Big Data for Social Good: The developers' journey - Group two

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Watch this live chat with our second group of teams and participants from the #Hadoop4Good challenge to learn why they chose their projects, hear some of their challenges and delve deeper into the story behind their applications.

See all the participant projects and view our group one discussion.

Watch the winner announcement


0:00 do 0:04 donald was born 11 for my name is Courtney 0:07 ally with me i dnt man I have bad I'll 0:10 working will yeah alright 0:13 a data scientist and developers over the past couple of months 0:16 for our beneficial to the chance so 0:20 most maybe turn what's in your first time lost will 0:23 we want more first six Dementors and we'll talk a little bit about 0:27 what did you know I'll were seeking to accomplish with the 0:31 insights to write an application for a while and they also have an opportunity 0:35 at those books questions 0:36 so today we're going to do that with our sixth additional participants 0:40 and also talk a little bit about horrible words at war: 0:44 be announced or a one-week wall next 0:47 all went well so 0:51 that cool good this morning and Steve every you this is what is an opportunity 0:55 to really just talk a little bit or ball 0:57 what worked on on your process as well what's known y'all 1:00 when I think most part how all what was going on talk about our 1:04 was not was on also software suite 311 calls 1:08 sort they have over to you and more folks I'm 1:12 are you my needs not much im and be- submission-id: 1:17 was the usual analysis so York City 3-1 walk-ons 1:21 so it does reduce my so it can give no 1:25 I'm gonna be a professional been working in IT 1:28 your worldly mall already years now 1:31 more so than what was to be a and lately have been working with it big 8 1:36 and and I could never lose and so on and so or 1:39 hmm so will be disturbed before we continue 1:45 you have to do the directions most intently to what it did over 1:48 school everything just doing everything it by minutes I say and then with the 1:52 next person 1:52 yelping want to go through all your uses including what will take a little 1:57 what your process lol all we can turn it over to the next person for more and 2:01 we're all for any questions or 2:03 composed that it so I just need a little help with with tax 2:06 racial rigidly to share my screen to show what I did 2:10 incl degree 2:13 on its own the one I'm you see this is the urinalysis 2:17 PO Box 2831 because this is this submission 2:21 day %uh the primary and didn't do it which I will do little things that 2:26 yesterday nights and ringtones what the idea and why 2:29 there's so Benoit here was the hero 2:35 day going to the people's hands a little its be matched war between 2:38 literary analysis on the back and week 2:42 your you have one holds Gator from the website 2:46 you know because it would be too that was missing excoriated a2 2:51 sober critical at hand massage dear 2:54 going to who San Bernardino CA is a great big over 2:58 on the table back home remix now we realize very soon is based there isn't 3:03 at all 3:03 feature or hand there's bimbo on it listed 3:07 I also it will be monitored seem to be a work in progress 3:11 and thank so already dented was a bit with worry we will be able 3:15 I beat you must not be too I okay 3:19 a recent beating somebody let's go back to the basics 3:23 yen let's do something which is also had on 3:27 the intrinsic deductions or the interpretation would be our kids 3:31 the audience in this case being rebuke to be a commodities 3:35 so worried and it was a BTEC I'm going bill will 3:39 basic data analysis beating some reason aggregate 3:42 an up-and-down and we're sure some some beats no 3:45 this will be a risky job if you see this is gonna be a PM's 3:49 BMX Blackwall in there is a BBQ 3:52 are 3:54 reporter depiction of batt 3:56 0 graduated as your my children after 4:00 and we'll be here all staffing so be 4:03 film active completion aspect that I was playing pool man 4:07 so what I can do was a based on race day to 4:11 will be in bad meal and I we collect the data and we've agreed that backing 4:15 cheater 4:16 your biz do under it shows BRB 1908 4:20 gives basic some great b-day steven Powell summarized by silicon great you 4:24 know 4:24 my night with a column by the or by A&M 4:28 mambo the irangate and a few others but war 4:32 what we think it will be filed your concluding YouTube video 4:35 his apartment all like to see it being an to make sure I can improve things 4:39 you the for all your went back tones that actually will help me say 4:44 hey I didn't want this so way toward fixing 4:47 who I've been forced and Michael X 4:50 do we start with what about right to complain so you can see how the letter 4:55 there is this no lol 2008 a startup 4:59 it going to be in with all the way to the bottom and say okay it with your own 5:02 intense than much treatment and a triplet 91 bpm 5:07 mister their jobs get retailer by 5:10 back orbicular complete night any pics 5:13 not easy picture dude Matt Moore 5:16 we do it not going to be it's almost too Heidi 5:20 most would be incumbents are or 11 5:24 which 6 and biz is be done bleeding problems by 5:29 my mom what meant it was a big problems 5:32 summaries is all yours late in the month of January 5:36 am trial thrown them into order 5:40 repeal January be ready problems we can expect to be 5:44 because it's winter but this is a really basic scenario we could combine this 5:48 with let's say I want to see 5:50 no all I wanna seeee in aspic 5:53 mission as you can mine wall and you can see 5:56 a whole bill who played together in common as many as you 6:00 home