1. Idee “non convenzionali”
sulla “città intelligente”
ovvero: dietro ad ogni
frigorifero ci sta un uomo
Michele Vianello: Direttore Generale del VEGA
2. Sono il Direttore Generale
del VEGA (Il Parco
Scientifico e
Tecnologico di Venezia).
Sono un #nomadworker
Mi sono occupato e mi
occupo di WEB e di Social
Media,
di Città Intelligenti.
Mi trovate su Facebook, su
Twitter,
su Linkedin ecc. ecc.
Se volete seguirmi, leggete
il
mio blog:
http://www.michelecamp.it
p.s.
sono considerato uno
“starnutitore”
v. Seth Godin
vediamo se funziona anche con
voi....
3. “BUILD YOUR OWN SMART CITY”
Michele Vianello #nomadworker
http://www.michelecamp.it
4. “BUILD YOUR OWN SMART CITY”
vi narro storie
del genere
umano
Michele Vianello #nomadworker
http://www.michelecamp.it
6. Innovazioni
“disruptive”
Social Network
Michele Vianello #nomadworker
http://www.michelecamp.it
7. Innovazioni
“disruptive”
Social Network
the Big Data
Michele Vianello #nomadworker
http://www.michelecamp.it
8. Innovazioni
“disruptive”
Social Network Mobile
the Big Data
Michele Vianello #nomadworker
http://www.michelecamp.it
9. Innovazioni
“disruptive”
Social Network Mobile
the Big Data
Internet of Things
Michele Vianello #nomadworker
http://www.michelecamp.it
10. Innovazioni
“disruptive”
Social Network Mobile
the Big Data
Internet of Things
Cloud Computing
Michele Vianello #nomadworker
http://www.michelecamp.it
11. Un mondo interamente
connesso
Immaginate
Un’immensa nuvola
di dati
Michele Vianello #nomadworker
http://www.michelecamp.it
12. Persone che
condividono
conoscenze
Immaginate
Oggetti che
comunicano
Michele Vianello #nomadworker
http://www.michelecamp.it
17. “Sarà una città sradicata da qualsiasi punto definito
sulla superficie della terra, configurata dalle
limitazioni della connettività e dell’ampiezza di banda,
più che dall’accessibilità e dal valore di posizione
delle proprietà, ampiamente asincrona nel suo
funzionamento,
abitata da soggetti incorporei e frammentati che esistono
come collezioni di alias e di agenti elettronici.
I suoi luoghi saranno costruiti virtualmente dal
software e non più fisicamente da pietre e legno; questi
luoghi saranno collegati da legami logici al posto di porte,
passaggi e strade ”
Michele Vianello #nomadworker
http://www.michelecamp.it
20. OUT:
- FISICITA’
- CONTESTO/LUOGO
- ATOMI
- ORARI STABILITI
LA TECNOLOGIA DELLA
CONOSCENZA CI CONSENTE DI
DECONTESTUALIZZARE
Michele Vianello #nomadworker
http://www.michelecamp.it
21. OUT:
- FISICITA’
Lavoro
- CONTESTO/LUOGO
- ATOMI
- ORARI STABILITI
LA TECNOLOGIA DELLA
CONOSCENZA CI CONSENTE DI
DECONTESTUALIZZARE
Michele Vianello #nomadworker
http://www.michelecamp.it
24. giorno/attività
Il lavoro/La mobilità/Gli orari
Coworker-Nomadic Worker
versus
“La nostra vita di ogni giorno”
notte-dormire
Michele Vianello #nomadworker
http://www.michelecamp.it
slide di Michele Vianello
25. esto esto
t t
c on c on
giorno/attività
Il lavoro/La mobilità/Gli orari
Coworker-Nomadic Worker
versus
“La nostra vita di ogni giorno”
notte-dormire
esto to to
t te s t es
c on c on c on
Michele Vianello #nomadworker
http://www.michelecamp.it
slide di Michele Vianello
27. DECONTESTUALIZZAZIONE NEL LAVORO
E’ SCINDERE IL LUOGO DALL’ATTIVITA’,
DAL TEMPO
Michele Vianello #nomadworker
http://www.michelecamp.it
28. DECONTESTUALIZZAZIONE NEL LAVORO
E’ SCINDERE IL LUOGO DALL’ATTIVITA’,
DAL TEMPO
bla-
bla
bla-
bla- bla
bla
Michele Vianello #nomadworker
http://www.michelecamp.it
39. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
40. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
41. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
42. OPEN DATA
Surplus
cognitiv vengono postati
o 510.000
Fibra commenti
Digital
vengono caricati
Intelligenza
9800 600
Internet
Tweets filmati
Smart
cities
Social Cloud vengono scaricate
13000
Smart Grid
Wifi
apps
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
43. I city user devono acquisire la piena
consapevolezza delle potenzialità,
dei social per non sprecarle banalmente.
