Often people focus on techniques, tools and vendors when talking about advanced analytics! This single slide tries to introduce advanced analytics by simply showing how it complements conventional analytics which additional capabilities.

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Dimension Conventional Analytics Advanced Analytics
Data age Historical Historical, Live
Data sources Traditional such as ERP, EPM, CRM, … More, including social media and sensor
data
Data storage Data Warehouses Data Warehouses, Event Hubs, Data Lakes
Data processing Batch Batch, Streaming
Data format Structured data Structured, Semi-Structured and
Unstructured data
Data coverage Only your most critical data Possibly all of your available data
Data proximity In the data center In the data center, at the edge
Processes Well defined Exploratory
Skills Available Lacking
Hardware Mostly Specialized Mostly Commodity
Software Mostly Proprietary Mostly Open Source
Scalability Mostly Vertical Mostly Linear
Support Vendors Vendors, User Community
Time to insight Usually Longer Usually Shorter
Agility Schema-on-write Schema-on-read, Schema-on-write
Flexibility Static, Rules-based Dynamic, Patterns Identification
How Advanced Analytics complements Conventional Analytics?
By @SlimBaltagi