 Okay, so last in the dissection of the individual parts of the programme, we move to the data scientists and to talk us through that we have, well we welcome back Maureen Norton who is the Global Data Scientist Professional Leader for IBM and co-author of Analytics Across the Enterprise, how IBM realises business value from big data and analytics. Maureen is a distinguished market intelligence professional, the first woman to receive this recognition in IBM, congratulations Maureen. She leads AI and data science based transformation initiatives to accelerate the development of insights to drive action. Maureen championed the development of an award-winning industry recognised professional certification programme for data scientists and she partnered with the open group to collaborate with other enterprises on the standards and skills needed for certification in the profession. So Maureen is going to tell us this morning about the open certified data scientists over to you Maureen, welcome. Thank you, thank you very much Steve, appreciate that. Well you can't talk about the data scientist profession without first talking about data and we all know we're living in this incredible time, you know there's 500 million tweets sent every day, 294 billion emails, four petabytes of data created on Facebook. Maureen, Maureen, sorry it's Johnny, I just to cut in we're seeing your entire view not just your presentation view. Oh let me switch that, see your slide and your next slide and your notes. Oh we don't want to do that, okay let me see how do we fix that, I think there's a switch switch here, this is my, let's see go back here. I know you had it working fine in the test so. Yes we did, it worked fine in the test but kind of like Andra's battery going off, you know, once you start hitting it live, okay so. Maybe the top right hand corner options, I don't know if you've got some display options there. Yes, let me just check that out, here we go. That better? Yep, that's absolutely fine, thank you. Thank you for the interruption, I really do appreciate that. Okay, okay so as we were talking about there's just an explosion of data and you've probably heard of kilobytes and megabytes and gigabytes even terabytes and all of those are starting to sound like common everyday amounts that you would talk about attachments and emails and what's really fascinating with how the amount of data has been exploding is that you know there are 44 estimated zeta bytes right now and that as we think about it is there's 40 times more bytes than there are stars in the observable universe. So we all know we're living in this incredible time of data just exploding and this is something where you know the data scientist profession comes in right the professionals who can help make sense of all of this data much of it untapped for all of its its insights but there's there's also something that is troubling and that I think the open group certification can really help with. Gartner estimates that 85 percent of big data projects fail. Venture beat reports 87 percent of data science projects never make it to production and Gartner said that through 2022 only 20 percent of analytic insights will deliver business outcomes. So why do so many fail I mean there's several reasons you know of course not having the right data not having the right talent and again this is where I think the open group data scientist certification can really help making sure we have the right talent. A lot of times it's just solving the wrong problem not really deploying value and thinking that deployment is the last step you know we need these professionals to think of deployment up front how it's going to be integrated into a business process and another reason for that amount of failure is applying the wrong or worship no process so without established and clear methodologies for data science projects they often resort to ad hoc you know resulting in silo data missteps and kind of not looking at the entire life cycle. Not to mention sometimes if you don't have that kind of structure and requirements built around it there could be things like forgetting ethics right models will ruthlessly optimize what you tell them to do so this could be good but it can also lead to really serious ethical legal and brand damaging outcomes for example many of you have probably heard this example about target famously their advanced analytics team was tasked to predict whether a woman was pregnant so that they could then start offering targeted ads for products. Well they were very successful in this prediction a little too successful actually they were sending ads to a team whose father was very angered by these targeted ads at his teenage daughter he didn't know in fact that she was pregnant so this team well very successful they didn't factor in the wider privacy concerns and implications and that resulted in brand damage a public backlash for that invasive nature of it so there's really a lot at stake with this profession and so as IBM started to look at how we were going to try to put things in place that could really help the profession we partnered with the open group and built on those standards we in fact came to the open group to propose that the data scientist profession be added and we had our view of what a data scientist you know should do the conformance requirements that they should meet and and said let's work with other members and other companies because we didn't want just an IBM view of the world or profession you know we really wanted that industry standard too as James so eloquently mentioned earlier on to to instill trust in that profession and it's critical when you have people who are using supporting and analyzing your data to have that profession be trusted so we built an internal IBM certification to articulate these three different levels and it really adds so much value by being an ACP it really elevates it so that when we recognize somebody with the certification internally with the badges you see there they are also recognized by the open group and have that external validation and credential as well and then as also mentioned earlier it really extends the value into other standards organizations so we're thrilled that for the first time because the data scientist profession is certification is still just a few years old so we're thrilled for the first time that BCS the British Computing Society will be recognizing the level two and level three data scientist certification towards becoming a chartered IT professional so we see great value in that the other thing I wanted to make you aware of is that even in the very first year the data scientist certification started making these kind of lists the top 15 that will pay off what's really important though is on this list of 15 there's very few there's only two that you could categorize as vendor neutral which is very significant you know the the fact is that a lot of these certifications are also knowledge based not experienced base so you know we're very proud that we made this list but I think the fact is that it's really a differentiator and it's it's very comprehensive because it is an industry standard and something that we have a lot of buy-in for so the other interesting thing and I'd encourage companies if you haven't started looking at the open data scientist certification we were able to implement that internally and also we were recognized with an industry award for great employers a Stevie award because of what we put in place for our data scientist so we know we're onto something good here so the certification path is really a way to craft that clear career model and path towards certification and as we are developing this and going forward we wanted to really step back and say okay this is new right most data scientists have never had to certify and so having a professional certification we get the question often well why should data scientists certify some of them will be saying I have my phd already or I have this qualification you know why do I need or should I do this and I really think that there's kind of four buckets of reasons and many of these have been touched on before in the other professions but for the individual it really helps them stand out and be more competitive to fuel career growth and it gives that all-important industry vendor neutral recognition for the