Michele Vianello #nomadworker
http://www.michelecamp.it
44. “Internet of things" permette agli oggetti di
comunicare tra di loro attraverso il web.
Ma, non dimentichiamolo mai, non è il frigorifero
che fa la spesa. Dietro a una lampadina
ci sta sempre un uomo che l’accende.
Michele Vianello #nomadworker
http://www.michelecamp.it
45. The Internet of Things Leads to the Internet
of Everything
Over 50% of Internet connections are things
Remote sensing of objects 2011: 15+ billion permanent, 50+ billion intermittent
and environment 2020: 30+ billion permanent, >200 billion intermittent
Building and New routes to
infrastructure market via
Audio $0.5 management intelligent objects
Cameras and microphones
widely deployed Everything
has a URL
2 GB flash $3
Content and services via
connected products
Augmented Situational decision
reality support
LTE
NFC
GPRS $7/Wi-Fi $3
7" 800 x 400 display $20
47. social network
BIT!!!! gioco
CONOSCENZA
BIT!!!!
attività istituzionali
attività lavorative
Michele Vianello #nomadworker
http://www.michelecamp.it
48. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart cominciamo a definire
cities
questa infinita quantità
Social Cloud
di dialoghi prodotti da tutti noi
Smart Grid
Wifi SURPLUS COGNITIVO
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
49. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
50. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
#traffico
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
51. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
“terminiamo” la privacy
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
52. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
53. OPEN DATA
Surplus
cognitiv la “privacy”
o è un
Fibra valore
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
54. OPEN DATA
Surplus
cognitiv la “privacy”
o è un
Fibra valore
Digital
Intelligenza
Internet
la
Smart
cities “condivisione”
è un
Social Cloud
valore
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
59. “Settori industriali in crisi come
l’energia e i trasporti stanno vivendo
un profondo cambiamento via via che
l’era digitale porta alla luce nuove
opportunità per accelerare la ricerca
e collaborare sulla base di alternative
sostenibili. Le vecchie verità su come
motivare e preservare il capitale
umano si stanno dimostrando
inadeguate rispetto ai nuovi modelli
di innovazione in base a cui le
organizzazioni si approvvigionavano
di idee -nonché delle competenze
necessarie per metterle in pratica-
attingendo ad un vasto bacino di
talenti.”
Michele Vianello #nomadworker
http://www.michelecamp.it
62. OPEN DATA
Surplus
cognitiv
o
Fibra
Digital
Intelligenza
Internet
Smart
cities
Social Cloud
Smart Grid
Wifi
Cloud
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
63. OPEN DATA
Surplus
cognitiv
o Social network
Fibra Internet of
things
Digital
Dati di pubblica
Intelligenza
Internet utilità
Smart
cities
Social Cloud “SOCIAL
Smart Grid
Wifi
Cloud CLOUD”
Social Network Michele Vianello #nomadworker
http://www.michelecamp.it
65. Big Data ... Fast Data … All Data
Mobile and
Communications
66. Big Data ... Fast Data … All Data
RFID, Meters
and Other OT
Mobile and
Communications
67. Big Data ... Fast Data … All Data
ball and
ey, base
ying hock ns.
