Twitter is Google Search in Reverse

Remember the search interfaces of yester-years? Pulldowns, check boxes, and operands defined the experience until Google stripped it all away. The exposed input box felt naked next to its companions. Yet the babe had brawn. Over the years the ubiquitous search box came to dominate content retrieval because of its simplicity, expressiveness, and relative clairvoyance. You typed some text in, Google rewarded you with a best guess of information you must have been looking for.

Our utterly selfish "give me" relationship with Google quickly earned Google medals in advertising. We were still putting enough "in" to Google's Engine for it to quasi-cleverly match up your key words with the highest-bidding, and content-relevant advertiser.

Spin up to today and we have a similar input box delivering 140 characters of further indulgence. "Give me" seemed to evolve social consciousness into an "I am". Our passive-aggressive social cloud is bloated with micro-summaries of people's whereabouts, whatchados, grandiose plans colored by nuance and mediocrity. And what with it? Nothing. Or rather nothing much.

Those still riding the web2.0-enabled Collaboration and Productivity opportunities are escaping email for what they hope to be a Twitter-gendered repose from Info Glut. But this is naivete. Every medium for communication will only alleviate over-saturated predecessors until usage turns into abuse-age. A much savvier colleague of mine had an insight that, paraphrased, in the consumer world, Twitter creates communication where it does not already exist. In the workplace, however, we are trying to better direct our information traffic, to reduce abuse, to improve relevancy, and tune interruption.

Twitter is a cloud of unstructured data. This data is time sensitive. A classical use case is "What am I doing now?". Stretched a bit we can evolve to "I am planning something right now that I will do shortly" and "I have just done something stranger and friends alike should know about".

As is, this glorified presence system is prime for integration with our Instant Messaging Clients' Status Notes or Away Message. But this is not very exciting. As the significance of any single Twitter fades with passing seconds into oblivion, what are we, the Information Workers, gaining from such an exchange? A Status Feed is great, but really, just the tip of the ice berg.

Sometimes actual Knowledge is Twittered. For example, "I just read a great article on Silverlight about Animations at http://..." or "Firebug just crashed on me after visiting a site with Google Ads again!".

The first sample is clearly relevant to people interested in Silverlight. The second is clearly a bug report and a stability alarm. Perhaps unfiltered noise in the consumer cloud but in the Enterprise access to these streams of consciousness is the very essence of the next generation's competitive edge.

And so Twitter must become the reversed flow of Google-like search.

In the Enterpise, search blankets our repositories and knowledge bases, constructing a uniform way for retrieval. Twitters (micro-content, really) must be deconstructed and filed back in. To be able to distinguish Status from Knowledge and to create on-demand availability of this type of information mashed up with related information is the cosmic pixie dust of the future.

Speaking of the future, Twitter recently acquired Values of n for I Want Sandy, a personal digital secretary. If Twitters about "right now" generate Knowledge then Twitters about the future must generate Activities. Activities produce Knowledge: more Twitters, CRM information, documents, blog posts, etc. When all this information is accounted for it truly seems that the personal Digital Assistant need not be so personal after all.

To move beyond this "give me" towards a notion of Coordinated Intelligence, we will need to embrace Semantics, Context, Community-friendly Knowledge Management strategies, and that bit of nakedness. I'll race you there.

NYBI Meetup #3 Recap

The Recap
The third Meetup was fully dedicated to discussion. It was driven by a few PowerPoint slides from one NYBI member's presentation given at the CTO Summit in Summer of 2007.

One slide of interest was about a proposed BI Ontology reproduced, in part, below:

BI Ontology

• Decision Space
• Decision Purpose
• Decision Frequency
• Decision Impact
  
• Tool Space
• Data
• Models
• Experience
• Feedback
  

There was another level of detail for each sub-bullet that will become available when I post the original slides. Ontologies are important because they provide a shared and common understanding of concepts presented and discussed in forum. The same way that we hope to derive consensus on Trends and Truths within the BI space, so do we hope to establish a descriptive (and shared) language about BI with the aid of the proposed Ontology.