for oftentimes for the work that they're already doing for your enterprise it helps you showcase talent and for the profession it helps elevate it to build more trust now I specifically jumped over for clients because for clients it is extremely important and I have some data I wanted to share with you on that so increasingly clients are asking for certified professionals on their engagements 93% in fact of it decision makers believe that certified team members bring added value above and beyond the cost of certification so there was a global knowledge did a survey and back in 2008 was the first time they did it skills and salary report and at that time they asked about certification so you know over a decade ago and there'd been many articles and discussions regarding the value of certification but in general employer support for them was kind of mixed and then you fast forward to that number I mentioned now 93% of it decision makers really see the value of that certification so I mean what a difference a decade makes certifications have become increasingly important and valued and that is something that we wanted to also see for the data scientists profession as more and more companies are understanding the value of their digital transformation incorporating AI and data science solutions and so how do they quantify that value they really looked at it as you know when you have certified individuals on projects it's increasing increased productivity problems are solved faster troubleshooting is quicker and there's just a lot of those things that have been really helpful to that so all of these four buckets of reasons I think are are great but what I think is even more powerful is that the synergy among them and that's really where community comes in so we wanted to really focus on building a strong community of professionals that can help each other mentor support and really help build up the competence and skill level of that so as James mentioned earlier you know different professions have gone through this historically and if you think about it would you let an architect build your house if they didn't meet certain standards would you let a surgeon operate on you you know if they weren't held to high standards and then of course then would you entrust your data to data scientists that are also not held to those standards and I think the resounding answer to that is no you would not it's too valuable and too much is at stake so you want to make sure your data is entrusted to those with the capability to derive these very important trustworthy insights and that is why I'm really excited to share with you that the open data scientists profession certification helps to set those standards and it was done as I mentioned with all you know all the members were allowed to you know review and comment and edit so this really was that collaborative effort and the standards are with the role of data scientist the you know we should make sure that there is a clear hypothesis for the problem being solved that the methodologies are being tailored for that problem and so being able to build this these standards to ensure data scientists are using solid methodologies and approaches that are tailored for this problem is key the other part is this is very tied to an organization's digital transformation so designing a strategy based on the talent needed for that digital transformation is critically important and that really will help to drive the trust in the profession to unleash the innovative spirit that we see hidden in the company's data and so ensuring that data scientists really meet these will help elevate your business strategy and it empowers that talent to really help with that so how did these standards really help drive business outcomes we know that data and analytics has a broad enterprise purpose but most of the time the projects are really being done in a very siloed fashion and that creates a challenge we've talked about the elephant in the room in terms of the high rate of projects which don't end up being deployed and they shouldn't they should be having a bigger impact well putting that in kind of the business contact there's a lot of challenges to adoption of AI and the lack of a well defined strategy is certainly key but a piece of the puzzle is really how you are managing your data science talent to be able to help impact that strategy and that adoption so for example it's really important in terms of operationalizing AI that you're not doing just pilots and deploying single applications because that's really very different from fully operationalizing algorithms across an entire organization and you can imagine the greater impact that has and so by building this community of data scientist and building around standards then it can really help you get out of that individual pilot or a siloed mode and really start developing your business strategy so that you can operationalize AI and really get the most value out of it and that often means re-architecting your company's operating model so building and supporting this profession is a key part of that and as everybody is focused on their digital transformation it's increasingly important so well we talked about the importance of getting out of the silos you know that is really a key thing that we wanted to focus on and there's lots of different frameworks that we use and share with our clients in terms of doing that but really having that kind of outcome driven strategy on how you can change your business model to incorporate AI is really what's at the heart of this and it's what that data science profession certification supports and of course we all know a successful strategy really relies on execution so we're looking to make sure that we're engaging with leaders from all these other companies and members of the open group to really help craft that you know big visions and be able to help achieve those and the open group is a part of our strategy and we want to see that adopted across a lot more companies so that we can really support the transformation in the in the digital era so Steve I'm going to turn it back over to you thank you very much great as ever Maureen thank you very much for that for that overview and as you say this is not just certification for certification sake this is this is really addressing the the fundamental need and urgent need for digital transformation and having the right people in place to be able to to lead those journeys so very important stuff and so thank you very much Maureen please stay where you are we'll and if the the other speakers this morning who are still with us if you could join us for for the panel session and while you come back on we've a few of the speakers have mentioned that these programs create a community within their within their organization certainly for the for the accredited for the ACPs but perhaps even more important is is a community across those different organizations and you know across the whole industry and the profession so it's great that I'm able to announce to announce today something we've been figuring out how to do and working on for a little while but the open group is today announcing a data scientists a data science community of interest so what does that mean well it's open to both members and non-members of the open group and the goal is to basically if you have an interest in data science we're going to provide an open forum to discuss topics of interest to data scientists and with opportunities to learn from others a key part of all of these programs is is the mentorship and the guidance and you know very few challenges or obstacles are are unique to you or your organization so learning from others is is is a key part of it and we will host various data science workshops and events which will as as now the slide says it will provide additional learning and networking opportunities so we we plan to start those towards the end of this this quarter and into next so those of you with a data science interest join join Maureen and the and the others in the community and for now you can join the LinkedIn group and register your interest on our on our website opengroup.org slash community slash data science so please get involved so it's a great great to have that and we look forward to that to that growing and being being useful part of developing the profession