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Business Intelligence Analytics (History Timeline (WW2 - Enigma -…
Business Intelligence
Analytics
Benefits
General
Actionnable BI
Make decisions nd take actions based on data
Knowledge sharing
Same information adapted to each team
Break silos into the company
Proactivity
Automatic detection
Machine learning
Better insights
RCA - Automatic Diagnostic
Interlude - Video Machine learning
For broadpeak
New use cases
New teams
New budgets
Upsells
Increase footprint
More difficult to be swapped
Broadpeak
Where we stand
Our strategy / Vision
Split Ingestion/Processing & Storage
NBI scenario (no storage)
Feed 3rd party system
Analytics scenario (storage)
On-demand dashboarding
Analytics Professional Services
Advanced visualisation
Machine learning
Definition
Business intelligence uses technology to gather and analyze data, translate it into useful information and present it to support better business decision making
Dozens of definitions!
"Concepts and methods to improve business decision making by using fact-based support systems"
History
Timeline
WW2 - Enigma - Collect huge amount of data, detect trends, crack code
1956 - IBM's Hard Disk - Lot of storage - BI foundation
1958 - A Business Intelligence System - Data driven decision making
1970s - Companies put data into databases & create reports - But data into silos. One dimension, no cross talk.
One of the first real applications of BI came from Nielsen. Nielsen is the company which produces the Nielsen ratings, which gauge how many people are watching a particular TV show at any time.
1980s - Data Warehouses
Access and manage data in one place
Very technical
Required dedicated IT staff to build & run reports
Because of processing limitation, reports could take very long time to run (obsolete reports by the time they were finished)
DSS - Decision Support Systems - KPI reports
1990s - BI 1.0
More and more companies start to provide BI software
but very expensive solutions and not flexible
Companies focused on their core KPIs
Late 1990s - OLAP Cubes (OnLine Analytical Processing)
Multidimensionnal analytics
OLAP cubes allowed business users to query a database using English rather than a command line prompt
2000s - BI 2.0 and beyond
exponential increases in processing power
increased demand for more intuitive business intelligence solutions
increase in BI platforms’ flexibility and ease-of-use
new capability such as real-time processing through frameworks like Hadoop
BI platforms started to be offered as self-service analytics software
Interactive dahsboards
Interlude 1995 - Rise of personnal computer & Internet Users
Hadoop?
Competition
Conviva
NPAW
Cedexis
Typical Use Cases
Sales planning & Forecasts
Customer Behaviour
Capacity/Resource planning
Optimization
RT monitoring
Geo-spacial analysis
Churn prevention
Fraud detection
Interlude - Bytel & Qlikview
X% of content uses Y% of streaming bandwidth
Main actors
Gartner quadrant?
Dinosaurs
IBM/Cognos, SAP, Oracle
Leaders
MicroStrategy,Qlik,Tableau
Challengers
Kibana