I like pla mountai ica
climbing rth Amer
ations in No surpassed and
nt civiliz playing hockey, baseball
that
The ancie eeIring marvels they invented
gin
like
had en becaus
climbing e mouney also
tains.
d Greece ye s eelier. Th prove ica
Rome anThe ancient ar I like play in North Amer
out 700 civilizationsing hock
" to im
the "0" ab engineerinmean eering. surpabaseball and
en g marvels that ey, ssed
had "gold eir engin bing
red the clim ted
discove y aspect ofGreece because they inven s.
th mountain
rk
in New Yo They also
ever Rome andThe ancient civilizati. n
abou
the "0" ally t ented
inv700 years eelier ons in Nort
t America
s actu had engibuen ing marto improveh America
Pizza wa n food neer means vels g."
RFID, Meters
discovered thee"gold hettiengineerinthat surpassed
not ItaliaRom spag wa
everythe "0"and Gree
city. It isNot only that, t of their ce because they inve
aspec
food. abou. ted in s
in Chinat 700 yearNew YorkThey nted
Pizza was actually inven
inventedovered the "gol
disc earlier. also
Documents
American
every aspect but etti den mean"
city. It is not Italian food of their was to improve
Not only that, spagh
food.Pizza engineering.
was actuChina.
in ally invented in
invented
and Other OT
city. It is not Italia New York
food. Not only that n food but Ame
rican
, spaghetti was
invented in Chin
and Content
a.
Mobile and
Communications
68. Big Data ... Fast Data … All Data
ball and
ey, base
ying hock ns.
I like pla mountai ica
climbing rth Amer
ations in No surpassed and
nt civiliz playing hockey, baseball
that
The ancie eeIring marvels they invented
gin
like
had en becaus
climbing e mouney also
tains.
d Greece ye s eelier. Th prove ica
Rome anThe ancient ar I like play in North Amer
out 700 civilizationsing hock
" to im
the "0" ab engineerinmean eering. surpabaseball and
en g marvels that ey, ssed
had "gold eir engin bing
red the clim ted
discove y aspect ofGreece because they inven s.
th mountain
rk
in New Yo They also
ever Rome andThe ancient civilizati. n
abou
the "0" ally t ented
inv700 years eelier ons in Nort
t America
s actu had engibuen ing marto improveh America
Pizza wa n food neer means vels g."
RFID, Meters
discovered thee"gold hettiengineerinthat surpassed
not ItaliaRom spag wa
everythe "0"and Gree
city. It isNot only that, t of their ce because they inve
aspec
food. abou. ted in s
in Chinat 700 yearNew YorkThey nted
Pizza was actually inven
inventedovered the "gol
disc earlier. also
Documents
American
every aspect but etti den mean"
city. It is not Italian food of their was to improve
Not only that, spagh
food.Pizza engineering.
was actuChina.
in ally invented in
invented
and Other OT
city. It is not Italia New York
food. Not only that n food but Ame
rican
, spaghetti was
invented in Chin
and Content
a.
Internal Applications,
Mobile and Email, More
Communications
69. Big Data ... Fast Data … All Data
ball and
ey, base
ying hock ns.
I like pla mountai ica
climbing rth Amer
ations in No surpassed and
nt civiliz playing hockey, baseball
that
The ancie eeIring marvels they invented
gin
like
had en becaus
climbing e mouney also
tains.
d Greece ye s eelier. Th prove ica
Rome anThe ancient ar I like play in North Amer
out 700 civilizationsing hock
" to im
the "0" ab engineerinmean eering. surpabaseball and
en g marvels that ey, ssed
had "gold eir engin bing
red the clim ted
discove y aspect ofGreece because they inven s.
th mountain
rk
in New Yo They also
ever Rome andThe ancient civilizati. n
abou
the "0" ally t ented
inv700 years eelier ons in Nort
t America
s actu had engibuen ing marto improveh America
Pizza wa n food neer means vels g."
