly block chart by building the first device capable of tracking eye movements while people were reading. This breakthrough initiated a revolution for scientists but it was intrusive and readers had to wear special lenses with a tiny opening and a pointer attached to it like the 1st image pictured above.
Fast forward 100 years…combine all ingredients into the cauldron of innovation & technological advancement, sprinkled with my favorite algorithmic pals: CNN & LSTM & voila! You have just baked yourself a popular visualization known as a heat/tree map (with identifiable info redacted) :
This common visual is  akin to eye tracking analytics which you will see exemplified in the last example below. Cool history lesson, right?

Even cooler is this example from a travel website ‘Travel Tripper’ which published Google eye-tracking results specific to the hotel industry. Instead of a treemap that you might be used to (akin to a Tableau or other BI tool visualization OOTB), you get the same coordinates laid out over search results in this example; imagine having your website underneath and instead of guessing what content should be above or below the fold, in the top left or right of the page, you can use these tried and true eye tracking methods to quantify exactly what content items customers or users are attracted to 1st and where their eyes “dwell” the longest on the page (red hot).

So, for those non-believers, I say, become a web analytic trendsetter, driving the future of machine design forward (ala “Web Analytics 3.0”).

Be a future-thinker, forward mover, innovator of your data science sphere of influence, always curious yet informed to make intelligent choices.

Finance is the Participation Sport of the BI Olympics

IT is no longer the powerhouse that it once was, and unfortunately for CIOs who haven’t embraced change, much of their realm was commoditized by cloud computing powered by the core principles of grid computational engines and schema-less database designs. The whole concept of spending millions of dollars to bring all disparate systems together into one data warehouse has proven modesty beneficial but if we are being truly honest, what has all that money and time actually yielded, especially towards the bottom line?
And by the time you finished with the EDW, I guarantee it was missing core operational data streams that were then designed into their own sea of data marts. Fast forward a few years, and you probably have some level of EDW, many more data marts , probably one or more cube (ROLAP/MOLAP) applications and n-number of cubes or a massive 1+ hyper-cube(s) and still, the business depends of spreadsheets to sit on top of these systems, creating individual silos of information under the desk or in the mind of one individual.

Wait<<<rewind<<< Isn’t that where we started?

Having disparate, ungoverned and untrusted data sources being managed by individuals instead of by enterprise systems of record?

And now we’re back>>>press play to continue>>>

When you stop to think about the last ten years, fellow BI practitioners, you might be scared of your ever-changing role. From a grass-roots effort to a formalized department team, Business Intelligence went from the shadows to the mainstream, and brought with it reports then dashboards, then KPIs and scorecards, managing by exception, proactive notifications and so on. And bam! We were hit by the first smattering of changes to come when Hadoop and others hit the presses. But we really didnt grok what the true potential and actual meaning of said systems unless you come from a background like myself, either competitively, or from a big data friendly industry group like telecommunications, or from a consultant/implementation p.o.v.
And then social networking took off like gang busters and mobile became a reality with the introduction of the tablet device (though, I hate to float my boat as always by mentioning my soap box dream spewed at a TDWI conference about the future of mobile BI when the 1st generation iPhone released).

But that is neither here nor there. And, as always, I digress and am back…

At the same time as we myopically focused on the technological changing landscape around us, a shifting power paradigm was building wherein the Finance organization, once relegated to the back partition of cubicles, where a pin drop was heard ’round the world (or at least, the floor), was growing more and more despondent with not being able to access the data they needed without IT intervention in order to update their monthly forecasts and produce their subsequent P&L, Balance Sheet and Cash Flow Planning statements. And IT’s response was to acquire (for additional millions of dollars) a “BI tool” aka an ad-hoc reporting application that would allow them to pull their own data. But it had been installed and the data had been pulled, and validated and by the time of completion, the Finance team had either found an alternate solution or found the system useful for a very small sliver of analysis but went outside of IT to get additional sources of information that wanted and needed to adapt to the changing business pressures from the convergence of social, mobile and unstructured datasets. And suddenly those once, shiny BI tools, seemed like antiquated relics, and simply could not handle the sheer data volumes that were now expected from it or would crash (unless filtered beyond the point of value). Businesses need not adapt their queries to the tool but need a tool that can adapt to their ever-changing processes and needed.

