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Y O U R    D A T A ,    N O    L I M I T S
Kent  Graziano,  Senior  Technical  Evangelist
Snowflake  Computing
Demystifying  Data  
Warehouse  as  a  Service  
(DWaaS)
@KentGraziano
2
My  Bio
•Senior  Technical  Evangelist,  Snowflake  Computing
•Oracle  ACE  Director  (DW/BI)
•OakTable
•Blogger  – The  Data  Warrior
•Certified  Data  Vault  Master  and  DV  2.0  Practitioner
•Former  Member:  Boulder  BI  Brain  Trust  (#BBBT)
•Member:  DAMA  Houston  &  DAMA  International
•Data  Architecture  and  Data  Warehouse  Specialist
•30+  years  in  IT
•25+  years  of  Oracle-­related  work
•20+  years  of  data  warehousing  experience
•Author  &  Co-­Author  of  a  bunch  of  books  (Amazon)
•Past-­President  of    ODTUG  and  Rocky  Mountain  Oracle  
User  Group  
3©  2016  Snowflake  Computing  Inc.  All  Rights  Reserved.
About  Snowflake  
Founders  and  leadership  
team  with  significant  
experience
Founded  in  
2012  by  industry  
veterans
Vision  :  A  world  with  
no  limits  on  data
First  data  warehouse,  
taking  full  advantage  
of  cloud  computing
4
Agenda
•Data  Challenges
•What  is  a  DWaaS?
•What  can  a  DWaaS do  for  me?
•Features  of  a  DWaaS
•Top  10  Features  of  Snowflake
Data  challenges  today
6
40 Zettabytes by 2020
Web ERP3rd party  apps Enterprise  apps IoTMobile
7
It’s not the data itself
it’s  how  you  take  full  advantage  of  the  insight  it  provides
Web ERP3rd party  apps Enterprise  apps IoTMobile
8
All  possible data All  possible actions
Most  firms  don’t  consistently  turn  data  into  
action
73% 29%
of  firms  
aspire  to  be  
data-­driven.
of  firms  are  
good  at  turning  
data  into  
action.
Source:  Forrester
Silos  &  Islands
Data  distributed  across  multiple  systems,  
difficult  to  bring  together
Silos  &  Islands
Silos  &  Islands
Complexity
Multiple  systems,  complex  pipelines,  
specialized  skills  and  resources  
Silos  &  Islands
Complexity
ComplexitySilos  &  Islands
Cost
Upfront  capital  costs,  multiple  copies  
of  data,  high  cost  to  store  data  
Silos  &  Islands Complexity
Cost
Silos  &  Islands CostComplexity
Delays
Data  users  forced  to  wait  for  access  
to  data  and  analytics
Silos  &  Islands CostComplexity
Delays
DelaysSilos  &  Islands CostComplexity
17
The  evolution  of  data  platforms
Data  warehouse  
&  platform  
software
Vertica,  
Greenplum,  
Paraccel,  Hadoop,
Redshift
Data  
warehouse  
appliance
Teradata
1990s 2000s 2010s
Cloud  DWaaS
Snowflake
1980s
Relational  
database
Oracle,  DB2,
SQL  Server
18
What  is  a  DWaaS?
•DW-­ Data  Warehouse
•Relational  database
•Uses  standard  SQL
•Optimized  for  fast  loads  and  analytic  queries
•aaS – As  a  Service
•Like  SaaS  (e.g.  SalesForce.com)
•No  infrastructure  set  up
•Minimal  to  no  administration
•Managed  for  you  by  the  vendor
•Pay  as  you  go,  for  what  you  use
19
Goals  of  DWaaS
•Make  your  life  easier
•So  you  can  load  and  use  your  data  faster
•Support  business
•Make  data  accessible  to  more  people
•Reduce  time  to  insights
•Handle  big  data  too!
•Schema-­less  ingestion
20
What  to  Expect  from  a  DWaaS
•It  should  support  standard  SQL  (natively)
•It  should  support  standard  ETL  &  BI  tools
•ODBC  or  JDBC  connectivity
•It  should  be  infinitly scalable  (cloud)
•Handle  huge  amounts  of  data
•Handle  large  number  of  concurrent  queries  without  
performance  degradation
•It  should  handle  flexible  schema  data  types
•No  sharding or  ETL  required
21
What  to  Expect  from  a  DWaaS
•It  should  be  secure
•Built  in  encryption?
