DBTB INT Andy Petrella

[Music] so I'm Andy petrella i'm the founder on the co-founder of the company name data fellows peasant belgium but also here in the US we are creating the link operation over here ah many things actually so i know the crowd is very interesting data so and since data Phyllis is very focusing on our new ways to manage data how to be able to to be productive with data science and thing like these i know this is varied a good crowd to speak to this this time i will talk about our work in genomics and interoperable solutions that are scalable and and dedicated specifically to genomics and health actually so it's really exciting because this is a research subject into into the lab fellows and we want to have more people involved also since there is driver one of the sponsors over here and a few other people that i know that very interesting the subject so again this is even now we're down in the indo indo to say on the population to to what we do yeah [Music] so it's so cool exciting because we are revisiting the way data science is done in enterprise specifically right so Dallas n has to be done efficiently but also with a productive philosophy in mind so it's no time it's not the time anymore where we can play with the data now we have to work with the data because enterprises are willing to very add up the way they do their business using the data that means that they have to be accurate and always on time when they I are using some information and since information comes from data having the right solutions to go from one side to the other is very important so we are focusing on this productivity and and the toolkit that we are providing is that we're building is is is a I mean it's a mix of several methodologies but also how to say shortcuts that allows data scientist to be to be very close to the to the runtime and the environment and also what is really cool internal is that we do a lot of graph analysis and NLP and a high in order to be able to do data science on there are signs that we want to also to to improve the efficiency of data scientist by removing a lot of burden like finding the right day like cleaning the right data and so on instead of repeating themselves so we are reducing this by proposing the right data directly so it's like a push notification like oh you should use this data now instead of this one because it's smoking [Music] from our talks some la the importance of driving data product towards service instead of charts or reports so this is mental demanding the main focus 1222 strangely it's certainly that we want to strengthen into indico system so this has to be re-entered by dairy scientists that now their work is a little bit changing they are part of the IT team instead of being part of their own team separated with from the rent time and i would say that but it's not new that week using on disability computing might be the right choice right now like we can see in different universities now it's also interesting to add enterprise being involved much much more in that area so to focus is it 822 TK Wilson data scientist is is like big data it doesn't mean much i would say that for my side i am very good and just facial for instance and i'm getting used to genomics thanks to exhibit or with my associate that has a lot of knowledge in bioinformatics and genomics so that means that is very good at that so we can call him a data scientist in genomics and myself I'm just special but the real important is to be able to understand the business to understand what you can do with the data we can what kind of data is available and then of course behind that you have to understand the right the mathematics that will be interesting just not trying to apply models but also understand what's going on behind ya a lot of the result of matures right now that is trying for me fooling the people that they can do data science using high-level abstractions which is good in some sense because it's it learned a lot to people that means that they are sensitive to what they can do they can somehow feel it but it's still important to understand what's going on behind because we are in the momentum where a lot of initiative are created art artists started everywhere to to move to understand how we can go further using the technology that we have available right now like spark or HDFS which is not that new but still for for universities for instance system it's unusual to work with this kind of iron man they were more used to hpc so yeah so understanding what's going on behind is very important and choosing a domain knowledge where you wear your you have a lot of interests important because then you can choose no what kind of a war you can do and you'd like to do [Music]