Drowning in data but starving for information…

So if necessity if the mother of invention, Finance was its well deserving child. And why? The business across the board is starving for information but drowning in data. And Finance is no longer a game of solitaire, understood by few and ignored by many. In fact, Finance has become the participation sport of the BI Olympics, and rightfully so, where departmental collaboration at the fringe of the organization has proven as the missing link that before prevented successful top-down planning efforts. Where visualizations demands made dashboards a thing of the past, and demanded and better story, vis-a-vie storylines / infographics, to help disseminate more than just the numbers, but the story behind the numbers to the rest of the organization, or what I like to call the “fringe”.

I remember a few years ago when the biggest challenge was getting data, and often, we joked about how nice it would be to have a sea of data to drown in; an analysts’ buffet-du-jour; a happy paralysis-induced-by said analysis plate was the special of the day, yet only for a few, while the rest was but a gleam in our data-starved eyes.

Looking forward from there, I ask, dear reader, where do we go from here…If it’s a Finance party and we are all invited, what do we bring to the party table as BI practitioners of value? Can we provide the next critical differentiator?

Well, I believe that we can, and that critical differentiator is forward-looking data. Why?

Gartner Group stated that “Predictive data will increase profitability by 20% and that historical data will become a thing of the past” (for a BI practitioner, the last part of that statement should worry you, if you are still resisting the plunge into the predictive analytics pool).

Remember, predictive is a process that allows an organization to get true insight and has been executed amongst a larger group of people to drive faster, smarter business users. This is perfect for enterprise needs because by definition, they offer a larger group of people to work with.

In fact, it was Jack Welch would said  “An organization’s ability to learn, and translate that learning into action rapidly, is the ultimate competitive advantage” 

If you haven’t already, go out and started learning one of the statistical application packages. I suggest “R” and in the coming weeks, I will provide R and SAS scripts (I have experience with both) for those interested in growing their chosen profession and remaining relevant as we weather the sea of business changes

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Futures According to Laura… Convergence of Cloud and Neural Networking with Mobility and Big Data

It’s been longer and longer between my posts and as always, life can be inferred as the reason for my delay.

But I was also struggling with feeling a sense of “what now” as it relates to Business Intelligence.

Many years ago, when I first started blogging, I would write about where I thought BI needed to move in order to remain relevant in the future. And those futures have come to fruition lately. Gamuts ranging from merging social networking datasets into traditional BI frameworks to a more common use case of applying composite visualizations to data (microcharts, as an example). Perhaps more esoteric was my staunch stance on the Mobile BI marriage which when iPhone 1 was released was a future many disputed with me. In fact, most did not own the first release of the iPhone, and many were still RIM subscribers. And it was hard for the Blackberry crowd to fathom a world unbounded by keyboards and scroll wheels and how that would be a game changer for mobile BI. And of course, once the iPad was introduced, it was a game over moment. Execs everywhere wanted their iPads to have the latest and greatest dashboards/KPIs/apps. From Angry Birds to their Daily Sales trend, CEOs and the like had new brain candy to distract them during those drawn out meetings. And instead of wanting that PDF or PowerPoint update, they wanted to receive the same data on their iPad. Once they did, they realized that having the “WHAT” is happening understanding was only the crack to get them hooked for a while. Unfortunately, the efficacy of KPI colors and related numbers only satisfies the one person show – but as we know, it isn’t the CEO who analyzes why a RED KPI indicator shows up. Thus, more levels of information (beyond the “WHAT” and  “HOW OFTEN”)  were needed to answer the “WHY” and “HOW TO FIX” the underlying / root cause issue.