•It  shoud be  stable
•Resiliancy and  availability
•It  should  be  easy  to  configure  and  manage
•It  should  provide  a  lower  TCO
•Cloud  scale  pricing
22
Common  Scenarios
Datamart &  data  silo  consolidation
Consolidate  legacy  datamarts to  eliminate  silos  and  
support  new  projects
Integrated  data  analytics
Directly  load  structured  +  semi-­structured  data  for  
reporting  &  analytics
Exploratory  &  ad  hoc  analytics
Direct  access  to  data  for  SQL  analysts  &  data  scientists  to  
explore  data,  identify  correlations,  build  &  test  models
1011
23
What’s possible
Up  to  200x  faster  reports  that  enable  analysts  to  make  
decisions  in  minutes  rather  than  days
Load  and  update  data  in  near  real  time  by  replacing  legacy  
data  warehouse  +  Hadoop  clusters
Developing  new  applications  that  provide  secure  (HIPPA)  access  
to  analytics  to  11,000+  pharmacies
24
Introducing  Snowflake
25
Snowflake:
Data  Warehouse  Built  for  the  Cloud
Data  Warehousing…
• SQL  relational  database
• Optimized  storage  &  processing
• Standard  connectivity  – BI,  ETL,  …
•Existing  SQL  skills  and  tools
•“Load  and  go”  ease  of  use
•Cloud-­based  elasticity  to  fit  any  scale
Data  
scientists
SQL  
users  &  
tools
…for  Everyone
26
Concurrency Simplicity
Fully  managed  with  a  
pay-­as-­you-­go  model.  
Works  on  any  data
Multiple  groups  access  
data  simultaneously  
with  no  performance  degradation
Multi  petabyte-­scale,  up  to  200x  faster  
performance
and  1/10th  the  cost
200x
The  Snowflake  difference
Performance
27©  2016   Snowflake   Computing   Inc. All  Rights  Reserved.
Diverse  Data Analytics  &  Apps
100%  Cloud
Scale  of  Data
Workload,  and  concurrency
Our Vision
Enterprise  apps          Corporate          Web
Mobile            Internet  of  things            3rd party
Data  exploration      BI  /  reporting
Predictive  analytics        Data-­driven  apps
Complete  SQL  
Database
Zero  
Management
©  2016   Snowflake   Computing   Inc. All  Rights  Reserved.
Data Warehouse built for the cloud
All  of  
your  Data
All  of  
your  Users
Pay  only  for  
what  you  use
28
The  Data  Warrior’s
Top  10  Cool  Things
About  Snowflake
(A  Data  Geeks  Guide  to  DWaaS)
29
#10  – Persistent  Result  Sets
•No  setup
•In  Query  History
•By  Query  ID
•24  Hours
•No  re-­execution
•No  Cost  for  Compute
30
#9  Connect  with  JDBC  &  ODBC
Data  Sources
Custom  &  Packaged  
Applications
ODBC WEB UIJDBC
Interfaces
Java
>_
Scripting
Reporting  &  
Analytics
Data  Modeling,  
Management  &  
Transformation
SDDM
OBIEE  &  ODI  too!
31
#8  -­ UNDROP
UNDROP  TABLE  <table  name>
UNDROP  SCHEMA  <schema  name>
UNDROP  DATABASE  <db name>
Part  of  Time  Travel  feature:  AWESOME!
