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Me: Dony Riyanto, a veteran geeks
Code Pascal in 91’s, Assembly in 92’s, Learn
soldering in 97’s, and hunger for more
knowledges (2015)
vizualize.me/donyriyanto
slideshare.net/donyriyanto
donyriyanto@yahoo.com
 Why should I learn Internet? Why should I
have a mobile phone (hp)?
 Is PHP developer need to learn
NoSQL/NewSQL?
 Wikipedia source:
 Some other source:
 You need to flatten the world to 2D (rows
n cols) and create the relationship.
 They lough at you when your table un-
normal (no/wrong relationship)
 You’re commited to relationship
 A complex relationship with ‘normal’
table is not good for very big data, and
its badly slowing down
‘New’ types of data/model:
 Key/Value
 Document
 Graph/Relation
 Relational/Large Column
 Also Raw file (image, sound, log,
webpage, PDF, DNA structure, finger
print)
 MariaDB
 MongoDB
 Neo4J
 Redis
 VoltDB
 So much more
 “A bin replacement for MySQL”
 Maria is the little sister of My
 MariaDB is 100% compatible to
corresponding MySQL version, but with
many additional features:
› Support UUID natively
› Support big data and a lot faster
› Support flexible collumn and JSON like data,
natively
› etc
When should I use MariaDB?
 Stick to MySQL but need better solution
 Have existing project with mysql that
have database problem
 From the maker of PostgreSQL
 World fastest in-memory DB to date
 Why in-memory? They found that 70% of an
SQL query time is cosumed by disk operation,
 So they just come out with this great solution:
 A sql like database all in memory
 It is grid by its self. Its both Master and Slave
 SQL90 subset compatible
 Pretty much easier to understand when used to
have conventional so called “Rows and Cols”
 ‘Spike’ project
 When fast is critical (financial data,
command center application, medical,
etc)
 Read reviews and comparrisons
 Review key user’s review
 Learn by doing
 Imagine that you have data of all
banking transaction in the world or in
Indonesia,
 Imagine that you have access to
Facebook database and all the post
and profile of their users,
 Imagine that you can have access to all
SMS traffic in Indonesia,
 What would you do?
 Imagine that you have real time
agriculturar data of Indonesian’s Petani
(farmer),
 Imagine that you have real time satellite
and ground station’s data of Indonesian
farming field,
 Image that you have real time data of
national statistics (BPS),
 Image that you have realtime data of
commodities market,
 Can you help our farmer faster before they
crop?
 Telco
 Tax
 Banking
 Agriculture
 Industry
 Crime handling
 Corruption handling
 Dissaster handling
 So so much more
The so called 3 Vs
 Volume
 Variety
 Velocity
And more Vs:
 Virality, Viscosity
 Veracity, Value
Big data need ‘Big’ infrastructures:
 Database that can handle big data (combination of
RDBMS, data warehousing, NoSQL, big data)
 Hardware (server, storage, network) that can handle
big data
 Software:
› Data visualisation
› Analytical tools
› Machine learning tools
 Things to gather data (sensors network):
› IoT, smart things,
› Drone, ROV, HASP, satellite
 Brainware: Data Scientist (“is the most sexiest job in
coming years”)
 Is internet for you? Yess
 Developers (DBA, mobile dev, web dev,
backend dev, UI/UX designers, makers)
 Small Medium Enterprises (UMKM),
 Bioinformatics, ElectroInformatics,
GeoInformatics, Scientist, Statistical guy,
(how they quickly detect malaria epidemi in a particullar area just by tweet)
 Advertising industries, Manufacturing,
Farming and agriculture
(UCS ‘ads that see’, blumbangreksa)
Know your web visitor better.
 Collect all information for 3 months:
› Everyting: traffic, cookies, browser agent, IP, location,
average time per click/page/leave, click source, etc
› Challange them to login using socmed (facebook, twitter)
or tag
› Record their post and socmed actvities
› Analyze the words, profile back ground, ages,
communities
 Make a simple data visualization a.k.a dashboard.
 Can you see clearly now?
 Repeat the task with collaboration to partner’s web
site...