you know what you're doing great concern is what was important 6:04 maybe we'll see or this 6:07 or looking beach now me for the exit rickety 6:10 you can ski conditions or be square abusive or 10 6:14 06 in mines it or so let's see how one min 6:17 on business all one minute that is were created in Step man 6:22 mind to night she was a different time 6:25 look toward the future is not you can be evolved humans 6:29 I'll something that has been being computer better 6:33 be analyzed and derived because Ben 6:37 I'll it's like a black box and its however basic discovery in 6:41 with the confusion someone who wants to build a dam to be 6:44 unit or the data he didn't lose it act 6:48 this is what would be done it not much you 6:51 medication to beat all that is aggregates 6:54 you can slice it visually using some basic radio and you can see the rain to 7:00 this tour been back since you and dad 7:04 will ban you can basically be able to save create I'm 7:07 buildings there be an actress 7:10 europeans yeah began ill get and there are you 7:14 war wife-beater at me and in important between the different departments 7:19 one big and let them go back do is from 7:22 and I'm 7:25 I'll as I had mentioned in here 7:29 there are some back into their own yes for instance a indirect to 7:32 I %um awesome the ER some personal training that is 7:36 there are quite a few call 07 New York City now why does need to be handled by 7:41 a computer 7:42 UT may be relevant between our where someone who is in the authorities 7:47 with two incredibly and the Indian if this is not 7:50 supposed to happen believe its human resources so they can 7:54 it was appropriate that's one use case 7:57 you have announced this service where you see I'll 8:01 if you can you to select group will you be doing general construction 8:05 you see something back and saying dude when East was quite 8:09 Ian 18 8:10 it leaks by courtesy but I'm and maybe the farmers their hand at least you 8:15 don't know each other and find out what's really going on 8:18 and that we big intensity okay 8:21 it would be neat what we're doing to address this problem maybe there is 8:24 something which might the ground level 8:26 where when it is done construction people remember you've got me so that's 8:30 very quiet mobile to me is 8:31 should be important sOooo the 8:35 bill done a tremendous termite with you and I was it was 8:38 not make a great mom X in person you 8:41 somebody in statuary since bill but maybe 8:45 inferences on will be included in the europeans 8:49 he had to be arms because even if I do or 8:52 advances to be more than glad it has Peninsula repair 8:57 variates and enough to be in there has to be some human intervention to be 9:01 sorry 9:01 with the youth and a new for you to be turned away with the decision will be 9:05 the judge 9:06 fish me gymnast in no way do you know any smoke Mac should work together in 9:12 warrior and solo and start and then 9:16 see it 18 inspections or and put 9:19 oh actually or wanna I will increase also who is always a mess the first time 9:24 someone's then you will 9:25 no good just last night and I think whole time slower 9:29 normal were all the questions I will try to answer but the way what you thought 9:33 of coral 9:34 workout rules for long as it was good or chrome or 9:37 are all want your sponsor or so 9:41 that is what we were all of books do you have questions I don't see any questions 9:45 young lot but your Google questions with in stock awards worth your call 9:50 and I'm ok they will do that 9:53 an a any vignette nyack 9:56 or chrome or chrome or 00 10:00 thank you very much for your overview on your participation will 10:03 that was impossible why don't we were or /url 10:07 my house was built up a little bit about some there all along with its not see 10:10 I'll worked all sports are still some 10:14 for a walk yet 10:17 I had a home yeah I'll 10:20 the nation we'll see how can I see campus so that he/she 10:24 the she stays I'll up by an estimated a 10:28 and a mess and going to jail and as though he had no accidents 10:33 a.m. our what happens if they want to go let me 10:37 that day and makes our and also I have lost your location that 10:41 we had on the experience says I'll 10:45 or at the beach and I'll 10:49 engineer has pop so the 10:52 our asses although one last time 10:56 all St baggio so he doesn't understand the whole 11:00 SAT back is is not enter on the latest 11:04 other in this is a a specific shell 11:07 less addresses I'll you 11:11 a step up miss who is a each 11:14 yeah 11:18 okay great so somewhat did you weren't forced are not processed 11:23 or something interesting findings but wait what rivals articles 11:27 or well I guess what another question I schools 11:30 well we'll see what you were able to quite a while 11:34 laying out below alright so something or quote 11:37 well we're worse or its deterrent now all souls 11:40 were also materials are all yeah he had a 11:45 yeah this is they use he was a 11:48 each that uses anyhow I'll saw the 11:51 her up in 11:55 in you had a real at is the leading you 11:58 yes it is %uh so I am well uses a 12:02 her but nothing is then yeah it was the 12:06 obligation is he isn't so 12:10 any vendor I'll year who is only 12:14 most let me use those is motivated 12:17 enter up Google them in a Vegas 12:21 so Media Indonesia 12:26 on that whom 12:28 was a 12:31 universe I'm and 12:35 also the I had is a 12:38 the murder I had a and it doesn't a 12:42 lead are you basically get I'll in a mood and the head as you can 12:50 be be here that well so that's really interesting it's funny quote for 12:55 personal reasons news network so what's nice is that what's new 12:58 not so much the overall goal hopes for when analyzing