An introductory slide or two spoke to the "State of Affairs" as well the "This is how we came to be here" and spurred on 2 full hours of discussion.

Some highlights:

• Most organizations looking to introduce BI into their fold succeed in rolling out a Data Warehouse. Rolling out Reporting infrastructure is the difficult part. If the organization is lucky enough to succeed, this reporting infrastructure tends to be the most expensive investment.
• The industry itself evolved from ad-hoc tools to very structured tools and mechanisms. Approach to successful BI implementation became a Trade and a science in of itself.
• The BI Ecosystem is very large. There are a few established Tools and Tool Vendors but community of people that provide quality or reporting services is for these Tools is significantly larger.
• Vendor tools, however, are going through mergers and the Vendors are losing independence. Will a community emerge to not just support the Vendors but to actually drive innovation in the space and offset the aforementioned loss of independence by Vendors?
• Paper distribution has been consistently declining over the last 4 years to be replaced by digital systems. Are paper statements in existence today exercises in Data Summarization? Why are our banking statements and our bills still so confusing and uninformative?
• In turn, with an encroaching demand from end-users to be able to do real-time analytics and trending of their own personal data, why are banks so slow to spice up their online banking systems? Are new sites like Mint.com and QuickenOnline setting a new standard in personal finance analytics?
• How much longer will we wait for the higher activities of analysis? Is the next step in BI Tools that aid in decision making process rather than just visualization? Can "actions" exposed by these new BI Tools be contextually relevant and drive specific end-results, such as yield competitive advantage?
• Volume of data is now manageable. Tools that are making sense of this volume are driving innovation.
• Is the notion of Business Intelligence simply too constrained to fully encompass possibilities? Are we transitioning to a more general-purpose, behavioral, Collective Intelligence that enables an organization to tap into data previously unaccessible or simply discarded? Can this aid an organization's process of innovation and feed competitive advantage?
• Is it possible to phase out manual Knowledge Management along with paper distribution and plugin in systems that interpret data on a Semantic level?
• Are Personalization of Services and Individual Privacy on opposing sides? Are the notions of privacy on the Internet and a Corporate Intranet so drastic that most innovation in Collective Intelligence will, in fact, occur on the Intranet where Individual Privacy is a more manageable Can of Worms?
  

Truths and Trends

• Truth: There are lots more data sources of interest than what is currently accessible on the internet
• Truth: Improving on what computers tend to do well does not necessarily result in value to the end-user
• Truth: Audio processing is more difficult than Video processing
• Trend: Use of Voice and Video as datasources is a new frontier. We wonder how much of it is native analysis vs metadata processing.
• Trend: More real-time decision-making at the hands of the user.
• Trend: Enterprise environment will give way to enterprise community.
• Trend: Web2.0 Collaborative tools are becoming more accepted in the enterprise as both the enterprises and the vendors mature
• Truth: There are lots more data sources of interest than what is currently accessible on the internet
• Truth: Improving on what computers tend to do well does not necessarily result in value to the end-user
• Truth: Audio processing is more difficult than Video processing
• Trend: Use of Voice and Video as datasources is a new frontier. We wonder how much of it is native analysis vs metadata processing
  
• Trend: More real-time decision-making at the hands of the user.

Next Meetup
SAP Business Objects folks will be joining us to help us explore Xcelsius, their new analytics tool. They will also speak to the rest of the near-future product road-map. Details are available on the http://nybimeetup.org site.

NYBI Meetup #2 Recap

The Recap
The second NYBI Meetup took place in a spacious board room of 1633 Broadway. The meeting kicked off with an exploration of QlikTech's in-memory analytics platform called QlikView with Scott Taylor and Nik Boman. QlikView is seeing success in the financial sector in NY and we wanted to know what made QlikView tick, what made it great, and how the "wisdom" of the NYBI crowd could make it even better. The PPT presentation of QlikView is available from the NYBIMeetup.org's File download section here.

From my recollections and sparse notes
QlikView is a visualization and analysis tool.