The mobile app was born.

It is the reborn mobile dashboard that has been transformed into a new mobile workflow, more akin to the mobile app. 

But it took time for people to understand the marriage between BI dashboards, the mobile wave, especially the game change that Apple introduced with it’s swipe and pinch to zoom gestures, the revolution of the App Stores for the “need to have access to it now” generation of Execs, the capability to write-back from mobile devices to any number of source systems and how functionally, each of these seemingly unrelated functions would and could be weaved together to create the next generation of Mobile Apps for Business Intelligence. 

But that’s not what I wanted to write about today. It was a dream of the past that has come to fruition. 

Coming into 2013, cloud went from being something that very few understood to another game changer in terms of how CIOs are thinking about application support of the future. And that future is now.

But there are still limitations that we are bound by. Either we have a mobile device or not, either it is on 3 or 4G or wifi. Add to that our laptops (yes, something I believe will not dominate the business world in a future someday). And compound that with other devices like smartphones, eReaders, desktop computers et al. 

So, I started thinking about some of the latest research regarding Neural Networks (another set of posts I have made about the future of communication via Neural networks) published recently by Cornell University here (link points to http://arxiv.org/abs/1301.3605).

And my nature “plinko” thought process (before you ask, search for the Price is Right game and you will understand “Plinko Thoughts”) bounced from Neural Networks to Cloud Networks and from Cloud Networks to the idea of a Personal Cloud. 

A cloud of such personal nature that all of our unique devices are forever connected in our own personal sphere and all times when on our person. We walk around and we each have our own personal clouds. Instead of a mass world wide web, we have our own personal wide area network and our own personal wide web.

When we interact with other people, those people can choose to share their Personal networks with us via Neural Networking or some other sentient process, or in the example, where we bump into a friend and we want to share details with them, all of our devices have the capability to interlink to each other via our Personal Clouds. 

Devices are always connected to your Personal Cloud which is authenticated to your person, so that passwords which are already reaching their shelf life (see: article for more information on this point), are no longer the annoying constraint when we try to seamlessly use our mobile devices while on the go. Instead, they are authenticated to our Personal Cloud following similar principles as where IAM (Identity and Access Management) is moving towards in future. And changes in IAM are not only necessary for this idea to come to fruition but are on the horizon.

In fact, Gartner published an article in July 2012, called “Hype Cycle for Identity and Access Management Technologies, 2012” in which Gartner recognized that the growing adoption of mobile devices, cloud computing, social media and big data were converging to help drive significant changes in the identity and access management market.

For background purposes, IAM processes and technologies work across multiple systems to manage:

■ Multiple digital identities representing individual users, each comprising an identifier (name or key) and a set of data that represent attributes, preferences and traits

■ The relationship of those digital identities to each user’s civil identity

■ How digital user identities communicate or otherwise interact with those systems to handle
information or gain knowledge about the information contained in the systems

If you extrapolate that 3rd bullet out, and weave in what you might or might not know/understand about Neural Networking or brain-to-brain communication (see recent Duke findings by Dr. Miguel Nicolelis here) (BTW – the link points to http://www.nicolelislab.net/), one can start to fathom the world of our future. Add in cloud networking, big data, social data and mobility, and perhaps, the Personal Cloud concept I extol is not as far fetched as you initially thought when you read this post. Think about it.

My dream like with my other posts is to be able to refer back to this entry years from now with a sense of pride and “I told you so.” 

Come on – any blogger who makes predictions which come true years later deserves some bragging rites. 