certainly no 13:03 what serious problems in preparation for our broken benefit from some moral 13:08 support 13:08 what was your partner or so I don't think I wouldn't want your 13:13 all send any questions or while soho 13:17 more no other or questions your what we were right I wasn't I hope you're 13:22 somewhat lazy 13:23 you well look what is too well what if I know I'm rocky open now 13:29 my app is called juneau juvenile is the Latin verb 13:33 which means to you a geneticist he and 13:37 for this amp and you know my intention was to assist 13:41 halsey officials public administrators 13:44 economic development officials community NGO leaders 13:48 with said Heene economic and social development goltz 13:53 a.m. the inspiration for this app was dead 13:57 i've lived most in my life in contrasting community each 14:02 I grew up in Rust Belt Region it was Ian 14:05 decades-long economic decline announce 14:09 for the past 20 years I've lived in Austin Texas 14:12 which is bien the national economic development success story 14:16 so through this up to this challenge 14:19 I wanted to focus on line economic and social development 14:23 in ask the question what are the characteristics that make 14:28 some community six each and others fail 14:32 so 14:34 kinda how I when the bell doing is she and in building the rapid yen some 14:39 I want to create meant reached 14:42 to make sure the all the a plunge in the community 14:46 ENT am this app is really committed 14:49 data mashup from I am self-rule 14:53 I'm open source I am Open Data 14:56 I am datasets from different federal agencies 15:00 the first one was the am Internal Revenue Service 15:03 he and the data don't use from their tracks population migrations 15:09 based on personal income tax returns 15:12 so I used net migration percent changes in Metairie 15:18 which heels a good overall me to reach to 15:21 indicates and perceived economic opportunity 15:25 or the lack thereof by tracking whether people are moving into the community 15:30 or fleeing away from the community just second Metrik 15:36 I used I'm is the combined homicide 15:40 in suicide death rates per capita from the national center of Health Statistics 15:46 I'm this is a good quality of life indicator 15:50 because it can say things about public safety 15:54 effectiveness of Community Mental Hills drawing in domestic violence 15:59 poverty and your I am 16:02 then I over ladies two metrics 16:06 with the Census Bureau's American Community Survey 16:09 to get the commute the characteristics 16:12 the community I'm for the and up 16:16 it looked into groups the first group 16:20 was book club 10 percent help communities 16:23 who had the lowest death rate in the highest population influx 16:28 people moving into the community the end 16:31 verses the bottom 10 percent I'll which had 16:34 the highest death rate each in the highest population 16:37 L close these were kind of the 16:40 floor and ceiling metrics for the United States 16:45 comparing these two groups I think class applied the community characteristics 16:50 into three categories: workforce 16:53 social economic in behavioral 16:56 in examine several characteristics 16:59 within these categories for Hadoop 17:03 I'm this was the first time I used it so in my exploratory data analysis 17:09 I look at the death reach by mister classification 17:12 this was either like I'll large urbane 17:15 three-inch Metro Tim suburban small towns 17:20 you rule he and I'm your walled communities in this 17:25 in exploratory data analysis appeared to have the highest death rates all these 17:30 groups 17:30 inist to me seem strange 17:34 so don't know you have to kind of go a little bit deeper 17:38 he aunt you know this the open data movement is still 17:42 in its infancy but one of the things 17:45 did you need to be aware of with these datasets 17:49 or the polity regulations the right mortality analysis data set 17:54 that I used only reported communities with Chan 17:58 or more %uh total homicides and suicides 18:03 so the question is: key against how much my analysis data 18:08 is Missy due to these regulations so the master mortality data set 18:13 is very large enhanced all the identifiers such 18:17 as community each stripped so I used to do 18:21 a big hard to find the total number of homicides and suicides reported 18:26 compared it with the analysis with my analysis data 18:31 i them 15 percent to be excluded 18:35 from my analysis if u'd 6 percent of those that are excluded from rural 18:39 communities 18:41 so up you know when you look at this analysis 18:45 I'm you have to I'm take a look 18:48 that 18:49 not wholly the analysis data sets itself 18:52 but also the missing day the missing data can you get a complete picture 18:57 I'm I used our studio 19:01 my five-year-old lamp lot to do the analysis 19:05 and when it was connected to IBM duping the class now 19:09 it was blazing fast so this is something I may have struggled with 19:13 I am if I had to do the analysis on my local machine 19:17 um in the kinda just kinda want to follow up on candy impact 19:23 and I'm goals I'm 19:27 did I see it through sure that you know asap he and I am 19:31 I hope that this prototype will help communities think about all 19:36 using big data just hit social 19:40 Economic Development Goals in execute the actions 19:44 with this now for example a community rank in the 40th percentile 19:49 can use the metric to the 50th percentile to set achievable goals 19:54 I'll for their economic and social development 19:58 as I mentioned earlier Austin is an economic development success story 20:03 but it was built upon thirty years executing 20:07 incremental achievable goals now I'm 20:11 I use the American Community Survey data