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Best  Practices  Brief  

   

     

Four  Pillars  of  Business  Analytics    Improve  customer  experience  and  analytic  capabilities    with  Actuate  BIRT  Business  goals  for  applications  must  address  data,  people,  process  and  technology,  according    to  Gartner’s  Jamie  Popkin.  In  a  keynote  presentation  at  the  Gartner  Catalyst  Conference,  Popkin  called  this  framework  the  Four  Pillars  of  Business  Analytics.    

“Gartner  indicates  by  2015,  25%  of  analytic  capabilities  will  be  embedded  in  business  applications  and  designing  data  visualizations  for  web  and  mobile  apps  will  become    a  major  growth  engine  for  the  worldwide  Business  Intelligence  and  Analytics    Software  Market.”    

 –  Jamie  Popkin,  Managing  VP,  Gartner  

Transforming  analytic  data  into  usable  business  information  and  designing  compelling  data-­‐driven  customer-­‐facing  applications  remains  both  an  art  and  a  science,  and  a  clear  path  to  success  is  sometimes  hard  to  identify.  Inspired  by  Popkin’s  talk,  Actuate  believes  the  Four  Pillars  framework,  shown  in  Figure  1:  Gartner’s  Four  Pillars  of  Business  Analytics,  can  help  application  initiatives  succeed.  The  Four  Pillars  can  help  developers  and  IT  managers  ask  better  questions  –  and  get  better  answers  –  when  they  develop  business  analytics  applications.  An  emerging  set    of  design  principles,  inspired  by  the  Four  Pillars,  provides  a  blueprint  for  delivering  apps  that  inform,  connect,  and  motivate  end  users.  

This  best  practices  brief  describes  the  Four  Pillars  of  Business  Analytics  framework,  then  shows  how  you  can  employ  the  Four  Pillars  to  understand  your  application  needs  and  design  and  build  applications  that  inform,  connect  and  motivate  users.  The  brief  also  explains  why  Actuate’s  BIRT  platform  is  ideal  for  high-­‐user,  high-­‐volume  analytic  applications.    

 

   

Best  Practices  Brief  

 

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Best  Practices  Brief  

Understanding  the  Four  Pillars    

 

Figure  1:  Gartner’s  Four  Pillars  of  Business  Analytics    

1. Information  management  foundation  (Data)  The  Data  pillar  balances  governance  and  access  in  the  information-­‐driven  enterprise.  It  requires  connecting  to  disparate  data  sources  –  regardless  of  their  type  and  location  –  to  build  a  virtual  data  warehouse  that  is  easy  and  secure  to  consume  and  use.    

2. Organization  (People)  The  People  pillar  brings  IT  and  Business  communities  together  to  meet  shared  company  goals.    IT  people  require  a  visual,  programmatic  and  assembly  style  development  environment,  with  deep  integration  APIs  for  embedding  processes.  Business  people  need  secure  and  personalized  self-­‐service,  along  with  the  ability  to  embed  analytics  in  existing  applications  and  display  them  anywhere  –  including  wearable  and  mobile  devices  –  to  boost  usage.  For  IT  people,  engaging  business  groups  early  in  the  application  design  and  development  process  helps  to  drive  conversations  forward.    

   

 

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Best  Practices  Brief  

3. Fact-­‐based  decision  making  (Process)  The  Process  pillar  requires  having  the  right  information  at  the  right  time  to  make  better,  faster  decisions.  Because  different  roles  make  different  types  of  decisions,  it’s  important  to  leverage    the  same  data  to  support  a  variety  of  processes.  For  example,  operational  and  executive  users  require  dashboards;  customers  want  statements,  proposals  and  reports;  and  departments  need  performance  scorecards.  All  of  these  outputs  should  be  built  with  reusable  components  and  shared  across  groups  to  ensure  maximum  use.  

4. Appropriate  technology  platform  (Technology)  The  Technology  pillar  encompasses  development  and  deployment,  with  systems  that    break  down  silos  of  capability.  Integrated,  open,  extensible  tools  support  growth,  so  Actuate  embraces  standards-­‐based  content  development  environment  and  provides  a  flexible,    scalable  and  secure  automated  deployment  server  (BIRT  iHub).  This  combination  has  the  flexibility  to  deliver  data  from  any  source  and  embed  it  in  any  application.  

Another  way  to  understand  the  Four  Pillars  is  through  the  Business  Analytics  Framework  shown    in  Figure  2.  In  this  arrangement,  the  Data  pillar  is  the  Information  foundation  of  the  framework,    and  the  People,  Process,  and  Platform  (Technology)  pillars  are  broken  out  by  their  specific  needs  and  requirements.  It’s  important  to  note  in  Figure  2:  The  Business  Analytics  Framework  the  “Business  Models,  Business  Strategy  and  Enterprise  Metrics”  spans  all  of  the  pillars,    as  does  system  performance.      