Or at least, I think so…

MicroStrategy Personal Cloud – a Great **FREE** Cloud-based, Mobile Visualization Tool

Have you ever needed to create a prototype of a larger Business Intelligence project focused on data visualizations? Chances are, you have, fellow BI practitioners. Here’s the scenario for you day-dreamers out there:

Think of the hours spent creating wire-frames, no matter what tool you used, even if said tool was your hand and a napkin (ala ‘back of the napkin’ drawing) or the all-time-favorite white board, which later becomes a permanent drawing with huge bolded letters to the effect of ‘DO NOT ERASE OR ITS OFF WITH YOUR HEAD’ annotations dancing merrily around your work. Even better: electronic whiteboards which yield you hard copies of your hard work (so aptly named), which at first, seems like the panacea of all things cool (though it has been around for eons) but still, upon using, deemed the raddest piece of hardware your company has, until, of course, you look down at the thermal paper printout which has already faded in the millisecond since you tore it from machine to hand, which after said event, leaves the print out useless to the naked eye, unless you have super spidey sense optic nerves, but now I digress even further and in the time it took you to try to read thermal printout, it has degraded further because anything over 77 degrees is suboptimal (last I checked we checked in at around 98.6 but who’s counting), thus last stand on thermal paper electronic whiteboards is that they are most awesome when NOT thermoregulate ;).

OK, and now We are back…rewind to sentence 1 –

Prototyping is to dashboard design or any data visualization design as pencils and grid paper are to me. Mano y mano – I mean, totally symbiotic, right?

But, wireframing is torturous when you are in a consultative or pre-sales role, because you can’t present napkin designs to a client, or pictures of a whiteboard, unless you are showing them the process behind the design. (And by the way, this is an effective “presentation builder” when you are going for a dramatic effect –> ala “first there were cavemen, then the chisel and stone where all one had to create metrics –> then the whiteboard –> then the…wait!

This is where said BI practitioner needs to have something MORE for that dramatic pop, whiz-AM to give to their prospective clients/customers in their leave behind presentation.

And finally, the girl gets to her point (you are always so patient, my loving blog readers)…While I biased, if you forget whom I work for, and just take into account the tool, you will see the awesomeness that the new MicroStrategy Personal Cloud is for (drum roll please) PROTOTYPING a new dashboard — or just building, distributing, mobilizing etc your spreadsheet of data in a highly stylized, graphical means that tell a story far better than a spreadsheet can in most situations. (Yes, neighseyers, I know that for the 5% of circumstances which you can name, a spreadsheet is more àpropos, but HA HA, I say: this cloud personal product has the ability to include the data table along with the data visualizations!)

Best of all it is free.

I demoed this recently and was able to time it took to upload and spreadsheet, render 3 different data visualizations, generate the link to send to mobile devices (iPads and iPhones), network latency for said demo-ees to receive the email with the link and for them to launch the dashboard I created, and guess what the total time was?

Next best of all, it took only 23.7 minutes from concept to mobilization!

Mind you, I was also using data from the prospect that I had never seen or had any experience with.

OK, here is how it was done:

1) Create a FREE account or login to your existing MicroStrategy account (by existing, I mean, if you have ever signed up for the MicroStrategy forums or discussion boards, or you are an employee, then use the same login) at https://www.microstrategy.com/cloud/personal

Landing Page After Logged in to Personal Cloud

2) Click the button to Create New Dashboard:

Create Dashboard Icon

• Now, you either need to have a spreadsheet of data OR you can choose one of the sample spreadsheets that MicroStrategy provides (which is helpful if you want to see how others set up their data in Excel, or how others have used Cloud personal to create dashboards; even though it is sample data , it is actually REAL data that has been scrub-a-dub-dubbed for your pleasure!) If using a sample data set, I recommend the FAA data. It is real air traffic data, with carrier, airport code, days of the week, etc, which you can use to plan your travel by; I do…See screenshot below. There are some airports and some carriers who fly into said airports whom I WILL not fly given set days of the week in which I must travel. If there is a choice, I will choose to fly alternate carriers/routes. This FAA data set will enable you to analyze this information to make the most informed decision (outside of price) when planning your travel. Trust me…VERY HELPFUL! Plus, you can look at all the poor slobs without names sitting at the Alaska Air gate who DIDNT use this information to plan their travel, and as you casually saunter to your own gate on that Tuesday between 3 – 6 PM at SeaTac airport , you will remember that they look so sad because their Alaska Air flight has a 88% likelihood of being delayed or cancelled. (BTW, before you jump on me for my not so nice reference to said passengers), it is merely a quotation from my favorite movie ‘Breakfast at Tiffany’s’ …says Holly Golightly: “Poor cat…poor old slob without a name”.

