Saturday, March 15, 2014

Predictive Analytics Conference

Predictive Analytics has come a long way in last few years. It continues to get simplified and the consensus is that you no don't need a PH.D. to practice it. It is no longer a backroom activity and modern tools are allowing it to be deployed to much larger population in an organization. You also don't need to wait for your data warehouse to be in place before you can start predictive analytics. The tools continue to make it much easier to visualize and explain the results.

In general, the field is evolving at a rapid pace. Still most of the organizations, with few exceptions, don't have a strategy and roadmap in place. More awareness is required to understand use cases and best practices. Yes, there are more predictive analytics books on this topic which again validates the popularity of this discipline. But a conference like Predictive Analytics conference is a good place to start where there is a great opportunity to network and understand how others are benefiting from this discipline.

I am a blog partner with the Predictive Analytics and you can get 15% discount using the code "PMBP14." Here are some upcoming dates:

Predictive Analytics World Toronto – May 12-15,
Predictive Analytics World Chicago – June 16-19,
Predictive Analytics World Manufacturing Chicago – June 17-18, 2014 -

Sunday, December 23, 2012

Web Content Management: Opportunity to integrate with Big Data Analytics and Machine Learning technology!

Web Content Management (WCM) space has come a long way in terms of maturity from mid 90s to where it is today. Many companies, specially the ones who rely on their online business for revenue generation, are probably going through third or fourth iteration of overhauling their WCM solution. There are hundreds of commercial and open source offerings in this space catering to all sizes and different needs.The WCM vendors have also done a good job in keeping pace with the customers' demands. In fact, WCM has graduated to being part of a Web Experience Management (WEM) or Customer Experience Management (CXM) where WCM is one of the aspects of the solution along with  web analytics, optimization, targeting, A/B testing, social media integration, personalization and marketing integration. Overall, the space is matured and all major players from HP, Adobe, Oracle, Opentext, SDL, IBM, Microsoft and hundreds of others are playing in it. All of them are trying hard to find their own niche and differentiation as it is a crowded space.

CMS tools have also become more business friendly and no longer require the level of involvement of IT for every small task. Now the business has better ability to do tasks like content creation, presentation management and workflow without IT intervention. These tools continue to offer advanced features like in-context editing, multi-site management, multi-channel delivery, social media integration, globalization etc.. There is definitely room for improvement in the areas of multi-channel delivery, globalization, social media etc.. All leading products support standards like J2EE/.Net and have a cloud offering so that is no longer a competitive differentiation. Mobile is definitely a must-have thing now and everyone, CMS vendors as well as businesses, is trying to keep pace with the increasing number of varied mobile devices in the market. Definitely, there are more channels and platforms to worry about now. Content is no longer though of as a web page now! It doesn't mean because of these advancements in tools and technology, all projects run smoothly. They don't and the main issue is lack of CMS experience, inability to structure CMS projects correctly from timeline perspective and in some cases because of disconnect between business and IT. I also wonder where do we go from here as far as capabilities of CMS tool is concerned?

The focus on building an integrated digital marketing experience by vendors where content is at the core is the right thing but one important aspect is still lacking. That aspect is ability to have recommendation and deep personalization as part of the experience. The bar is set by and it is the model  everyone can look upto. It is not an easy thing to build but CMS vendors need to think of ways to offer templates which can enable it. They also need to think of  innovative ways to integrate with all the work that is happening in Big data Analytics world. In my experience, companies have a very good understanding about the level of personalization and recommendation they should provide to their end users. They just don't know how! They are just constrained by the limitations of their IT departments to deliver this functionality. IT also has a big challenge as they don't have access to out-of-the-box tools or an easier path to provide such functionality. Analytics and machine learning, technology behind deep personalization and recommendations, are not understood very well by many IT departments. It is also not easy to build as an  investment like an in recommendation technology is not easily affordable. Something to keep in mind for CMS tool vendors!

Thursday, September 29, 2011

Data Without Borders: Data can be a burden if it is not set free!

Wikipedia describes philanthropy etymologically means "the love of  humanity"— love in the sense of caring for, nourishing, developing, or enhancing. Historically, philanthropy has always been associated with giving generous donations of money. It will continue to be associated with giving generous donations but some professionals can make bigger impact by donating their skill set than money. Yes, I am talking about the skill set of data science! Data science is relatively a newly coined term and probably originated from data geeks working on hard data problems in the companies like Linkedin, Facebook and other technology companies who needed these experts to make sense and insights from the vast amount of data being produced everyday. Data Without Borders, a newly founded organization, seeks to match non-profits in need of data analysis with freelance and pro bono data scientists who can work to help them with data collection, analysis, visualization, or decision support. The concept is brilliant and makes sense!

There are various initiatives out there where technology is being leveraged creatively to help the non-profit organizations. The Bill and Melinda Gates Foundation has recently funded a new digital-media hub call The hub uses semantic technology to create a platform that combines the video sharing power of YouTube with the open information of Wikipedia and the mission of your favorite advocacy organization. I had written about it in more detail in one of my posts titled - Philanthropy goes Semantic.  Ushahidi, initially started as a simple web site to map reports of violence in Kenya, is another non-profit tech company that specializes in developing free and open source software for information collection, visualizing and interactive mapping. To my knowledge, Hans Rosling, a medical doctor and a statistician with decades of work studying outbreaks in Africa, is probably the first data science philanthropist. He co-founded Gapminder foundation which developed the Trendalyzer software, acquired by Google, that converts international statistics into moving, interactive graphics. His TED presentation about his best stats you have ever seen is worth watching.

The genesis of the idea of "Data without Borders" is to match the NGOs, who are sitting on lots of data with nobody to look at because of  resource and budget constraints, with data scientists who have the energy, time and passion to make sense of this data. Timing of this initiative couldn't be better because data scientists can now have a common and noble cause to rally behind! It is the beginning of a powerful vision but it will surely have its own challenges.  Having some experience with an NGO myself, I can say that sustaining the enthusiasm and commitment of data scientist for a long-term can be challenging. We are all aware that data scientists are going to be one of the most sought after, busiest and highly paid professionals in the next decade! So I will go for a good data scientist with more commitment over a rock star data scientist in this context. Also, a weekend of data hackathon in this context will probably won't be enough because data Science is an iterative process and will require an ongoing engagement. It is still not clear to me that why there are not initiatives like open government data in case of NGOs to build powerful data mashups. I am aware of new standards like IATI but its more about aid spending by governments. In this context, I believe that too much data can be a burden if it is not set free and used effectively. Ideally, in case of NGOs, open data shouldn't have political or privacy barriers. In the end, the co-founders of "Data without Borders" will need all possible support, structure and maybe funding, to be successful in their mission. Winston Churchill, rightly said, "We make a living by what we get, but we make a life by what we give."