which is used a lot in economic 20:16 development 20:17 in according to the Census Bureau this data is used to make decisions for 20:22 four hundred billion dollars and state in federal funds distributed the 20:27 communities each year 20:28 so this IBM big data for social good challenge 20:33 acutely demonstrates how communities can harness 20:37 Open Data to gain a competitive advantage 20:41 for their funding request 10 that sh 20:44 desks maia presentation think yes 20:48 she robo call all what or 20:51 it's really interesting still more are also taking 20:56 all while what want equality 20:59 all all 21:01 what a letter or the most locals 21:04 I'll all of war or of course 21:08 all are you interested also while well 21:12 okie Oracle's or well his agents all 21:16 alright all %uh what the court 21:20 all what I love this is a note so than I live in Chicago 21:27 I from on I Mayo a big data progress though 21:31 been using that up for some time and I was very curious to see our 21:35 in the cloud and that's what got interested main and this 21:38 competition I've bit before darts for many years 21:42 I court many years chicago is released 21:45 its our date as sup 3 open source publicly outlook though 21:51 %uh no I resource on DL internet 21:54 arm let me share my screen is possible of as a side of Chicago as 21:59 released a ate up or to look for many years now and it 22:03 releases allowed a s sex and the primary data set back to that sadly both 22:10 is be crimes stated said that's almost like this in years 22:14 baidoa and I just want to tell you that it's 22:18 $55 million carts it's not a small subset 22:22 a second a date so good they relax a bit a tux 22:25 up before best song so when this competition came over 22:30 of you know I just started thinking about how to build a very cohesive 22:35 I'll bet friend and sort this dataset and being a 22:40 precedent in the Chicagoland region I 22:43 I've started thinking as to what's useful sure they arrested in such 22:47 Chicago 22:48 from don't just the data that's habitable publicly by the city of 22:52 Chicago 22:53 so I decided to army note look at this CD 22:57 as a in as a as a composite of 23:00 out walks objects the smallest level of our government 23:05 be at so the city is divided into about 50 wats 23:09 and each wall art as its own are demanded at its own public schools as 23:13 hell 23:14 early days so basically the government of chicago is divided into waters 23:18 and each water as they are demand has a as I mentioned so 23:22 if you I you know the resources available in the city of Chicago and 23:26 let's do 23:27 arm you know from the perspective of the bed in I mean you want to know which 23:31 wide as 23:32 the most crimes at the best schools what the ratings of the school on things that 23:36 are 23:37 so this web application navigate Chicago 23:41 is babylon Lumix lee also done Lumix 23:44 is a is that bad you to 23:48 the services Ablett though flooded residents of Chicago so 23:52 what you're seeing on my screen is the Trent and dove 23:55 the age thirty WRC when you 23:59 under this web page so the force question would be like okay what's my 24:02 wall art right so you would click on this and I knew it would 24:06 go to this page are you know you can find out which wall art your 24:10 I'll basically belong to just for the 24:14 from sake of but this presentation let's assume that you are in water 24:18 want so so lets a go toward one 24:22 I'll 24:24 I you note so I get to know more about 24:28 this wall art so I can see the walk boundaries 24:31 and all my heart amanece and guess what you can also know what the latest salary 24:35 of the argument is 24:37 because this all public information at lambeau as part of Chicago data photo: 24:41 now I I can get information on what they all say 24:44 our for number index that this is regularly information Ababa 24:48 but as I said I want to know more about the water and i cant s 24:52 look at the wat map but I can look at the client's 24:55 right so I can look at like what I did Paul 24:59 5 crimes that happen in de Swart so 25:02 you can see like you know this criminal damage 25:06 arson and expect that so there's a pie chart but and also you have a public 25:10 lout 25:11 chart Object List Rd Paul she you 25:14 are you know crime types there are very applicable 25:17 to this water and you can't see in the last fifteen years this 25:21 been about close two hundred thousand crimes and then you can see 25:25 all the listings of the radius stop crime backus 25:29 I before I get this I want to mention back it's $55 million carts Ababa some 25:35 beach 25:35 kagabi decor and trust me you Contador descent the Microsoft Excel 25:40 they have it big side warning on BR 25:43 Chicago Addo said that you don't try do we know da blow dis into 25:48 XO but the beauty of our Lumix was I was 25:51 a burden or disabled exchange in less than 10 minutes 25:54 it took about a I wouldn't after download the $55 million to cart state 25:59 it was as if I took over and out but it according to basics in less than 10 26:03 minutes so that was 26:05 something fascinating about to blow mix for me and once 26:09 I started you know kind of categorizing 26:12 I'll you note the crime pipes tigar then I started 26:15 a you know categorizing by the wall arts and started developing 26:20 charts and you know this is what you see so what are the primary analysis my 26:25 application 26:26 does s I know kinda Group Inc 26:29 crimes up by water level and the types and things like that so 26:33 I can also show you the analysis I it do 26:36 up thing I mentioned is as a 26:38 added you want to know which one is the best schools what the 26:41 ratings for the schools are this is something I really struggled