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1. Panorama’s Experts
Top BI Trends
for

2. Your Presenter of the Future
Tomer is a key leader in defining the
future of BI.
Tomer holds a B.Sc. in Engineering and an
MBA from Tel Aviv University.

4. 10 - BI is here, there and everywhere.
•Cloud
• More and more – even if concerns remain
• The economics are there
• Vendors will offer more incentives for cloud offerings
•Form factors
• More mobile – less desktop
• Augmented reality

5.  The 4 “V”s of Big Data
– Volume – Exceed the regular physical restrictions.
– Velocity – Smaller decision window and data
change rate.
– Variety – Many uncleansed formats make the
integration difficult.
– Veracity – Different data types that speak in
different languages.
9 - The rise of the three Vs

6. 8 – Too much data
• This is not news…
• But can you handle all this data? And how?

7. 7 - Automated Data Integration
 Data is accelerating
• More data sources
• More data
• More software to take advantage of it
 Other data sources you have are also accelerating in size and
complexity
• Customer interactions
• Operational data
• Regulatory requirements
 Blending the data is essential to derive the needed insights
 How many people do you have to manage all this? Will you
accelerate your hiring?
 The Answer – automated data ETL, handling, integration, and
publishing
• Without it – no IOT, no Big Data, no Insights, no value

8. 6 - Fading of the centralized on–premise
Data Warehouse
 The pain
• Agility  it is not
• Scalability tough
• Price  expensive to set up and operate
• Automation  what?
• Versatility of data types  so let’s make it into a table
 The cure
• Federated data and metadata handling
• Continuously add data sources of a variety of types
• Grow, change - static
• Automation!!! (or pay-up)
• Versatility of data types  so let’s use it

9. 5 – Death to slow data sources
• Remember our DTW:
• The pain
• …
• The cure
• Federated data and metadata handling
• …
• This only works if the data sources can react quickly.
• Luckily most are adapting to the new world.
• Main villains in this story –
• Hadoop - Great for storing data – awful retrieval
• Middlewares of all sorts
• The old DB technologies

10. 4 - Data exchanges
• We are taught to believe that what makes us competitive is our data
– THIS IS TRUE
• But – much of the data we would like to use is public
• Economic data
• Currencies, stocks and indexes
• KPIs
• Geo-materials
• Holidays
• The easier it is to add new data sources the more there is a need for
the ability to purchase / exchange these data sets

11. 3 - It is all about the insights
• Users are baffled by the amount of data thrown at them
• Trivial KPIs fail to deliver competitive edge
• Users really need Insights
• The next generation of KPIs
• Automatic
• Suggestive analytics
• Predictive
• Value driving

12. 2 – Data Scientists are NOT the answer
• The number of data scientists will NEVER grow by as much as the
data.
• The data complexity is such that soon they will all need to be
Einsteins…
• The idea of Big Data = Data Scientists will simply never add up.

13. 1 - AI of Business Intelligence data
• The solution – AI of Business Intelligence data
• Intelligent systems that learns and can suggest what you need to
know based on (for example):
• Your previous operations
• Your colleagues operations
• Collaboration history
• Data that has interesting attributes
• The data behavior
• The result – See what you need – not what you are used to.

14. tpaz@panorama.com
Panorama Software
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