狠狠撸shows by User: NikoVuokko
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Wed, 11 Nov 2015 10:10:26 GMT狠狠撸Share feed for 狠狠撸shows by User: NikoVuokkoAnalytics in business
/slideshow/analytics-in-business/54988521
analyticsinbusiness-englishwebversion-151111101026-lva1-app6892 Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media.
The main messages of the lecture are:
- The purpose of analytics and of the data analyst is to solve business problems
- Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics.
- Deploying analytics is more dependent on humans than on technology
- Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets.
]]>
Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media.
The main messages of the lecture are:
- The purpose of analytics and of the data analyst is to solve business problems
- Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics.
- Deploying analytics is more dependent on humans than on technology
- Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets.
]]>
Wed, 11 Nov 2015 10:10:26 GMT/slideshow/analytics-in-business/54988521NikoVuokko@slideshare.net(NikoVuokko)Analytics in businessNikoVuokkoMaterial for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media.
The main messages of the lecture are:
- The purpose of analytics and of the data analyst is to solve business problems
- Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics.
- Deploying analytics is more dependent on humans than on technology
- Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets.
<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-englishwebversion-151111101026-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Material for the 26 Oct 2015 lecture I held for Aalto University business students. The lecture focuses on the high level topics in analytics and Big Data that are either central to the subject or just highly visible in the media.
The main messages of the lecture are:
- The purpose of analytics and of the data analyst is to solve business problems
- Big Data brings over some very special traits to doing analytics that don't exist when working working with smaller datasets. Understanding these traits is a must for successful analytics.
- Deploying analytics is more dependent on humans than on technology
- Data and analytics are nowadays significant assets to many companies. Therefore they need their own strategy and need to be managed just like any other business critical assets.
]]>
13317https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-englishwebversion-151111101026-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=boundspresentation000000http://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Drones in real use
/slideshow/drones-in-real-use/54947014
technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892 Where are drones actually used and how do they relate to the Internet of Things?
狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15.
The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.]]>
Where are drones actually used and how do they relate to the Internet of Things?
狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15.
The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.]]>
Tue, 10 Nov 2015 10:48:38 GMT/slideshow/drones-in-real-use/54947014NikoVuokko@slideshare.net(NikoVuokko)Drones in real useNikoVuokkoWhere are drones actually used and how do they relate to the Internet of Things?
狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15.
The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Where are drones actually used and how do they relate to the Internet of Things?
狠狠撸s to the presentations I held at Tech'15 Convention and Helsinki Tech Days '15.
The contents also focus on the data collected by drones and especially to one the most prominent drone use cases: inspection of public infrastructure.
]]>
11784https://cdn.slidesharecdn.com/ss_thumbnails/technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=boundspresentation000000http://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Analytiikka bisneksess盲
/slideshow/analytiikka-bisneksess/54433547
analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892 Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat:
- Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia
- Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle
- Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta
- Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa.
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Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat:
- Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia
- Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle
- Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta
- Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa.
]]>
Tue, 27 Oct 2015 14:35:16 GMT/slideshow/analytiikka-bisneksess/54433547NikoVuokko@slideshare.net(NikoVuokko)Analytiikka bisneksess盲NikoVuokkoMateriaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat:
- Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia
- Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle
- Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta
- Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa.
<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Materiaali 26.10.2015 pidetylle Aalto-yliopiston kauppakorkeakoulun analytiikan kurssille aiheesta "Analytiikka bisneksess盲". Luento k盲y korkealla tasolla l盲pi keskeisi盲 tai muuten vain pinnalla olevia aiheita analytiikasta ja Big Datasta. T盲rkeimpi盲 viestej盲 ovat:
- Analytiikan ja analyytikon teht盲v盲n盲 on ratkoa bisnesongelmia
- Big Data tuo analytiikan hyvin erityisi盲 ominaisuuksia, joita ei esiinny pienemm盲ss盲 mittakaavassa. N盲iden ominaisuuksien ymm盲rt盲minen on kriittist盲 analytiikan onnistumiselle
- Analytiikan k盲ytt枚枚notto on enemm盲n kiinni ihmisist盲 kuin teknologiasta
- Data ja analytiikka on nykyisin keskeinen omistuser盲 monille yrityksille. Siksi datalle ja analytiikalle pit盲盲 muodostaa oma strategiansa ja sit盲 hallita kuten mit盲 tahansa bisneskriittist盲 p盲盲omaa.
]]>
9576https://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=boundspresentationBlackhttp://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Sensor Data in Business
/slideshow/sensor-data-in-business/47704890
sensordata-fortuminternalevent2015-03-31-150ppien-150503160857-conversion-gate01 狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.]]>
狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.]]>
Sun, 03 May 2015 16:08:57 GMT/slideshow/sensor-data-in-business/47704890NikoVuokko@slideshare.net(NikoVuokko)Sensor Data in BusinessNikoVuokko狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sensordata-fortuminternalevent2015-03-31-150ppien-150503160857-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> 狠狠撸s for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.
]]>
4442https://cdn.slidesharecdn.com/ss_thumbnails/sensordata-fortuminternalevent2015-03-31-150ppien-150503160857-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=boundspresentationBlackhttp://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Sensoridatan ja liiketoiminnan tulevaisuus
/slideshow/sensoridatan-tulevaisuus-data-fortum-internal-event-20150331-slide-share-version/46691996
sensordata-fortuminternalevent2015-03-31-slideshareversion-150406134052-conversion-gate01 Finnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.
I will hopefully translate these into English at some point :)]]>
Finnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.