On time Performance (Live FAA Data)

If using your own data, select the spreadsheet you want to upload

3) Preview your data; IMPORTANT STEP: make sure that you change any fields which to their correct type (either Attribute or Metric or Do Not Import).

Cloud Import - Preview Data

Keep in mind the 80/20 rule: 80% of the time, MicroStrategy will designate your data as either an Attribute or Metric correctly using a simple rule of thumb: Text or VarChar/NVarChar if using SQL Server, will always be designated as an Attribute (i.e. your descriptor/Dimension) and your numerals designated as your Metrics. BUT, if your spreadsheet uses ID fields, like Store ID, or Case ID, along with the descriptor like Store DESC or Case DESC, most likely MicroStrategy will assume the Store ID/Case ID are Metrics (since the fields are numeric in the source). This is an Easy Change! You just need to make sure ahead of time to make that change using the drop down indicator arrows in the column headings – To find them, hover over the column names with your mouse icon until you see the drop down indicator arrow. Click on the arrow to change an Attribute column to a Metric column and vice-versa (see screenshot):

Change Attribute to Metric

Once you finish with previewing your data, and everything looks good, click OK at the bottom Right of your screen.

In about 30-35 seconds, MicroStrategy will have imported your data into the Cloud for you to start building your awesome dashboards.

4) Choose a visualization from the menu that pops up on your screen upon successfully importing your spreadsheet:

Change data visualization as little or as often as you choose

Here is the 2010 NFL data which I uploaded this morning. It is a heatmap showing the Home teams as well as any teams they played in the 2010 season. The size of the box is HOW big the win or loss was. The color indicates whether they won or lost (Green = Home team won // Red = Home team lost).

For all you, dear readers, I bid you a Happy New Year. May your ideas flow a plenty, and your data match your dreams (of what it should be) :). Go fearlessly into the new world order of business intelligence, and know that I , Laura E. your Dashboard Design Diva, called Social Intelligence the New Order, in 2005, again in 2006 and 2007. 🙂 Cheers, ya’ll.

http://tinyurl.com/ckfmya8

https://my.microstrategy.com/MicroStrategy/servlet/mstrWeb?pg=shareAgent&RRUid=1173963&documentID=4A6BD4C611E1322B538D00802F57673E&starget=1

Business Intelligence Clouds – The Skies the Limit

I am back…(for now, or so it seems these days) – I promise to get back to one post a month if not more.

Yes, I am known for my frequent use of puns, bordering on the line between cheesy and relevant. Forgive the title. It has been over 110 days since I last posted, which for me is a travesty. Despite my ever growing list of activities both professional and personally, I have always put my blog in the top priority quadrant.

Enough ranting…I diverged; and now I am back.

Ok, cloud computing (BI tools related) seems to be all the rage. Right up there with Mobile

BI, big data and social. I dare use my own term coined back in 2007 ‘Social Intelligence’ as now others have trade marked this phrase (but we, dear readers, know the truth –> we have been thinking about the marriage between social networks / social media data sets and business intelligence for years now)…Alas, I diverge again. Today, I have been thinking a lot about cloud computing and Business Intelligence.