to find it 26:45 on because 26:46 I had to pull the data from Chicago Public Schools so it's not gonna fight 26:51 to get a couple good things but so I had to do a lot of thought you know and work 26:55 with best 26:55 so in this case high 80 26:58 in a big date of fraud if you elementary schools 27:01 in the wall art and then I it ran through the composite 27:06 you know score as well as select reading growth Matt 27:09 brought and the demographics up b-schools so this is all about 27:12 through the Chicago Public School so for example ward 1 27:16 as I okay bunch of elementary schools and you know 27:20 then you can see that you know the Hispanic person dates and 27:23 african-american person 27:24 H things like that then I started charging dog the 27:27 reading outside a composite growth how was it 27:30 dog you know I we've affect the scores 27:34 so I far back as the low-income percentage enrollment in the school Inc 27:38 resist Matt groat 27:40 is slower so similarly high date 27:43 from amino percent H enrollment and a school Inc resisted reading growth is 27:49 higher so 27:50 if you have cakes with low income per cent HD reading growth has been 27:54 higher so I similarly I big dog you know 27:57 format and after reading so for a particular 28:01 I'll walk so these this was so most 28:04 the analysis I did up but I took this one step I had like i cant you cant get 28:09 more information about I'll know this city of Chicago I 28:13 you got me running my neighbor be elected as today you can also see 28:17 I a salary and press me is not be number one now 28:20 ironing implying in the city of chicago is number two 28:23 I would like to find out about because through analysis I day 28:27 I got a bit of 50 µl and Bryce sauce at Grace 28:31 of 50,000 to cart analyzed through big sheets on big problem makes 28:35 and iPhone I and you can see there disappeared and 28:38 of least on makes the most as an employee of Chicago 28:42 they made makes up next time is is number two 28:46 of fifty I and Bryce are you can find 28:49 but if you want to see be crime rate at the city level 28:53 you know you can find out the charts update and desist 28:57 Press this is for fifteen years this is across the city of Chicago 29:01 and the ratings city though the number of crimes that happen in the city of 29:05 Chicago 29:06 by each crime type so we have about 5.5 million 29:09 I'll $55 million to arts FF are to Chicago 29:13 I can do it I education and now it says 29:16 I'll 29:18 I'll men this this is basically a arm 29:23 a kind of up putting the services are available as part of Chicago 29:29 I'll into the well 29:32 into the sport coat I'll study some think it's not working right now 29:36 a maps okayed a book the widgets working so you can find out 29:40 I love like the school's where they're located on things that are 29:44 and a provider budgets you can embed this API 29:47 you know and you can bend estates made it things I 29:50 if you are interested in public safety you have a link to 29:54 the AMBER Alert I'm sure everybody savell no clothes no subarctic 29:57 and you can look at the police stations available in the city of Chicago you can 30:01 go down 30:02 and you know you can find out the address of the PlayStation 30:06 and and let's say let's find out 30:09 s so you can find out the location you can do 30:12 you can google maps you can similarly do it the fire station 30:16 in a canoe can narrow it down this is all I've looked through the city of 30:19 Chicago 30:20 and you can do let public libraries you know similarly 30:24 embroidered I Public Library use 30:27 and then if you're a senior citizen if you want to know 30:31 I'll you know where their senior santa are far the city of Chicago 30:36 you can you know a get that information 30:40 and if you want to know more about help get out the vote 30:43 you know so it embedded into this website so you can look at the mental 30:47 health centers 30:48 on a map so for example all Salon de Almeida let's end our so you can 30:53 in a you can zoom and and tomorrow and things like that 30:57 I'm condom distribution sites that are available in city of Chicago 31:01 um this is related to health care and if you're interested in transportation dog 31:06 Absa 31:07 a success close love bites sharing system that's have lived in the city of 31:10 Chicago 31:11 it's a trying to locate a bike center thats nearby 31:15 you know you can do that I'd um its it as a but it doesn't bite standards 31:19 stations it's a big success in the city of Chicago 31:21 at their local metro us I'll CPA so it's all have lebow 31:26 in a single but orkut and you know it's 31:29 it's very usable you can learn a bar the city and the 31:33 mayor a crime rates education analysis 31:37 some you know you can't look good on the larger map um you know 31:41 on and thanks 31:47 I liked so its basically a 31:51 it's a usable web portal I use big sheets saddam 31:55 primarily the charts than I do get the data from Chicago Public Schools 31:59 arlen nom no one place 32:02 baby can now are we can see it and you can read about their 32:06 died in May might project H what it is as this said 32:10 away the Chicago data portal not sufficient to just sit by Joe 32:14 sex API San map 69 I could really use about bike that general public 32:19 of $54 million the dark side guard what did I use 32:22 I aggregated by primary types I can do with the water level 32:26 I not things like that so my view both 32:30 problem the chalice of Chicago and blesses public at lambeau 32:33 a and apps iight it to the wall arts and also get some education and I'll Isis 32:38 and its avalible in a link I and you can just click on it 32:42 anti comes up basically it's a very usable 32:45 amo by strangely I'll web