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Open Source Ecosystem Future of Enterprise IT


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Red Hat Forum 2016
Big Data and Analytic Landscape

Published in: Technology
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Open Source Ecosystem Future of Enterprise IT

  1. 1. Open  source  ecosystem  – Future   of  Enterprise  IT ASHNIK  Pte  Ltd.
  2. 2. 2 In the last 15 years 52% of the fortune 500 companies have disappeared Since 1995, 89%of those fortune 500 companies are gone 75 15 0 10 20 30 40 50 60 70 80 1995 2015 Avg.  Life  expectancy Avg.  Life  expectancy Did  you  know Source:
  3. 3. Leveraging  the  Power  of  SMAC  to  bring  Transformation 3 Transforming  Business Transforming  Applications  &   Solutions Transforming  Processes Transforming  IT  Infrastructure Transforming  Data  &  Interaction SMAC  Framework Dive  into  unfamiliarity  in  new  geographies  with  new  models  and  different   experiences  with  wider  reach  through  mobility  and  social  powered  by  cloud Applications  that  cater  to  rapidly  evolving  business  and  workforce  needs,  in   the  hands  of  right  users  powered  via  mobile  and  cloud   Simplified  and  harmonized  processes  across  the  organization  with  context   enmeshed  within  social  and  mobile     Agile  IT  infrastructure  that  caters  to  dynamic  business  needs    ,  on  demand   computing,  SaaS,  Paas  – Cloud  and  Analytics Improved  ways  of  using  data  for  interactions  to  improve  product  and  service   offerings  using  advanced  analytics  and  real  time  insights  from  mobile  and   social  
  4. 4. Big  Data  &  Analytics  Landscape
  5. 5. Enterprise  Data  Warehouse 5
  6. 6. Few  Observations 6 Ø Easy  point  to  start  with  Big  Data  initiative. Few  key  things  to  look  at   ü 2-­‐5  year  TCO  calculation  of  your  existing  data  including  cost  of  integrating  all  that  data. ü Analysis  of  what  is  the  data  which  can  be  used  for  analytics. ü Check  out  if  any  of  the  cold  data  needs  to  be  retained  as  that  would  drive  your  storage Few  factors  to  consider  to  decide  technologies ü If  analytics  to  be  done  on  Hub.  BI  tools  with  Big  Data  integration. ü Which  technology  to  choose  for  HUB  and  what  skills  would  be  required. ü Approach  of  data  integration  and  transformation  required  to  moved  forward  for  analytics.
  7. 7. Data  Hub 7
  8. 8. Few  Observations 8 Ø When  a  huge  and  increasing  volume  of  data  is  needed  for  business  analytics  with  flexible   requirements  of  latency.   Few  factors  to  consider  to  decide  technologies ü Data  Integration  tool  and  HUB  which  would  meet  the  enterprise  requirements. ü BI  tools  with  capabilities  of  integrating  with  Big  Data.
  9. 9. HUB  and  ODS 9
  10. 10. Few  Observations 10 Ø This  is  pattern  is  helpful  when  you  require  to  quickly  making  data  available  for  analytics  and   secondly  when  you  look  to  source  more  data  for  data  science   Few  key  things  to  look  at   ü When  planning  check  out  the  capability  of  analytics  available  in  your  BI  database  compared  to   what  value  you  want  to  derive  from  that  data. Few  factors  to  consider  to  decide  technologies ü Which  BI  DB  to  use.  If  you  one  already  that  can  be  explored  to  use  as  there  will  be  no  learning   curve. ü If  there  is  a  need  to  build  new  distributed  HUB  or  to  use  existing  data  platform. ü To  design  the  architecture  for  integration  of  data  and  when  to  land  the  blended  data.
  11. 11. Hub  -­‐ Spoke 11
  12. 12. Few  Observations 12 Ø This  is  pattern  is  helpful  when  you  want  to  provide  multiple  points  for  analytics. Ø When  planning  expansion  for  existing  big  data  platform  for  different  business  needs. Few  key  things  to  look  at   ü Who  owns  the  data? Few  factors  to  consider  to  decide  technologies ü What  to  use  to  build  the  HUB.   ü Selecting  right  tools  for  DI  and  Data  blending.
  13. 13. Connecting  Hadoop  and  EDB  Postgres  to  Shrink  Big  Data  Challenges. 13 CONFIDENTIAL ©  2011  EnterpriseDB.  All  rights  reserved. EDB  Postgres  FDW  helps  connecting  external  data  stores  to  Postgres  and  enable  applications  to   query  this  data  with  SQL  as  if  it  is  native  Postgres  data.   Helps  to  easily  combine  data  also  eliminates  complexity  and  risk  and  positions  Postgres  as  a   single,  federated  data  management  solution. See  more  at:­‐plus-­‐edb-­‐blog/ahsan-­‐hadi/connecting-­‐ hadoop-­‐and-­‐edb-­‐postgres-­‐shrink-­‐big-­‐data-­‐challenges#sthash.uovsLojx.dpuf
  14. 14. Open  Source  Technologies  – Business  Transformation 14 Data  Store Data   Integration Data   Enrichment Data   Accuracy Natural  Language  Processing  – Pyhton,R  ,  etc. Application   Delivary Platform CONFIDENTIAL  ©  2016    Ashnik  Pte  Ltd.  All  rights  reserved.
  15. 15. How  can  Ashnik  and  ITG  help! 15 We  partner  with  different  open  source  technologies q Solution  Consulting q Services  Consulting We  bring  the  experience  to  your  team q Database q Data  Modelling q Integration q Big  Data   Trainings End-­‐to-­‐end  Project  Engagements q Consulting q Services q Training CONFIDENTIAL  ©  2016    Ashnik  Pte  Ltd.  All  rights  reserved.
  16. 16. Ashnik  Technology  Partners 16 CONFIDENTIAL  ©  2016    Ashnik  Pte  Ltd.  All  rights  reserved.
  17. 17. 17 Stay  in  touch itgroupincorporated @itgroupinc ashnikbiz @ashnikbiz CONFIDENTIAL  ©  2016    Ashnik  Pte  Ltd.  All  rights  reserved.
  18. 18. Thank  You