 

Figure  2:  the  Business  Analytics  Framework  

 

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Best  Practices  Brief  

Addressing  Complexity  in  Customer  Facing  Applications  Once  you  understand  your  application  needs  in  the  context  of  the  Four  Pillars,  look  at  each  application  in  terms  of  users  and  data.  How  many  people  will  use  an  application,  and  how    much  personalized  data  each  user  will  require  from  the  app?  As  illustrated  in  Figure  3:  Customer-­‐Facing  Applications  –  Complexity  Comparison,  applications  with  the  most  users    and  the  highest  volume  of  personalized  data  per  user  are  typically  the  most  complex,  and  the  most  challenging  in  terms  of  design,  data  access,  management,  and  delivery.  These  applications  require  a  secure,  scalable  platform  –  Actuate  BIRT  –  to  meet  unique  challenges:  

• Take  a  customer-­‐centric  view,  in  order  to  focus  on  adding  value  

• Manage  increased  complexity  as  customers  and  data  are  added.  These  apps  –  particularly  those  used  by  financial  institutions’  customers  –  must  support  millions  of  users  who  aren’t  consistently  tech-­‐savvy  and  who  have  unique  information  requirements    

• Serve  enterprise  analytics  needs.  These  apps  must  move  beyond  departmental  scale  to  support  massive  amounts  of  data  and  users  

 

Figure  3:  Customer-­‐Facing  Applications  –  Complexity  Comparison  

   

 

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Best  Practices  Brief  

Applications  in  the  upper-­‐right  quadrant  –  those  with  large  numbers  of  users  and  high  volumes  of  data  per  user  –  deliver  more  value  to  users  when  they  employ  analytics.  Analytics  is  the  discipline  that  applies  logic  and  mathematics  to  data  to  provide  insights  that  help  people  make  better  decisions.  (Indeed,  analytics  is  synonymous  with  “fact-­‐based  decision-­‐making”  found  in  the  Process  pillar.)    

Four  types  of  analytics  –  descriptive,  diagnostic,  predictive,  and  prescriptive  –  are  illustrated    in  Figure  4:  Four  Types  of  Analytics.  Each  type  of  analytics  starts  with  data  and  poses  a  question,  and  each  requires  some  amount  of  human  input  to  arrive  at  a  decision.  In  the  case  of  decision  automation  –  a  subset  of  prescriptive  analytics  –  specific  actions  can  be  taken  based  on  data  without  human  input.    

Each  of  the  four  types  of  analytics  has  a  place  in  an  information-­‐driven  enterprise  and  in  your  analytics  strategy.  They  are  not  a  hierarchy;  prescriptive  analytics  are  not  better  than  predictive  analytics,  for  example,  and  each  type  of  analytics  is  applicable  to  specific  use  cases.    

 

Figure  4:  Four  Types  of  Analytics  

The  ways  users  consume  and  interact  with  analytics  vary.  Embedded  analytics,  dashboards    and  reports  are  common  methods  for  presenting  analytics  to  users.  Capabilities  such  as  queries,  data  visualizations  and  packaged  analytic  solutions  for  specific  business  problems  are  often  built  into  analytic  applications.  

   

 

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Best  Practices  Brief  

How  BIRT  iHub  Creates  Competitive  Advantage  Once  you  understand  the  Four  Pillars,  the  complexity  inherent  in  many  customer-­‐facing  applications,  and  the  ways  analytics  can  drive  application  usefulness,  the  challenges  inherent    in  application  design,  deployment  and  delivery  can  seem  daunting.  It  requires  a  powerful,  flexible  platform  that  can  take  data  from  multiple  sources  (including  social  media,  data  warehouses  and  enterprise  applications)  and  personalize  that  data  at  enterprise  scale.  

Actuate’s  BIRT  product  suite  meets  those  needs.  With  BIRT,  all  data  is  synthesized  through    an  advanced  designer,  called  BIRT  Designer  Pro,  and  delivered  through  an  enterprise-­‐ready  data  integration,  reporting,  and  business  analytics  server  called  BIRT  iHub.  In  Figure  5:  Features  and  Capabilities  of  BIRT  iHub  highlights  some  major  features  and  capabilities  of  BIRT.  Analytic  content  can  be  delivered  to  any  device  (leveraging  a  cloud-­‐friendly  architecture)  in  the  form    of  data  visualizations,  dashboards,  reports,  and  customer-­‐facing  applications.    

 Figure  5:  Features  and  Capabilities  of  BIRT  iHub  

 

 

 

 

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