application will start on Blu mix 32:50 thank you so much and the overall 32:54 I will all will be I'm just so impressed with the way it was revealed 32:58 is a longer and more well applicability all be 33:01 applications or you know cities across the country I think people 33:06 I'll be here for lot last week we had summoned joining 33:10 and talk about the spring flowers and that was really no also 33:13 very very interesting and this week we got a couple people talk about 33:16 once it is beset all operational tightenings 33:19 they thinkers also will consume also thank you very much for all your 33:24 and I don't know yet what fifteen minutes let's warm or cold was gonna 33:27 tell us what 33:28 that white you follow a whole lot would like to hear all about what it is and 33:33 I'm sure our viewers but to do so over TMR all 33:35 yes thank you very much gurney 33:39 in there yes our worker who was 33:42 bowel to the the City of London so I 33:46 we trade shoots a comparison criers 33:49 and the house prices tonight's to some demographic variables 33:53 and the our goal 33:55 it was to detect say there is a relation between 33:59 it defines 6 a.m. the and the 34:03 find level social scrapping with house prices 34:07 and the those the the mall that demographic variables 34:11 I we cool see their the specific here 34:14 what time period these between years 34:18 sue 2009 than the 20 min 34:21 and in order to do that too we we used to 34:25 some data sets provided by the 34:28 the City of London how we chose that because we've seen that 2010 34:33 those in other sets that were provided for the for to combat the issue was 34:38 about to be even with the City of London 34:41 and where babies the need to be so we all were always 34:45 now focusing all on them for our business 34:48 and many other things so out that we used for 34:53 the for different that sets in order to 34:56 to do this and the first one was about to D house prices 35:01 that that was the one provided that byee 35:04 the home but European Challenge competition 35:08 and the Wii also integrated that 35:11 with a crime summary that sets too so 35:14 that was about the summer the prize for in the City of London and one about you 35:19 just people 35:21 to is so the you can't seem to do 35:24 people believe that the population by the the 35:28 the Euro age and then other data sets the 35:33 mean the summary which contained it be 35:37 here them big summary of them a great 35:41 demographic and democratic through 35:45 related the them solu- red after 35:48 destroys who wielded everything into 35:52 the Lumix and then we had the 35:56 quite big piece of the meant that the quality and the 36:00 that the preparation the just before we 36:04 we proceed do with the prosti menya 36:07 and the queries because we found out that 36:10 and not so many the variables and 36:13 all the theme all the years that week 36:17 wanna 24 was on and 36:20 red after their to Wii U we started with the Big C pulled out the 36:24 iteration and in order to provide 36:29 the some statistical investigation we used the 36:33 IBM Watson the family pics and 36:37 so hour ago lou was to understand the howl 36:42 the you know who net at different 36:45 a less OA because at that was our level of detail 36:49 I'm could the 36:53 I mean Yahoo me we could we wanted to find a way to this caller 36:58 how these different variables who defected 37:02 the me you know the house prices 37:05 in the in order to do this we provided a it 37:09 single-level in this survey and analysis 37:12 and in or it should be as allies everything you know we used the 37:16 problems so we use that you frank that a different kind of service 37:21 and the if you will not like issue you 37:25 making you a brief overview both for 37:28 though Watson we the what we did and trying to share my screen Yahoo 37:34 so the busy career 37:37 I were our that the visa is the is based on different types 37:42 and that we can start from the mop 37:46 of the crimes so you could see 37:49 at the road dish or maps of London 37:52 I hooey which shows to 37:55 to focus on noam a small subset of 37:58 and less so 80s that just because that's a blow was not 38:02 that's a a great to with the be a 38:06 with the performance we've got all know with the full set of 38:10 a less waste a she can see each year the correlation between the crimes 38:16 and summoned the group that demographic variables which are 38:20 the percentage of people aged between 16 and 29 min the number of employees 38:25 working in each area 38:27 in the percentages of ever is on interest but those 38:30 absences a so the 38:33 these that the music is is is very interactive 38:37 and that you can miss select the 10 38:40 those the crimes that I'm did we chose to focus on 38:45 and that you can see Howell the 38:49 thing you know in the correlation between 38:53 the parables and the the crimes variety 38:57 during the years so 39:01 who we can see you my we also chose a different bands 39:06 and as you can see we who 39:10 which focuses on low-medium and the high levels 39:13 of crimes associates who me correlated should be use 39:17 different crimes and in order to you 39:22 to choose them we yeah 39:24 the me that these assumptions some choices 39:27 and the 39:31 mean that will should be dead search for house prices 39:35 and we correlated them to the number of dwellings 39:40 and the number of children in the in poverty 39:44 and for each obvious 39:47 al-issawi we can get more details 39:51 simply seeking them out on this link and that we've got 39:55 all different the two so all-news 39:59 different indicators also 40:03 through across the frontiers and of course you can also select 40:07 your specific al-issawi if you're 40:10 very