32
#7  Fast  Clone  (Zero-­Copy)
•Instant  copy  of  table,  schema,  or  
database:
CREATE OR  REPLACE  
TABLE MyTable_V2
CLONE MyTable
• With  Time  Travel:
CREATE SCHEMA
mytestschema_clone_restore
CLONE testschema
BEFORE (TIMESTAMP =>
TO_TIMESTAMP(40*365*86400));;
33
#6  – JSON  Support  with  SQL
Apple 101.12 250 FIH-­2316
Pear 56.22 202 IHO-­6912
Orange 98.21 600 WHQ-­6090
{ "firstName": "John",
"lastName": "Smith",
"height_cm": 167.64,
"address": {
"streetAddress": "21 2nd Street",
"city": "New York",
"state": "NY",
"postalCode": "10021-3100"
},
"phoneNumbers": [
{ "type": "home", "number": "212 555-1234" },
{ "type": "office", "number": "646 555-4567" }
]
}
Structured data
(e.g. CSV)
Semi-structured data
(e.g. JSON, Avro, XML)
• Optimized storage
• Flexible schema - Native
• Relational processing
select  v:lastName::string as last_name
from  json_demo;;
34
#5  – Standard  SQL  w/Analytic  Functions
Complete SQL database
• Data  definition  language  (DDLs)
• Query  (SELECT)
• Updates,  inserts  and  deletes  (DML)
• Role  based  security
• Multi-­statement  transactions
select  Nation,  Customer,  Total
from  (select  
n.n_name Nation,
c.c_name Customer,
sum(o.o_totalprice)  Total,
rank()  over  (partition by  n.n_name
order by  sum(o.o_totalprice)  desc)
customer_rank
from  orders  o,
customer  c,
nation  n
where  o.o_custkey =  c.c_custkey
and c.c_nationkey =  n.n_nationkey
group  by  1,  2)
where  customer_rank <=  3
order  by  1,  customer_rank
35
Snowflake’s multi-cluster, shared data architecture
Centralized  storage
Instant,  automatic  scalability  &  elasticity
Service
Compute
Storage
#4  – Separation  of  Storage  &  Compute
36
#3  – Support  Multiple  Workloads
Scale  processing  horsepower  up  and down  on-­
the-­fly,  with  zero downtime  or  disruption
Multi-­cluster  “virtual  warehouse”  architecture  scales  
concurrent  users  &  workloads  without  contention
Run  loading  &  analytics  at  any  time,  concurrently,  to  
get  data  to  users  faster
Scale  compute  to  support  any  workload
Scale  concurrency  without  performance  impact
Accelerate  the  data  pipeline
37
#2 – Secure by Design with Automatic Encryption of Data!
Authentication
Embedded  
multi-­factor  authentication
Federated  authentication  
available
Access  control
Role-­based  access  
control  model
Granular  privileges  on  all  
objects  &  actions
Data  encryption
All  data  encrypted,  always,  
end-­to-­end
Encryption  keys  managed  
automatically
External  validation
Certified  against  enterprise-­
class  requirements  
HIPPA  Certified!
38
#1  -­ Automatic  Query  Optimization
•Fully  managed  with  no  knobs  or  tuning  required
•No  indexes,  distribution  keys,  partitioning,  vacuuming,…
•Zero  infrastructure  costs
•Zero  admin  costs
39
Data  Warehousing
as  a  Service  in  Action  Today
40
Cloud-­scale  data  warehouse
41
Steady  growth  in  data  processing
•Over  20  PB  loaded  to  date!
•Multiple  customers  with  >1PB  
•Multiple  customers  averaging  >1M  
jobs  /  week  
•>1PB  /  day  processed  
•Experiencing  4X  data  processing
growth  over  last  six  months
Jobs  /  day
42
Customer results
We  can  do  100  times  
more  queries  per  day,  
helping  us  give  our  
clients  richer  analysis  
far  more  rapidly.
— Balaji Rao
VP  Technology
Snowflake  is  faster,  
more  flexible,  and  
more  scalable  than  
the  alternatives  on  the  
market.  The  fact  that  
we  don’t  need  to  do  
any  configuration  or  tuning  
is  great  because  we  can  
focus  on  analyzing  data  
instead  of  on  managing  
and  tuning  
a  data  warehouse.
With  Snowflake,  
I’m  able  to  spin  up  
as  many  as  I  want  on  
demand  and  to  spin  
them  down  and  not  
pay  for  those  things  
that  I’m  not  using.
Snowflake  is  
awesomely  fast,  
allows  us  to  store  data  
at  a  low  cost and  deploy  
exactly  the  compute  
capacity  needed,  
and  does  all  of  that  without  
requiring  
tuning  or  tweaking.
