Panorama’s ExpertsTop BI Trends

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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.

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

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

8 – Too much data

• This is not news…

• But can you handle all this data? And how?

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

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

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

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

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

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.

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.

tpaz@panorama.com

Panorama Software

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