focused on on local one or more 40:14 of beats ummmm 40:17 which are the challenges that we at to figure out 40:20 and ensure overcome I'll 40:23 the new that they were mostly about to D yumm 40:28 the the data quality process because 40:31 that sets aware the 40:34 quite big and the the contains many many different variables 40:39 we have the problems with the different time frames 40:43 and also about to the death is always 40:46 it the mutually fiction we had to find a compromise between at the amount of data 40:52 that we want it to 40:53 to these will entice and performances 40:57 I'm so that's missing 41:00 you know that's it what great 41:05 it's really i mean was a little bigger really how all 41:08 and also you can see what that's not in office will this fall 41:12 for people who are you considering a city are trying to understand why crimes 41:15 or or or what so while 41:17 withdrawals are so what Merkel thank you very much for 41:21 or online when we go ahead and go over to him not to go Cameron her you have 41:26 modest and 41:27 we couldn't stomach ache while minutes or so call wanna make sure 41:30 of another five minutes from now on to just talk about some 41:33 perspective at the conclusion yeah so over the warmer 41:38 thank you a high 41:42 I may be happy to meet with the cell competition 41:45 and a in a guy I would like bill official debut and they put 41:49 and each one has given it back and it but good topic that interests them 41:54 and and they have been the analysis and similarly even I have taken the 41:58 a they can issue a bit I'm facing right now 42:01 I actually I'm not much to student so I'm in my last semester 42:05 unlike a want a just so golfers job such 42:08 I'll be Lake Cook I'm ready to mobilize neel 42:12 community we just know that my office location so then you to 42:16 you thought I was asking I'll when inflation from my friends and the 42:19 tickets make up missed a book on eBay 42:21 its early anymore so they let us to distinguish 42:25 in Walpole you know ehrlich a community a bitch 42:28 the image the median a hopeful income as 42:31 I'll low Alexa ordered their lives are in average 42:34 and ask whether even David addition %uh 42:37 they need %uh to know they just go for a goes to book a manikin because 42:42 make I'll the if you're going for Richard community %uh that have been 42:45 more crimes because 42:46 though the crimes about it but the people who owns 42:49 more so you don't like it don't make sense but 42:53 there was no luvn concrete evidence is there so this 42:58 upon them prompted me to do the analysis so 43:01 %uh well reply to kar love the data set from the 43:05 Chicago Crime I admit that that I and 43:08 the median household income from the census Lomond a 43:11 and us being you get that much unused and 43:15 I'm the fighting with actually surprised me %uh Interlake 43:19 than a little slow this is where Lake though I 43:22 ok with it ok what I thought %uh what my friends thought and Lake 43:26 more but if we are going for ownership committee 43:29 lead-up that the median household income is more then 43:32 there and bill be a call on this site that though crime is a crime it 43:36 other less fluent output the but this 43:39 analysis like to go luvn I you open that analysis based on the Compu level 43:44 because I got the information 43:46 %uh the compliment information was more reliable so in this 43:50 no date though they couldn't I'll using the IBM 43:54 Nomex I use the you putting the large number of baidoa 43:57 and then you know that big business have I'll use make I have cuidado con 44:02 separately on database and I you it and it died 44:05 explode but they could she can do that now with the and a unity use the other 44:09 I'm not a big dollar bill with a complete and Allison 44:12 but in now using I'd be in the mix I was a little a 44:15 all in one in at this stage so newspapers 44:19 you for me i know im in on it go home 44:23 also accident but I got to know that we had to go away the facts not but %uh 44:28 surgeon 44:28 so good this other third will head a 44:32 everyone like you me are mune anyone know who is the lucky are 44:36 erlich in all to the %uh the public people ok let go 44:39 love one but the law would say they got they want if they are moving to a new 44:43 community 44:44 ok cool Big Ten love just will be the fact that 44:48 lay in on it the though 44:52 love median household income has more 44:55 then they can go look that they can as a No a few that that their 44:58 left go read that a relief grant because but now we have a concrete evidence for 45:03 so this may like I think it the ahead the public people 45:07 and the what other up from the Armitage bus but it might 45:10 attract more business mostly just like the education 45:13 order to star in touch me inside the lab spiegel so unique a distant at that more 45:18 business to the those particular region late lead the median household income 45:23 will be more so this may I think it might you know 45:26 research and I didn't we have put 20 people o.o 45:29 and don't mention and open you know I love them 45:33 um 00 going forward like girl 45:37 there is a more I'm going to do more research in the cell 45:41 area and a pillow I know I'm playing ball blue didn't quite a bit for the 45:45 stuff that you buy up getting into the 45:47 hope for America so I know all /url 45:50 a I think that the issues challenges to know during the daytime and you 45:54 i render in on a clone huh getting the more 45:59 our data 46:00 %uh done it which never let us know I miss updating the challenge in getting 46:04 nobody 46:05 a big lol %uh different 11 administered a goal for dog I'll 46:10 you know let go the neighborhood rhea ideo already love that some other like