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Srinivasan Sundara Rajan

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Invisible Analytics and Power BI For Office 365

Unrelated to Telematics, recently we have seen the term ‘Invisible Analytics' being used as part of technology trends

Invisible Analytics: All the   hype  around   IoT  and  associated processing  will  not  be  of  much  use  if  the  massive  data  not  resulted  in  some  tangible  results end  users.  It  is  even  more  relevant  in  consumer scenarios .  What  is  the  use  of  an  high  end  car  with  telematics  engine  if  it is  not going to take  a  call  on  checking  the  break oil  leakage, much  before  the  vehicle ran  into some  trouble.  This  could be  just  one simple  example,  but  many  more  relevant  can  easily be foreseen.

Unrelated  to  Telematics, recently  we have  seen  the term  ‘Invisible Analytics'  being  used as part of  technology  trends  of  future.  As per  recent  Gartner  trends  for  2015,  Analytics will become deeply, but invisibly embedded everywhere." Big data remains an important enabler for this trend but the focus needs to shift to thinking about big questions and big answers first and big data second - the value is in the answers, not the data.  It  further  states  that,  Organizations need to manage how best to filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time.

The  above  point  leads  to the  fact  while  a  centralized  Analytics  solution  is  a  key  for  a holistic decision making  and predictions,  there  needs  to  be  a  Micro Analytics  engine  as part  of  each  device that  needs to  do a  similar  job may be  in  a  scaled  down  fashion.

Power BI Windows 10 &  Pervasive, Invisible Analytics : Power BI for Office 365 brings self-service BI solutions to everyday business users through the familiar tool they already use - Excel. There  are   several  sub  components  of  Power  BI  that  makes  a  fit  case  for  positioning  ‘Invisible Analytics'  for every  app.

Power BI Q&A  : Use natural language queries to find answers in your own data. Start with a question, and have fun traveling through your data refining or expanding your question, uncovering trust-worthy new information, zeroing in on details and zooming out for a broader view. You'll be delighted by the insights and discoveries you make.

Power BI Q&A presents your answers in the form of visualizations. As you type a question, Power BI Q&A picks the best visual to display your answer; and the visual changes dynamically as you modify the question.

Predictive Analytics : In Power View  which is part of  Power BI, you can now apply predictive forecasting, and hindcasting, when visualizing and exploring your data. Forecasting in Power View utilizes built-in predictive forecasting models using exponential smoothing to automatically detect seasonality in the data to provide forecast results from a series of data. Explore forecast results by adjusting the desired confidence interval or by adjusting outlier data to see how they affect results. You can also hindcast to see how Power View would have predicted the present and recent past based on older data.

The  above  two  features  are   typically  deal  with  the  Invisible  Analytics  mentioned  above,  there  are  other  features  like  rich  visualization,  charting  capabilities  do  exist  as  part of Power  BI.

One  current  issue  seems  to  be,   this  solution  is  tightly   integrated  with  Office  365  and hence  a connectivity  with  cloud  is  a  must ,  but  in  true  scenarios  for  consumer   the  invisible  analytics  may have to work locally to the  device.   At  present   I  could  not  see  APIs  for  Power  BI that  can be invoked  from a  Universal  App  for  Windows  10  devices.

However  considering  the  quite  a  few  progress  made on this  front  each  day,  this   possibility  is  quite  certain.  This   will  make  it  real the possibility  of  end  user  analytics,  natively  and  fully  localized  and  adjust  itself to the situations.

The Role Of Cloud Based Analytics: While  this invisible  analytics  at  the  device  level  is  useful  in  many  cases,  there  has  to  enough integration  with the  cloud  services to augment the analytics   to  beyond  what  can  be done  at  a  device  level.

For  example  :

  • Q&A guidance at the device level can connect to Cloud Services like IBM Bluemix Watson to handle the situations which cannot be locally handled
  • Predictive Analytics support can be extended to advanced algorithms from services like Windows Azure machine learning services.

In the  coming   days  a  tighter  integration  between  embedded  analytics  platforms  like Power BI  along  Universal  Device  operating  systems  like Windows  10  will  make  the  Invisible Analytics  a  real  thing and  available  for enterprises  and consumers.

More Stories By Srinivasan Sundara Rajan

Highly passionate about utilizing Digital Technologies to enable next generation enterprise. Believes in enterprise transformation through the Natives (Cloud Native & Mobile Native).