QlikView allows a Super User to correlate data sets from various data sources (local or remote) and to store a highly compressed (loaded data is 15% on avg of original data size) snapshot of the relational data map into memory. Coupled with a file structure that permits O(1) access to data and linear, O(n) traversal of data sets, this in-memory storage essentially serves as a Virtual Cube of correlated data for the user to play with. A very rich interface that is available in client, or embedded form, permits almost serendipitous creation of dashboards with parametric drilling, intelligent filtering - the works. Controls adjust themselves and each other instantaneously - the Regular User interacts with the charts through intuitive click and drag motions. The assumption is that the data loaded into QlikView is already of high quality/integrity.When asked "Who is typically the first person among client prospects to go 'Oooh! Aaaah!", response from the QlikTech guys was "Deprived end-users that have to go to IT for cube build-outs that may take months to generate 'ooh and aah'. IT that sanctions ownership supervises, scrutinizes, realizes that QlikView is a boon to them."

Challenges to QlikTech and points of Discussion

1. Is not the goal of BI, actionable outputs? Hypothetically, with QlikView I found my 3 bad products and I want to commit the pricing strategy - I have to write something out/communicate - If I want to do that, I have to interact with other modules (beyond BI modules) to make actions, how do you make the action happen? Should the products not better integrate into popular desktop productivity apps? For example, how can my interaction with these dashboard be affected if I could key off of an email address to view a Sales Report for that person in a sidebar within Outlook? (reference to Xobni). As a platform, QlikView has potential for such rich integration - the exercise is left for IT or QlikTech's affiliates.
   
2. What kind of API should BI platforms expose? What do we really wish to do on the Desktop vs on the Server?
   
3. What about community contributions? A community of business partners and affiliates who align to complete a vertical is not necessarily the same things as, let's say, a community of developers writing and contributing extensions to enhance a product's core (i.e. Firefox community and extensions development). Is there value for BI vendors to stretch beyond affiliate networks in order to establish an open participation and innovation culture? With respect to NYBI Meetup, what would something like that look like?
   

Truths and Trends
Following above rhetoric, in turn, should not NYBI Meetup be about actionable outputs? After all, a Community has to deliver value to those it serves. One baby step forward was to conclude the meetup with "Can we derive any Truths or Trends about BI from topics covered in discussion?" Here is what we came up with:

1. Truth: People are looking for a better way to solve the same problems. Core Issues of BI are still prevalent. Recent advances in BI tech now provide better ways to deal with these Issues. QlikView is a note-worthy example of such innovation in the space.
   
2. In-memory processing is Trend.
3. RIA (AJAX) adoption and movement to web interfaces is a Trend.
4. Truth: Data Quality is a Foundation for BI
5. Truth: BI Tools need to consume WebServices as a datasource
6. Truth: Killer App = functionality + price

Next NYBI Meetup is at end of April
We are always looking for interesting presentations. To sign up, please visit http://nybimeetup.org.

NYBI Meetup #1 Recap

The Recap
The first New York Business Intelligence Meetup ran about 40 minutes over its 90-minute allocation. Membership grew from 3 to 26 members in under two weeks. Ron Moore played host, in a cozy, makeshift conference room, to 11 members (12 total). I was the only person constantly looking at the clock - but that came with the job description.

Agenda was "oatmeal" - basic ingredients congealing into something healthy and edible by a diverse group of specialists and enthusiasts, all feeling out NYBI Meetup's stomping ground. Introductions and individual identification with the BI space were in order. There seemed to be an even distribution of hard-core practitioners of BI, entrepreneurs looking to carve out a niche, enthusiasts (like myself) looking for a clue, instructors, and technologists struggling with the "what should I" and "how should I" aspects of the field.

This naturally lent itself to a prolonged deliberation on various topics. From philosophy to best practices and usability, the group was etching out boundaries and establishing interest camps. For a taste, some thoughts floating around covered:

1. Who's job is it to define Vision for BI within an organization? What role do Technologists play?
2. How does one go from a home-brewed analytics engine with Excel as the interface to a sustainable, cost-friendly vendor solution?
3. What do end-users want out of BI? Do they even know?
   