— Craig  Lancaster
CTO
— Matt  Solnit
CTO
— Kurk Spendlove
Director  Engineering
43
Delivering  compelling  results
Simpler  data  pipeline
Replace  noSQL database  with  Snowflake  for  storing  &  
transforming  JSON  event  data Snowflake: 1.5  minutes
noSQL data  base:  
8  hours  to  prepare  data
Snowflake: 45  minutes
Data  warehouse  appliance:  
20+  hours
Faster  analytics
Replace  on-­premises  data  warehouse  with  Snowflake  
for  analytics  workload
Significantly  lower  cost
Improved  performance  while  adding  new  workloads-­-­at  
a  fraction  of  the  cost
Snowflake: added  2  new  workloads  for  $50K
Data  warehouse  appliance:  
$5M  +  to  expand
44
What  does  a  good  DWaaS enable?
Cost  effective  storage  and  analysis  of  GBs,  TBs,  or  even  PB’s
Lightning  fast  query  performance  
Continuous  data  loading  without  impacting  query  performance
Unlimited  user  concurrency
ODBC JDBC
Interfaces
Java
>_
Scripting
Full  SQL  relational  support  of  both  structured  and  
semi-­structured  data
Support  for  the  tools  and  languages  you  already  use
45
Making  Data  Warehousing  Great  Again!
46
As  easy  as  1-­2-­3!
Discover  the  performance,  concurrency,  
and  simplicity  of  Snowflake
1 Visit  Snowflake.net
2 Click  “Try  for  Free”
3 Sign  up  &  register
Snowflake  is  the  only  data  warehouse  built  for  the  cloud.  You  can  
automatically  scale  compute  up,  out,  or  down̶—independent   of  storage.  
Plus,  you  have  the  power  of  a  complete  SQL  database,  with  zero  
management,  that  can  grow  with  you  to  support  all  of  your  data  and  all  
of  your  users.  With  Snowflake  On  Demand™,  pay  only  for  what  you  use.  
Sign  up  and  receive
$400  worth  of  free
usage  for  30  days!
Available  on
Amazon.com
Introduction  to  Agile  Data  
Engineering
http://www.amazon.com/Bet
ter-­Data-­Modeling-­
Introduction-­Engineering-­
ebook/dp/B018BREV1C/
SHAMELESS  PLUG:
Kent Graziano
Snowflake Computing
Kent.graziano@snowflake.net
On  Twitter  @KentGraziano
More  info  at
http://snowflake.net
Visit  my  blog  at
http://kentgraziano.com
Contact  Information
YOUR  DATA,  NO  LIMITS
Thank  you

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Demystifying Data Warehouse as a Service (DWaaS)

  • 1. 1 Y O U R   D A T A ,   N O   L I M I T S Kent  Graziano,  Senior  Technical  Evangelist Snowflake  Computing Demystifying  Data   Warehouse  as  a  Service   (DWaaS) @KentGraziano
  • 2. 2 My  Bio •Senior  Technical  Evangelist,  Snowflake  Computing •Oracle  ACE  Director  (DW/BI) •OakTable •Blogger  – The  Data  Warrior •Certified  Data  Vault  Master  and  DV  2.0  Practitioner •Former  Member:  Boulder  BI  Brain  Trust  (#BBBT) •Member:  DAMA  Houston  &  DAMA  International •Data  Architecture  and  Data  Warehouse  Specialist •30+  years  in  IT •25+  years  of  Oracle-­related  work •20+  years  of  data  warehousing  experience •Author  &  Co-­Author  of  a  bunch  of  books  (Amazon) •Past-­President  of    ODTUG  and  Rocky  Mountain  Oracle   User  Group  
  • 3. 3©  2016  Snowflake  Computing  Inc.  All  Rights  Reserved. About  Snowflake   Founders  and  leadership   team  with  significant   experience Founded  in   2012  by  industry   veterans Vision  :  A  world  with   no  limits  on  data First  data  warehouse,   taking  full  advantage   of  cloud  computing
  • 4. 4 Agenda •Data  Challenges •What  is  a  DWaaS? •What  can  a  DWaaS do  for  me? •Features  of  a  DWaaS •Top  10  Features  of  Snowflake
  • 6. 6 40 Zettabytes by 2020 Web ERP3rd party  apps Enterprise  apps IoTMobile
  • 7. 7 It’s not the data itself it’s  how  you  take  full  advantage  of  the  insight  it  provides Web ERP3rd party  apps Enterprise  apps IoTMobile
  • 8. 8 All  possible data All  possible actions Most  firms  don’t  consistently  turn  data  into   action 73% 29% of  firms   aspire  to  be   data-­driven. of  firms  are   good  at  turning   data  into   action. Source:  Forrester
  • 9. Silos  &  Islands Data  distributed  across  multiple  systems,   difficult  to  bring  together
  • 10. Silos  &  Islands Silos  &  Islands
  • 11. Complexity Multiple  systems,  complex  pipelines,   specialized  skills  and  resources   Silos  &  Islands