Think about BI and portals, like Sharepoint (just to name 1)…It was all of the rage (or perhaps, still is)…”Integrate my BI reporting with my intranet / portal /Sharepoint web parts…OK, once that was completed successfully, did it buy much in terms of adoption or savings or any number of those ROI / savings catch – “Buy our product, and your employees will literally save so much time they will be basket weaving their reports into TRUE analysis'” What they didnt tell you, was that more bandwidth meant less need for those people, which in turn, meant people went into scarcity mode/tactics trying to make themselves seem or be relevant…And I dont fault them for this…Companies were not ready or did not want to think about what they were going to do with the newly freed up resources that they would have when the panacea of BI deployments actually came to fruition…And so, the wheel turned. What was next…? Reports became dashboards; dashboards became scorecards (became the complements for the former); Scorecards introduced proactive notification / alerting; alerting introduced threshold based notification across multiple devices/methods, one of which was mobile; mobile notification brought the need for mobile BI –> and frankly, and I will say it: Apple brought us the hardware to see the latter into fruition…Swipe, tap, double tap –> drill down was now fun. Mobile made portals seem like child’s play. But what about when you need to visualize something and ONLY have it on a spreadsheet?

(I love hearing this one; as if the multi-billion dollar company whose employee is claiming to only have the data on a spreadsheet didnt get it from somewhere else; I know, I know –> in the odd case, yes, this is true…so I will play along)…

The “only on a spreadsheet” crowd made mobile seem restrictive; enter RoamBI and the likes of others like MicroStrategy (yes, MicroStrategy now has a data import feature for spreadsheets with advanced visualizations for both web and mobile)…Enter Qlikview for the web crowd. The “I’m going to build-a dashboard in less than 30 minutes” salesforce “wait…that’s not all folks….come now (to the meeting room) with your spreadsheet, and watch our magicians create dashboards to take with you from the meeting”

But no one cared about maintenance, data integrity, cleanliness or accuracy…I know…they are meant to be nimble, and I see their value in some instances and some circumstances…Just like the multi-billion dollar company who only tracks data on spreqadsheets…I get it; there are some circumstances where they exist…But, it is not the norm.

So, here we are …mobile offerings here and there; build a dashboard on the fly; import spreadsheets during meetings; but, what happens when you go back to your desk and have to open up your portal (still) and now have a new dashboard that only you can see unless you forward it out manually?

Enter cloud computing for BI; but not at the macro scale; let’s talk , personal…Personal clouds; individual sandboxes of a predefined amount of space which IT has no sanction over other than to bless how much space is allocated…From there, what you do with it is up to you; Hackles going up I see…How about this…

Image via CrunchBase

Salesforce.com –> The biggest CRM cloud today. And for the last many years, SFDC has

enbraced Cloud Computing. And big data for that matter; and databases (database.com in fact) in the cloud…Lions and tigers and bears, oh my!

So isnt it natural for BI to follow CRM into cloud computing ?? Ok, ok…for those of you whose hackles are still up, some rules (you IT folks will want to read further):

Rules of the game:

1) Set an amount of space (not to be exceeded; no matter what) – But be fair and realistic; a 100 MB is useless; in today’s world, a 4 GB zip drive was advertised for $4.99 during the back to school sales, so I think you can pony up enough to help make the cloud useful.

2) If you delete it, there is a recycling bin (like on your PC/Mac); if you permanently delete it, too bad/so sad…We need to draw the line somewhere. Poor Sharepoint admins around the world are having to drop into STSADM commands to restore Alvin Analyst’s Most Important Analysis that he not only moved into recycling bin but then permanently deleted.

3) Put some things of use in this personal cloud at work like BI tools; upload a spreadsheet and build a dashboard in minutes wiht visualizations like the graph matrix (a crowd pleasure) or a time series slider (another crowd favorite; people just love time based data 🙂 But I digress (again)…

4) Set up BI reporting on the logged events; understand how many users are using your cloud environment; how many are getting errors; what and why are they getting errors; this simple type of event based logging is very informative. (We BI professionals tend to overthink things, especially those who are also physicists).

5) Take a look at what people are using the cloud for; if you create and add meaningful tools like BI visualizations and data import and offer viewing via mobile devices like iPhone/iPad and Android or web, people will use it…

This isnt a corporate iTunes or MobileMe Cloud; this isnt Amazon’s elastic cloud (EC2). This is a cloud wiht the sole purpase of supporting BI; wait, not just supporting, but propelling users out of the doldrums of the current state of affairs and into the future.

