The Capability Model in Action - Ahh deep understanding of the data and related business - this is, in my opinion the one aspect that is most resisted - people don't want to know that much and it hurts processes.
Veracity of data - Is it reliable - This is a very problematic aspect of our data. You have two maybe three departments involved in data collection and storage and we have seen times when one or the other departments have modified the data to their specific needs (not discussing before hand with others).
Velocity - In my opinion this should be discussed upfront for any new data-analytics process. Executives always want things asap but is this really necessary? Discussion and reflection on what is needed and when - things might not be needed asap.
Glad to see realisim, as well removing some of the mytique, in defining the skills needed for a Data Scientist/Worker, even from a Data Scientist: advanced expertise and experience in at least these three disciplines: Information Technology, Business Expertise from the internals of the organization, and Advanced Analytics as well as the desire to do they work required (acquiring education along the way). This puts realism into the real skills that can be acquired to do the work as well as realistic salaries to match the skills.
Some of the approaches today miss the critical point you made that "Analytics is about bringing the best information to the Point of Decision", it seems implicit in the very nature and reason for doing analytics in the first place.
Mark, thank you for some refreshing new thoughts on how to get to real results faster than what most consutants are presenting; the requirements approach doesn't work and should be replaced by a new paradigm.
Yes we do ask and are looking for data scientists. Buts that mostly up to the HR department. After they screen them according to our specs then they give us a list of those that made the cut and we take it from there
We're almost out of time, but I do want to ask one last question, and that's on data visualization. When you talk to people who are or want to be data scientists are you now adding that into your disucssion as a desired skill set?
@Doug! Thanks for tuning in! I typically use a supervised approach, i.e these data are associated with X, and these aren't...but there is a lot of manual work in manipulating the data to allow text analytics to distinguish the patterns
@benmoreland - the relationship with IT and with the various "silos" of data can be very challenging. I tyr to overcome those by using the value proposition - if we can break down those silos we can get to significant ROI
@Mark In one of sllides, you have mentioned about the advanced expertise in varied fields like IT, Business and Advance analytics and you have mentioned few examples of people having multiple degrees. Is there any other alternate way where one can gain expertise on all these domains without going to college, if yes, how and where does one have to start?
I've been thinking about the Meta's recent blog post about Kiss & Make Up with IT in the context of your presentations today. Big-Data Analytics Architecture often is going to pull the IT folks in, and they often don't share your vision and see having to support hardware or software changes as a burden. How do I get IT to cooperate with me? They often see my Big Data projects as creating more work for them.
Priority goes to Voice over IP phones, then Video over IP, then important data, then not important data. This could fit in the 3rd place but converged network traffic will cause quick access to be an ongoing challenge.
@Noreen Well I would think you have to makes sure your network is optimized from servers to network throughput, figure how you are going to draw data from sources the most efficiently, and then port this data into a program that can turn this data into something useful quickly. The goal of course is to beat the competition to the punch ! No small task ...and I am sure I have forgotten something.
@alihashmi Nothing yet, I have been so busy with my normal responsiblities which is mainly tech related, I have not had a chance to think about extending my skill set in this area. Which is something I plain to do in the comming months.
Turning this data around quickly into some useful information is vital....and really the difference between a company that effectively deals with Big Data versus those who just want to say they do.....
We so far have been fortunate in that we are able to handle the demand for big data but again thats now. I am very worried about the future because along with our clients we now are seeing a rise of workers byod and they are taking these home. And when they do that we cannot secure it or know who has access to it.
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