4. What are some common applications of BI? What are the new, creative applications that are enabled by recent trends in how people and systems exchange information?
5. What is the balance between need-based drivers and "cool" technology-based drivers?
   
6. Who's job is it to create awareness and to sell?
7. Why is the Microsoft stack more attractive than other stacks? What is the criteria?
8. What is the BI Pyramid and what is it's Tip?
9. Why is data integrity so darn difficult?
10. Can Open Source solutions compete?
    

Some entertaining, but paraphrased, sound bites:

• Technologists tend to lead innovation within BI because they can build "It". However, technologists also build a lot of "S. H. It".
• If the computer looked like a frying pan maybe my grandma would be more willing to use it. Shouldn't the same hold true for BI visualization tools?
• So, you could trade 2 Julia Roberts for 1 Richard Gere? -- In reference to a startup in Russia that created a data-mining driven "forex" market where people trade the perceived value of a celebrity
  

Ron passed up his presentation on Essbase for these discussions to continue. We did however, get to see a brief intro to Microsoft's Performance Point Server from Victor Shamanovsky.

For a wrap up, I wanted to set a clearer trajectory for the Meetup and to focus conversations towards more tangible/practical means. Consensus appears to be: 50% Process/50% Technology. Philosophy, high-level discussion akin to what's highlighted above would fall into the former category. Product demos and real hands on BI technologies for the latter one. Essbase and PPS presentations will roll over to the next event.

My take...
Achieving topical focus for a diverse group of interests and experiences is quite challenging. Discussion should most likely pivot (horrible pun intended) on:

• Business sectors and verticals. Past, current, future role of BI. Practical applications, best practices, room for innovation, market leaders, vendors, entrepreneurs etc.
• The discipline itself. Warehousing, ETL, working with structured/unstructured data, core technologies, architecture, data design and integrity, reporting, UI.

Perhaps each get-together should recognize a focal point for the Process portion, ie, Profitability modeling in Finance or Sentiment Analysis and Tonality. The Technology section should then dive into available solutions, innovation, and best practices within the realm of the topics discussed in the Process portion.

Where can this take us?

• A high-caliber Meetup around BI can obviously provide a business networking forum for industry professionals. Strengthening NYBI's reputation and brand will attract high caliber sponsors, vendors, and professionals. I would love for employers to look to the meetup for capable talent pool, for entrepreneurs to find collaborators, and so on.
  
• Can this meetup influence the trajectory of innovation within BI? Will vendors and entrepreneurs be interested in vetting new products and ideas through the meetup? Can we do more than discuss and look at demos and actually deliver our musings, evaluations and conclusions to the vendors themselves? In turn, can we build a reputation and level of trust for all of this to become a reality??
  

I submit the above as evidence of a budding Meetup. I leave it to the members to keep my optimism grounded. Thanks to everyone who could make it. To those who couldn't, hope to see you next time! Special thanks to Alon P, my buddy and co-organizer of the Meetup and to Ron Moore for hosting.

To sign up, please visit the NYBI Meetup Homepage. There will be a healthy amount of activity through the businessintell-2@meetup.com mail-list as we build and prepare for our next event in March.

New York Business Intelligence First Meetup!

In my musings on the next-generation enterprise, I keep coming back to the position that any social and contextual insights gleamed from provisioning new collaborative working models must influence an organization's business intelligence systems. This is not limited to rich interfaces and better interactivity. In fact, collaborative revolutions within the Enterprise will both feed and consume information from internally facing BI systems - the true neural network for an enterprise's brain.

I also recognize that my understanding of BI is rather rudimentary and lacks the perspective to truly participate in innovation within this field. And so, the New York Business Intelligence Meetup is born.

Click here to check out
The New York Business Intelligence Meetup!

First meetup is Tuesday, February 23rd at 7pm and is sponsored by Ron Moore, Founder and President of Marketing Technologies Group, an Essbase consulting and training firm. Ron has also, graciously offered his office space for the event, conveniently located in the Financial District, 55 Broad St. 10th Floor.

For more details, please visit the Event Page.