  • 13. Cost Upfront  capital  costs,  multiple  copies   of  data,  high  cost  to  store  data   Silos  &  Islands Complexity
  • 14. Cost Silos  &  Islands CostComplexity
  • 15. Delays Data  users  forced  to  wait  for  access   to  data  and  analytics Silos  &  Islands CostComplexity
  • 17. 17 The  evolution  of  data  platforms Data  warehouse   &  platform   software Vertica,   Greenplum,   Paraccel,  Hadoop, Redshift Data   warehouse   appliance Teradata 1990s 2000s 2010s Cloud  DWaaS Snowflake 1980s Relational   database Oracle,  DB2, SQL  Server
  • 18. 18 What  is  a  DWaaS? •DW-­ Data  Warehouse •Relational  database •Uses  standard  SQL •Optimized  for  fast  loads  and  analytic  queries •aaS – As  a  Service •Like  SaaS  (e.g.  SalesForce.com) •No  infrastructure  set  up •Minimal  to  no  administration •Managed  for  you  by  the  vendor •Pay  as  you  go,  for  what  you  use
  • 19. 19 Goals  of  DWaaS •Make  your  life  easier •So  you  can  load  and  use  your  data  faster •Support  business •Make  data  accessible  to  more  people •Reduce  time  to  insights •Handle  big  data  too! •Schema-­less  ingestion
  • 20. 20 What  to  Expect  from  a  DWaaS •It  should  support  standard  SQL  (natively) •It  should  support  standard  ETL  &  BI  tools •ODBC  or  JDBC  connectivity •It  should  be  infinitly scalable  (cloud) •Handle  huge  amounts  of  data •Handle  large  number  of  concurrent  queries  without   performance  degradation •It  should  handle  flexible  schema  data  types •No  sharding or  ETL  required
  • 21. 21 What  to  Expect  from  a  DWaaS •It  should  be  secure •Built  in  encryption? •It  shoud be  stable •Resiliancy and  availability •It  should  be  easy  to  configure  and  manage •It  should  provide  a  lower  TCO •Cloud  scale  pricing
  • 22. 22 Common  Scenarios Datamart &  data  silo  consolidation Consolidate  legacy  datamarts to  eliminate  silos  and   support  new  projects Integrated  data  analytics Directly  load  structured  +  semi-­structured  data  for   reporting  &  analytics Exploratory  &  ad  hoc  analytics Direct  access  to  data  for  SQL  analysts  &  data  scientists  to   explore  data,  identify  correlations,  build  &  test  models 1011
  • 23. 23 What’s possible Up  to  200x  faster  reports  that  enable  analysts  to  make   decisions  in  minutes  rather  than  days Load  and  update  data  in  near  real  time  by  replacing  legacy   data  warehouse  +  Hadoop  clusters Developing  new  applications  that  provide  secure  (HIPPA)  access   to  analytics  to  11,000+  pharmacies
  • 25. 25 Snowflake: Data  Warehouse  Built  for  the  Cloud Data  Warehousing… • SQL  relational  database • Optimized  storage  &  processing • Standard  connectivity  – BI,  ETL,  … •Existing  SQL  skills  and  tools •“Load  and  go”  ease  of  use •Cloud-­based  elasticity  to  fit  any  scale Data   scientists SQL   users  &   tools …for  Everyone
  • 26. 26 Concurrency Simplicity Fully  managed  with  a   pay-­as-­you-­go  model.   Works  on  any  data Multiple  groups  access   data  simultaneously   with  no  performance  degradation Multi  petabyte-­scale,  up  to  200x  faster   performance and  1/10th  the  cost 200x The  Snowflake  difference Performance
  • 27. 27©  2016   Snowflake   Computing   Inc. All  Rights  Reserved. Diverse  Data Analytics  &  Apps 100%  Cloud Scale  of  Data Workload,  and  concurrency Our Vision Enterprise  apps          Corporate          Web Mobile            Internet  of  things            3rd party Data  exploration      BI  /  reporting Predictive  analytics        Data-­driven  apps Complete  SQL   Database Zero   Management ©  2016   Snowflake   Computing   Inc. All  Rights  Reserved. Data Warehouse built for the cloud All  of   your  Data All  of   your  Users Pay  only  for   what  you  use
  • 28. 28 The  Data  Warrior’s Top  10  Cool  Things About  Snowflake (A  Data  Geeks  Guide  to  DWaaS)
  • 29. 29 #10  – Persistent  Result  Sets •No  setup •In  Query  History •By  Query  ID •24  Hours •No  re-­execution •No  Cost  for  Compute
  • 30. 30 #9  Connect  with  JDBC  &  ODBC Data  Sources Custom  &  Packaged   Applications ODBC WEB UIJDBC Interfaces Java >_ Scripting Reporting  &   Analytics Data  Modeling,   Management  &   Transformation SDDM OBIEE  &  ODI  too!