 Play video
 See: slideshare.net/donyriyanto

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No Sql Bigdata Drone

  • 1.
  • 2. Me: Dony Riyanto, a veteran geeks Code Pascal in 91’s, Assembly in 92’s, Learn soldering in 97’s, and hunger for more knowledges (2015) vizualize.me/donyriyanto slideshare.net/donyriyanto donyriyanto@yahoo.com
  • 3.  Why should I learn Internet? Why should I have a mobile phone (hp)?  Is PHP developer need to learn NoSQL/NewSQL?
  • 4.  Wikipedia source:  Some other source:
  • 5.  You need to flatten the world to 2D (rows n cols) and create the relationship.  They lough at you when your table un- normal (no/wrong relationship)  You’re commited to relationship  A complex relationship with ‘normal’ table is not good for very big data, and its badly slowing down
  • 6. ‘New’ types of data/model:  Key/Value  Document  Graph/Relation  Relational/Large Column  Also Raw file (image, sound, log, webpage, PDF, DNA structure, finger print)
  • 7.  MariaDB  MongoDB  Neo4J  Redis  VoltDB  So much more
  • 8.  “A bin replacement for MySQL”  Maria is the little sister of My  MariaDB is 100% compatible to corresponding MySQL version, but with many additional features: › Support UUID natively › Support big data and a lot faster › Support flexible collumn and JSON like data, natively › etc
  • 9. When should I use MariaDB?  Stick to MySQL but need better solution  Have existing project with mysql that have database problem
  • 10.  From the maker of PostgreSQL  World fastest in-memory DB to date  Why in-memory? They found that 70% of an SQL query time is cosumed by disk operation,  So they just come out with this great solution:  A sql like database all in memory  It is grid by its self. Its both Master and Slave  SQL90 subset compatible  Pretty much easier to understand when used to have conventional so called “Rows and Cols”
  • 11.  ‘Spike’ project  When fast is critical (financial data, command center application, medical, etc)
  • 12.  Read reviews and comparrisons  Review key user’s review  Learn by doing
  • 13.  Imagine that you have data of all banking transaction in the world or in Indonesia,  Imagine that you have access to Facebook database and all the post and profile of their users,  Imagine that you can have access to all SMS traffic in Indonesia,  What would you do?
  • 14.  Imagine that you have real time agriculturar data of Indonesian’s Petani (farmer),  Imagine that you have real time satellite and ground station’s data of Indonesian farming field,  Image that you have real time data of national statistics (BPS),  Image that you have realtime data of commodities market,  Can you help our farmer faster before they crop?
  • 15.  Telco  Tax  Banking  Agriculture  Industry  Crime handling  Corruption handling  Dissaster handling  So so much more
  • 16. The so called 3 Vs  Volume  Variety  Velocity And more Vs:  Virality, Viscosity  Veracity, Value
  • 17. Big data need ‘Big’ infrastructures:  Database that can handle big data (combination of RDBMS, data warehousing, NoSQL, big data)  Hardware (server, storage, network) that can handle big data  Software: › Data visualisation › Analytical tools › Machine learning tools  Things to gather data (sensors network): › IoT, smart things, › Drone, ROV, HASP, satellite  Brainware: Data Scientist (“is the most sexiest job in coming years”)
  • 18.  Is internet for you? Yess  Developers (DBA, mobile dev, web dev, backend dev, UI/UX designers, makers)  Small Medium Enterprises (UMKM),  Bioinformatics, ElectroInformatics, GeoInformatics, Scientist, Statistical guy, (how they quickly detect malaria epidemi in a particullar area just by tweet)  Advertising industries, Manufacturing, Farming and agriculture (UCS ‘ads that see’, blumbangreksa)
  • 19.
  • 20. Know your web visitor better.  Collect all information for 3 months: › Everyting: traffic, cookies, browser agent, IP, location, average time per click/page/leave, click source, etc › Challange them to login using socmed (facebook, twitter) or tag › Record their post and socmed actvities › Analyze the words, profile back ground, ages, communities  Make a simple data visualization a.k.a dashboard.  Can you see clearly now?  Repeat the task with collaboration to partner’s web site...
  • 21.  Play video  See: slideshare.net/donyriyanto