I will hopefully translate these into English at some point :)]]>
Mon, 06 Apr 2015 13:40:52 GMT/slideshow/sensoridatan-tulevaisuus-data-fortum-internal-event-20150331-slide-share-version/46691996NikoVuokko@slideshare.net(NikoVuokko)Sensoridatan ja liiketoiminnan tulevaisuusNikoVuokkoFinnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.
I will hopefully translate these into English at some point :)<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sensordata-fortuminternalevent2015-03-31-slideshareversion-150406134052-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Finnish slides for a presentation given at a Fortum's internal big data event. The presentation drafts out a journey from big data through sensor data in general into automated use of cutting edge sensors, drones and data technology in inspecting infrastructure.
I will hopefully translate these into English at some point :)
]]>
4341https://cdn.slidesharecdn.com/ss_thumbnails/sensordata-fortuminternalevent2015-03-31-slideshareversion-150406134052-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=boundspresentation000000http://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Introduction to Data Science
/slideshow/introduction-to-data-science-25391618/25391618
jyvskyl-lecture1share-130819144749-phpapp02 Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)]]>
Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)]]>
Mon, 19 Aug 2013 14:47:48 GMT/slideshow/introduction-to-data-science-25391618/25391618NikoVuokko@slideshare.net(NikoVuokko)Introduction to Data ScienceNikoVuokkoTwo hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jyvskyl-lecture1share-130819144749-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Two hour lecture I gave at the Jyv盲skyl盲 Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
]]>
187309https://cdn.slidesharecdn.com/ss_thumbnails/jyvskyl-lecture1share-130819144749-phpapp02-thumbnail.jpg?width=120&height=120&fit=boundspresentationWhitehttp://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Industrial Data Science
/slideshow/industrial-data-science/25391361
jyvskyl-lecture2share-130819143904-phpapp01 A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science.
See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)]]>
A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science.
See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)]]>
Mon, 19 Aug 2013 14:39:04 GMT/slideshow/industrial-data-science/25391361NikoVuokko@slideshare.net(NikoVuokko)Industrial Data ScienceNikoVuokkoA three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science.
See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jyvskyl-lecture2share-130819143904-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> A three hour lecture I gave at the Jyv盲skyl盲 Summer School. The talk goes through important details about the use of data science in real businesses. These include data deployment, data processing, practical issues with data solutions and arising trends in data science.
See also Part 1 of the lecture: Introduction Data Science. You can find it in my profile (click the face)
]]>
13525https://cdn.slidesharecdn.com/ss_thumbnails/jyvskyl-lecture2share-130819143904-phpapp01-thumbnail.jpg?width=120&height=120&fit=boundspresentationWhitehttp://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Metrics @ App Academy
/slideshow/metrics-22593266/22593266
metrics-130607040804-phpapp01 I've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck.
Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them.
AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.]]>
I've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck.
Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them.
AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.]]>
Fri, 07 Jun 2013 04:08:04 GMT/slideshow/metrics-22593266/22593266NikoVuokko@slideshare.net(NikoVuokko)Metrics @ App AcademyNikoVuokkoI've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck.
Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them.
AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/metrics-130607040804-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> I've been teaching AppCademy teams about metrics several times since 2013. This is the latest slide deck.
Main goal: dispel convenient default metrics, instead focus on your own business problems and derive metrics to solve them.
AppCademy is a 4-week accelerator camp run by AppCampus, a training program for Windows Phone dev teams.
]]>
5753https://cdn.slidesharecdn.com/ss_thumbnails/metrics-130607040804-phpapp01-thumbnail.jpg?width=120&height=120&fit=boundspresentationWhitehttp://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0Big Data Rampage
/NikoVuokko/big-data-rampage-2013-0513
bigdatarampage2013-05-13-130513050042-phpapp02 Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.]]>
Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.]]>
Mon, 13 May 2013 05:00:41 GMT/NikoVuokko/big-data-rampage-2013-0513NikoVuokko@slideshare.net(NikoVuokko)Big Data RampageNikoVuokkoPresentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.<img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bigdatarampage2013-05-13-130513050042-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Presentation for the 45 min. + QA talk I gave at HIIT seminar on 13 May 2013 for local data science researchers.
]]>
12332https://cdn.slidesharecdn.com/ss_thumbnails/bigdatarampage2013-05-13-130513050042-phpapp02-thumbnail.jpg?width=120&height=120&fit=boundspresentationBlackhttp://activitystrea.ms/schema/1.0/posthttp://activitystrea.ms/schema/1.0/posted0https://cdn.slidesharecdn.com/profile-photo-NikoVuokko-48x48.jpg?cb=1713247442All-around expert and public speaker in making data systems and data science solve real-world business problems, both conceptually and hands in the mud. I thrive being at the interface between business problem owners and technical capabilities and making sure that this communication works.
My experience ranges from designing large cloud-deployed real-time data platforms and predictive lifetime value algorithms to building from scratch software for automated hard rock drill positioning and crowd pattern analysis.
I hold an Olympic Bronze Medal in mathematics, PhD in data mining, and MSc in mathematics.
Specialties: data science, distributed systems, big data, digital marketinghttps://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-englishwebversion-151111101026-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=boundsslideshow/analytics-in-business/54988521Analytics in businesshttps://cdn.slidesharecdn.com/ss_thumbnails/technologyconvention-drones2015-10-07-150ppi-webversion-151110104838-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=boundsslideshow/drones-in-real-use/54947014Drones in real usehttps://cdn.slidesharecdn.com/ss_thumbnails/analyticsinbusiness-finnishwebversion-151027143516-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=boundsslideshow/analytiikka-bisneksess/54433547Analytiikka bisneksess盲