It’s tangible and just cool enough to tell your colleagues and work friends “hey, I’ve got a BI cloud; do you?”

To Start Quilting, One Just Needs a Set of Patterns: Deconstructing Neural Networks (my favorite topic de la journée, semaine ou année)

 

How a Neural Network Works:

A neural network (#neuralnetwork) uses rules it “learns” from patterns in data to construct a hidden layer of logic. The hidden layer then processes inputs, classifying them based on the experience of the model. In this example, the neural network has been trained to distinguish between valid and fraudulent credit card purchases.

This is not your mom’s apple pie or the good old days of case-based reasoning or fuzzy logic. (Although, the latter is still one of my favorite terms to say. Try it: fuzzzzyyyy logic. Rolls off the tongue, right?)…But I digress…

And, now, we’re back.

To give you a quick refresher:

Case based reasoning represents knowledge as a database of past cases and their solutions. The system uses a six-step process to generate solutions to new problems encountered by the user.

We’re talking old school, folks…Think to yourself, frustrating FAQ pages, where you type a question into a search box, only to have follow on questions prompt you for further clarification and with each one, further frustration. Oh and BTW, the same FAQ pages which e-commerce sites laughably call ‘customer support’ –

“ And, I wonder why your ASCI customer service scores are soo low Mr. or Mrs. e-Retailer :),” says this blogger facetiously, to her audience .

 

 

 

And, we’re not talking about fuzzy logic either – Simply put, fuzzy logic is fun to say, yes, and technically is:

–> Rule-based technology with exceptions (see arrow 4)

–> Represents linguistic categories (for example, “warm”, “hot”) as ranges of values

–> Describes a particular phenomenon or process and then represents in a diminutive number of flexible rules

–> Provides solutions to scenarios typically difficult to represent with succinct IF-THEN rules

(Graphic: Take a thermostat in your home and assign membership functions for the input called temperature. This becomes part of the logic of the thermostat to control the room temperature. Membership functions translate linguistic expressions such as “warm” or “cool” into quantifiable numbers that computer systems can then consume and manipulate.)

 

Nope, we are talking Neural Networks – the absolute Bees-Knees in my mind, right up there with social intelligence and my family (in no specific order :):

–> Find patterns and relationships in massive amounts of data that are too complicated for human to analyze

–> “Learn” patterns by searching for relationships, building models, and correcting over and over again model’s own mistakes

–> Humans “train” network by feeding it training data for which inputs produce known set of outputs or conclusions, to help neural network learn correct solution by example

–> Neural network applications in medicine, science, and business address problems in pattern classification, prediction, financial analysis, and control and optimization

 

Remember folks: Knowledge is power and definitely an asset. Want to know more? I discuss this and other intangibles further in part 1 of a multi-part study I am conducting called:

Measuring Our Intangible Assets, by Laura Edell

‘Social Intelligence’, the bridge between social networking and business intelligence, Starts To Build Momentum

Several years ago (in early 2009), I blogged about two of my passions, social networking and business intelligence. It was about the time that business folks starting building their profiles on LinkedIn, extending their networks via Twitter and started realizing that FaceBook wasn’t just a tool for their children to build their socialization skills but was a vehicle for networking with other professionals within and outside of their own personal networks. Grasping the power of the social network was still this abstruse almost arcane concept in its theoretical potential for corporate America. And while there were those visionaries, like the Wynn in Las Vegas, about whom I shared an anecdote within my TDWI presentation on Social Intelligence (one I will share in a moment) later that year, most companies saw social networking websites as distractions and often, banned them from use during the work day.

Why was Wynn different?