  • 31. 31 #8  -­ UNDROP UNDROP  TABLE  <table  name> UNDROP  SCHEMA  <schema  name> UNDROP  DATABASE  <db name> Part  of  Time  Travel  feature:  AWESOME!
  • 32. 32 #7  Fast  Clone  (Zero-­Copy) •Instant  copy  of  table,  schema,  or   database: CREATE OR  REPLACE   TABLE MyTable_V2 CLONE MyTable • With  Time  Travel: CREATE SCHEMA mytestschema_clone_restore CLONE testschema BEFORE (TIMESTAMP => TO_TIMESTAMP(40*365*86400));;
  • 33. 33 #6  – JSON  Support  with  SQL Apple 101.12 250 FIH-­2316 Pear 56.22 202 IHO-­6912 Orange 98.21 600 WHQ-­6090 { "firstName": "John", "lastName": "Smith", "height_cm": 167.64, "address": { "streetAddress": "21 2nd Street", "city": "New York", "state": "NY", "postalCode": "10021-3100" }, "phoneNumbers": [ { "type": "home", "number": "212 555-1234" }, { "type": "office", "number": "646 555-4567" } ] } Structured data (e.g. CSV) Semi-structured data (e.g. JSON, Avro, XML) • Optimized storage • Flexible schema - Native • Relational processing select  v:lastName::string as last_name from  json_demo;;
  • 34. 34 #5  – Standard  SQL  w/Analytic  Functions Complete SQL database • Data  definition  language  (DDLs) • Query  (SELECT) • Updates,  inserts  and  deletes  (DML) • Role  based  security • Multi-­statement  transactions select  Nation,  Customer,  Total from  (select   n.n_name Nation, c.c_name Customer, sum(o.o_totalprice)  Total, rank()  over  (partition by  n.n_name order by  sum(o.o_totalprice)  desc) customer_rank from  orders  o, customer  c, nation  n where  o.o_custkey =  c.c_custkey and c.c_nationkey =  n.n_nationkey group  by  1,  2) where  customer_rank <=  3 order  by  1,  customer_rank
  • 35. 35 Snowflake’s multi-cluster, shared data architecture Centralized  storage Instant,  automatic  scalability  &  elasticity Service Compute Storage #4  – Separation  of  Storage  &  Compute
  • 36. 36 #3  – Support  Multiple  Workloads Scale  processing  horsepower  up  and down  on-­ the-­fly,  with  zero downtime  or  disruption Multi-­cluster  “virtual  warehouse”  architecture  scales   concurrent  users  &  workloads  without  contention Run  loading  &  analytics  at  any  time,  concurrently,  to   get  data  to  users  faster Scale  compute  to  support  any  workload Scale  concurrency  without  performance  impact Accelerate  the  data  pipeline
  • 37. 37 #2 – Secure by Design with Automatic Encryption of Data! Authentication Embedded   multi-­factor  authentication Federated  authentication   available Access  control Role-­based  access   control  model Granular  privileges  on  all   objects  &  actions Data  encryption All  data  encrypted,  always,   end-­to-­end Encryption  keys  managed   automatically External  validation Certified  against  enterprise-­ class  requirements   HIPPA  Certified!