RFID, Meters
discovered thee"gold hettiengineerinthat surpassed
not ItaliaRom spag wa
everythe "0"and Gree
city. It isNot only that, t of their ce because they inve
aspec
food. abou. ted in s
in Chinat 700 yearNew YorkThey nted
Pizza was actually inven
inventedovered the "gol
disc earlier. also
Documents
American
every aspect but etti den mean"
city. It is not Italian food of their was to improve
Not only that, spagh
food.Pizza engineering.
was actuChina.
in ally invented in
invented
and Other OT
city. It is not Italia New York
food. Not only that n food but Ame
rican
, spaghetti was
invented in Chin
and Content
a.
Social Computing
Internal Applications,
Mobile and Email, More
Communications
70. Big Data ... Fast Data … All Data
ball and
ey, base
ying hock ns.
I like pla mountai ica
climbing rth Amer
ations in No surpassed and
nt civiliz playing hockey, baseball
that
The ancie eeIring marvels they invented
gin
like
had en becaus
climbing e mouney also
tains.
d Greece ye s eelier. Th prove ica
Rome anThe ancient ar I like play in North Amer
out 700 civilizationsing hock
" to im
the "0" ab engineerinmean eering. surpabaseball and
en g marvels that ey, ssed
had "gold eir engin bing
red the clim ted
discove y aspect ofGreece because they inven s.
th mountain
rk
in New Yo They also
ever Rome andThe ancient civilizati. n
abou
the "0" ally t ented
inv700 years eelier ons in Nort
t America
s actu had engibuen ing marto improveh America
Pizza wa n food neer means vels g."
RFID, Meters
discovered thee"gold hettiengineerinthat surpassed
not ItaliaRom spag wa
everythe "0"and Gree
city. It isNot only that, t of their ce because they inve
aspec
food. abou. ted in s
in Chinat 700 yearNew YorkThey nted
Pizza was actually inven
inventedovered the "gol
disc earlier. also
Documents
American
every aspect but etti den mean"
city. It is not Italian food of their was to improve
Not only that, spagh
food.Pizza engineering.
was actuChina.
in ally invented in
invented
and Other OT
city. It is not Italia New York
food. Not only that n food but Ame
rican
, spaghetti was
invented in Chin
and Content
a.
Social Computing B2B
Internal Applications,
Mobile and Email, More
Communications
71. Big Data ... Fast Data … All Data
ball and
ey, base
ying hock ns.
I like pla mountai ica
climbing rth Amer
ations in No surpassed and
nt civiliz playing hockey, baseball
that
The ancie eeIring marvels they invented
gin
like
had en becaus
climbing e mouney also
tains.
d Greece ye s eelier. Th prove ica
Rome anThe ancient ar I like play in North Amer
out 700 civilizationsing hock
" to im
the "0" ab engineerinmean eering. surpabaseball and
en g marvels that ey, ssed
had "gold eir engin bing
red the clim ted
discove y aspect ofGreece because they inven s.
th mountain
rk
in New Yo They also
ever Rome andThe ancient civilizati. n
abou
the "0" ally t ented
inv700 years eelier ons in Nort
t America
s actu had engibuen ing marto improveh America
Pizza wa n food neer means vels g."
RFID, Meters
discovered thee"gold hettiengineerinthat surpassed
not ItaliaRom spag wa
everythe "0"and Gree
city. It isNot only that, t of their ce because they inve
aspec
food. abou. ted in s
in Chinat 700 yearNew YorkThey nted
Pizza was actually inven
inventedovered the "gol
disc earlier. also
Documents
American
every aspect but etti den mean"
city. It is not Italian food of their was to improve
Not only that, spagh
food.Pizza engineering.
was actuChina.
in ally invented in
invented
and Other OT
city. It is not Italia New York
food. Not only that n food but Ame
rican
, spaghetti was
invented in Chin
and Content
a.