As a frequent corporate traveler, I have had many “check-in” line experiences: from the car rental counter to the hotel check-in line, I have had both good and bad experiences. On one somewhat lackluster experience, I was standing in line to check into the Wynn Hotel in Vegas. Several people ahead of me was a gentleman, fairly polished but obviously frustrated by his conversation with the desk clerk. As a highly perceptive observer (or at least, that is how I am spinning being nosy), I listened in on the situation. This gentleman had reserved a junior suite, since he and a colleague were sharing the room, a common occurrence as companies started to tighten their belts around corporate travel expenses. And, the suite was not available. The clerk seemed to want to help but was strapped by her computer system telling her no suites were available until the following night in the category booked. It turns out, she was new.

Quite gruffly, this gentlemen left the line, and proceeded to stand in the lobby, talking to his colleague about the disappointment, and commented that he was going to Tweet (post a message to his Twitter account) that buyer beware when it came to staying at the Wynn. Now, in a city like Las Vegas where capacity can exceed occupancy rates, combined with a name like the Wynn, combined with the sheer reach of a site like Twitter, this kind of negative word of mouth can really hurt a vendor. And more often than not, comments like this are over looked, or at least, were overlooked in the past, because of the lack of technology or reporting to alert such vendors to such disturbances in real time. In a travel situation, do you want to know that your issue was addressed after your trip with a gift and apology in the form of a coupon for choosing the stay there in future?

No…In fact, the breakage rate on such post-trip coupons is 70-80% (remember, I used to work for the largest online travel consortium) :). Thus, granting coupons is ineffective at winning the customer back. And it is because your trip, whether for business or pleasure, was ruined. And no, I am not being dramatic. You might not think a rooming issue can ruin a trip but it can. In fact, just being placed on the wrong floor or near an elevator or merely any event that is different that you were expecting can ruin a trip from a customer’s perspective.

But, I digress…

Back to my story: As soon as the customer finished posting his Tweet to Twitter, he turned to his colleague and walked to a cafe and sat down to order some refreshments. By the time I reached the front of the check in line, I noticed what appeared to be someone who appeared to be in charge (dark suit, name plate, piece of paper in his hand) approach the gentlemen and start a dialogue with him. Within moments, the two shook hands and the paper (which turned out to be room keys and an invoice) were swapped and the authority figure left about his business.

Intrigued, I walked up and asked the gentlemen what had happened. He was so excited by what had happened that he asked me to wait while he posted a note to Twitter. Since I had heard the original part of the story, I started to deduce what was happening. When he was finished, he said that gentleman was the hotel manager. He had been alerted to the room situation via a Twitter application which alerted management to travel disruptions as they occurred in real time to his smart phone. It was his job to make sure the customers were found in the hotel and the situation fixed to the betterment of the customer, no matter the situation. In this case, the customer was treated to an upgraded full suite, which was available, at no additional cost and given vouchers for the show that evening. The customer was so pleased, he had to go back to Twitter to recant his previous post, and to alert people to how well the situation was handled not days after the fact, but within the hour of it occurring.

I was floored.

You hear about the concept of the customer feedback loop but rarely do you see it implemented well or in a way that can affect overall customer loyalty or perception of the brand. In this case, it not only affected the customer and his colleague, but his entire social network.

Later, I found that same manager and asked his what he used to alert him to the Twitter incident from earlier.

He smiled and said we are in the business of pleasure, thus, it is our job to know when we fail. Alerting in real time is not as hard as you think with the right tools and technology. And left it at that.

Ok, so Vegas is a pretty secretive world of proprietary tools and technology, and are often market leaders when it comes to adoption.

And that is where Social Intelligence comes in: the ability to understand the Voice of the Customer as expressed within the intricate web of the social network via tools and technology. What better tools for alerting and reporting on incidents in real-time than those offered by the Business Intelligence suite of tools (at its most generalized state).

I am so happy to also report that in 2011, BI technology is taking an even larger footprint into the Social Intelligence space. When I can say more, I will. Just know I am really excited about the future ahead of us folks!

Happy New Year readers.

Interesting BI 101 Deck