I 46:14 let a good in all the above that you a choice 46:19 or education my so fine yes at the condo level because the comp 11 and the crime 46:24 date lead 46:24 matching with each other and I did ima get more delivered a cup 46:29 so this was a challenge I face and though 46:32 well what I let the other 20 going to look at this a safety 46:35 I'll use the IBM who makes a so this my presentation 46:39 well thank you very much 128 sorted by chance that we had 46:44 what your mark Lowe kinda give your perspectives and their dear friend 46:47 but similar to that used to piss or chrome to rate them also 46:50 Armenian and Turkmen house prices things like this to help 46:53 to write some your your outcomes so our articles very much for your real 46:58 are you you all have in common stock wasn't me 47:01 I were what rather get some perspective here from a non-refundable the 47:05 scientists what what what what what you are seeing or 47:08 that he over there and get this done so much work with insights as well 47:12 do order still it all starts with social for non well what do you think about 47:16 this theme 47:17 what he doesn't want it to real-world activities 47:20 got it thank you very much first of all competitions for you an IBM 47:26 go just very interesting contest great job %uh 47:29 and folks up anything from Broadway Nyack on a 47:32 Marco and Mr at my age you guys already done fantastic job I'm 47:37 it touched a such a swap ate a global 47:41 %uh young population thinking about doing 47:44 goat attacks in the ATL very very interesting 47:47 outbidding yet score essay my company 47:51 I never to sign says as larach work for large customer 47:54 of majoring in back doing social good and how 47:58 issue argues can be deployed you guys are demonstrated very well 48:02 as a an update JH I want already 48:06 talk about a couple of points as observation out which can be 48:09 uniformed all of you I don't want to go by 48:11 one by one because up to in the Investor I'm about 48:15 they first is a y de Chelly first hurdle 48:19 and what is of most important idea about hurdle 48:23 is really mixing their data and for all you know really done a fantastic 48:28 a project are on saving them not mixing my keeper data so says 48:32 bringing them together and to individual edition or analytics 48:36 some of your home based on that point i picking it up from only one source and 48:41 being in the huddle it a very are looking you are done a great job but I 48:45 think that hard look at show 48:47 get more sturdy but yields case for being bored is being made by data 48:51 sources 48:52 bringing the structured and unstructured content I think that's what the whole 48:56 promisee is 48:57 unsightly and great you guys to expand your projects 49:00 beyond what data source and see how can you bring in all 49:03 my keeper S 060 can you bring it engines 49:06 up for doing that dat girl by ruff the second is the 49:10 hope for books I want to talk about the or part of it that 49:14 work is really you are trying to view or more informatics 49:18 secondary investing and but your school but what I rectory CDs 49:22 or just going of large what is the impact what is really to society 49:27 of the organization's I'll by the way out are you must be aware that 49:31 so should or are just so she came back organizations are 49:34 Tyler largest embroider alone in america if you just take the worldwide 49:38 population in the 49:39 embroil made Hz a very large so what you base that going 49:43 is going to impact on Friday are not just employment secretary 49:46 a medical so I have more I saw of you have missed on that point in time the 49:51 ongoing impact of your work but I can you host all 49:54 added that in future us all I would like to reiterate 49:57 each one of your presentations are your submissions 50:01 on the first to the quality of the idea now so I'll break or 50:05 all of you how great ideas okay the second if the implementation of the idea 50:11 as I mentioned to you that you base of the army strong mixing the data 50:14 he making use of herbal at the technology and its maximum benefit 50:19 so implementations of you know be lost on points 50:22 but I get all your 50:24 very good and the potential impact of what I guess 50:27 I literally and get you all are gopac team 50:30 I don't go to church me also sought walk impact you can bring to your ID onto 50:35 society 50:36 at our school got that white the deck or be back to you 50:40 and then thank you so very much more perspective and I think 50:44 you know just at the time in total content of that what we were 50:48 talking what will challenge we have what you guys have yet to use Orbitz for many 50:53 different things but when I was also so you still think the one who might be 50:56 able to take this forward and you're ready 50:58 and most the demonstrations we saw here those work on some demos 51:01 you could see how this is an all you know consumable all 51:05 for many people will take it in Japanese tall 51:08 solo you know to let them can still hear her most will meet you while 51:13 wow I know I'd love to see the whole and I are working 51:16 lucky wasn't more of that process 51:19 sort of consoles so are deliberately 51:22 I'll think everybody here we're doing and I will just encourage 51:26 alright you know anyone that wants to come join us next 51:29 Wednesday were all again feature all these fabulous submissions and all will 51:33 submit your 51:34 well our signatures and judges nobody else 51:37 worked hard are we well I'll take that 51:40 well as your next wednesday and talk about some more 51:43 for more titles so thank you all for your insight 51:47 or terminal are and we will talk soon 51:50 have been a factor warm 51:52 all that 51:55 do