Cloud Computing
and Cloud Data
Social Computing B2B
Internal Applications,
Mobile and Email, More
Communications
72. 1-Liberare tutti i “data”,
2 - Visualizzare i “data”
3 - Storicizzare i “data”
4 - I “data” sono il
cervello della “città
narrante”
Michele Vianello #nomadworker
http://www.michelecamp.it
73. Naturalmente mi
interessano le vostre
idee, i vostri
suggerimenti, le vostre
critiche.
Scrivetemi sul blog,
su Facebook, su
il mio blog: http://www.michelecamp.it
Twitter.....
sono facilmente michele.vianello0@aliceeposta.it
reperibile in rete!!!! michele.vianello@vegapark.ve.it
@michelevianello #nomadworker
74. GRAZIE PER L’ATTENZIONE!!!!!
Naturalmente mi
interessano le vostre
idee, i vostri
suggerimenti, le vostre
critiche.
Scrivetemi sul blog,
su Facebook, su
il mio blog: http://www.michelecamp.it
Twitter.....
sono facilmente michele.vianello0@aliceeposta.it
reperibile in rete!!!! michele.vianello@vegapark.ve.it
@michelevianello #nomadworker
Notes de l'éditeur
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The Internet of Things (IoT) is a concept that describes how the Internet will expand as physical items such as consumer devices and physical assets are connected to the Internet. The vision and concept have existed for years; however, there has been an acceleration in the number and types of things that are being connected and in the technologies for identifying, sensing and communicating. This leads to the important trend of imbuing IT tools and practices into operational technology (OT), plus value can be gained when these newly smart and connected objects can be linked to traditional IT systems to inject purchases and other business transactions. They can also use this link to receive updated behavioral orders, adjusting the way those OT objects act to the situation and the objectives determined by the business strategy and IT systems. Key elements of the IoT include:\nEmbedded sensors: Sensors that detect and communicate changes (e.g., accelerometers, GPS, compasses, cameras) are being embedded not just in mobile devices but in an increasing number of places and objects. \nImage recognition: Image recognition technologies strive to identify objects, people, buildings, places, logos and anything else that has value to consumers and enterprises. Smartphones and tablets equipped with cameras have pushed this technology from mainly industrial applications to broad consumer and enterprise applications.\nNFC payment: NFC allows users to make payments by waving their mobile phone in front of a compatible reader. Once NFC is embedded in a critical mass of phones for payment, industries such as public transportation, airlines, retail and healthcare can explore other areas in which NFC technology can improve efficiency and customer service.\n
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Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n
Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n
Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n
Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n
Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n
Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n
Big data has such a vast size that it exceeds the capacity of traditional data management technologies; it requires the use of new or exotic technologies simply to manage the volume alone. But processing matters, too. A complex statistical model can make a 300 GB database seem bigger than a 110 TB database, even if both are running on multicore, distributed parallel processing platforms. Big data has quickly emerged as a significant challenge for IT leaders. The term only became popular in 2009. By February 2011, a Google search on "big data" yielded 2.9 million hits, and vendors now advertise their products as solutions to the big data challenge. Inquiries about big data from Gartner clients have risen sharply as well. \nMany new technologies are emerging, with the potential to be disruptive (e.g., in-memory DBMS), while others are hyped in the market and, although interesting, add no real value to the market (e.g., noSQL). Many new vendors are also emerging with this technology (see "Cool Vendors in Data Management and Integration, 2011" [G00211777]).\nIn addition to these, other new forces are coming into play. Analytics has become a major driving application for DW, with in-DBMS analytics (as delivered by Teradata and SAS, as well as others), use of MapReduce outside and inside the DBMS, and the use of self-service data marts, implemented in EMC/Greenplum and Teradata as a private cloud for internal implementation. \n