  • 38. 38 #1  -­ Automatic  Query  Optimization •Fully  managed  with  no  knobs  or  tuning  required •No  indexes,  distribution  keys,  partitioning,  vacuuming,… •Zero  infrastructure  costs •Zero  admin  costs
  • 39. 39 Data  Warehousing as  a  Service  in  Action  Today
  • 41. 41 Steady  growth  in  data  processing •Over  20  PB  loaded  to  date! •Multiple  customers  with  >1PB   •Multiple  customers  averaging  >1M   jobs  /  week   •>1PB  /  day  processed   •Experiencing  4X  data  processing growth  over  last  six  months Jobs  /  day
  • 42. 42 Customer results We  can  do  100  times   more  queries  per  day,   helping  us  give  our   clients  richer  analysis   far  more  rapidly. — Balaji Rao VP  Technology Snowflake  is  faster,   more  flexible,  and   more  scalable  than   the  alternatives  on  the   market.  The  fact  that   we  don’t  need  to  do   any  configuration  or  tuning   is  great  because  we  can   focus  on  analyzing  data   instead  of  on  managing   and  tuning   a  data  warehouse. With  Snowflake,   I’m  able  to  spin  up   as  many  as  I  want  on   demand  and  to  spin   them  down  and  not   pay  for  those  things   that  I’m  not  using. Snowflake  is   awesomely  fast,   allows  us  to  store  data   at  a  low  cost and  deploy   exactly  the  compute   capacity  needed,   and  does  all  of  that  without   requiring   tuning  or  tweaking. — Craig  Lancaster CTO — Matt  Solnit CTO — Kurk Spendlove Director  Engineering
  • 43. 43 Delivering  compelling  results Simpler  data  pipeline Replace  noSQL database  with  Snowflake  for  storing  &   transforming  JSON  event  data Snowflake: 1.5  minutes noSQL data  base:   8  hours  to  prepare  data Snowflake: 45  minutes Data  warehouse  appliance:   20+  hours Faster  analytics Replace  on-­premises  data  warehouse  with  Snowflake   for  analytics  workload Significantly  lower  cost Improved  performance  while  adding  new  workloads-­-­at   a  fraction  of  the  cost Snowflake: added  2  new  workloads  for  $50K Data  warehouse  appliance:   $5M  +  to  expand
  • 44. 44 What  does  a  good  DWaaS enable? Cost  effective  storage  and  analysis  of  GBs,  TBs,  or  even  PB’s Lightning  fast  query  performance   Continuous  data  loading  without  impacting  query  performance Unlimited  user  concurrency ODBC JDBC Interfaces Java >_ Scripting Full  SQL  relational  support  of  both  structured  and   semi-­structured  data Support  for  the  tools  and  languages  you  already  use
  • 45. 45 Making  Data  Warehousing  Great  Again!
  • 46. 46 As  easy  as  1-­2-­3! Discover  the  performance,  concurrency,   and  simplicity  of  Snowflake 1 Visit  Snowflake.net 2 Click  “Try  for  Free” 3 Sign  up  &  register Snowflake  is  the  only  data  warehouse  built  for  the  cloud.  You  can   automatically  scale  compute  up,  out,  or  down̶—independent   of  storage.   Plus,  you  have  the  power  of  a  complete  SQL  database,  with  zero   management,  that  can  grow  with  you  to  support  all  of  your  data  and  all   of  your  users.  With  Snowflake  On  Demand™,  pay  only  for  what  you  use.   Sign  up  and  receive $400  worth  of  free usage  for  30  days!
  • 47. Available  on Amazon.com Introduction  to  Agile  Data   Engineering http://www.amazon.com/Bet ter-­Data-­Modeling-­ Introduction-­Engineering-­ ebook/dp/B018BREV1C/ SHAMELESS  PLUG:
  • 48. Kent Graziano Snowflake Computing Kent.graziano@snowflake.net On  Twitter  @KentGraziano More  info  at http://snowflake.net Visit  my  blog  at http://kentgraziano.com Contact  Information
  • 49. YOUR  DATA,  NO  LIMITS Thank  you