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The three common Vs of Big Data: Volume, Velocity and Variety and Veracity—are a framework for understanding the elements and challenges of Big Data. You can cite as many factors as you like, but this alphabet soup all needs to add up to the ultimate V: Value. This value could be the ability to spot a key trend that was previously invisible, finding cost savings from looking at an initiative or line of business from a different logistical perspective, or detecting a point of contact with customers or clients where small improvements could yield significant gains. The evolution of data integration (getting all your legacy and real-time data into one place) and enterprise search (enabling you to query and actually make sense of data) together represent the keys to unlocking the fruits of big data.
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The Three Vs of Big Data Get You to the Fourth: Value
Presenter
Wes CaldwellChief Architect
Intelligent Software Solutions
Variety includes different types of data:Structured Unstructured Semi-structured All of the above
V1 - Variety of Data
Volume refers to the amount of data: Terabytes Records Transactions Tables, Files
V2 - Volume of Data
Velocity refers to the speed at which data is processed. Batch Real-Time Streams Near-time
V3 - Velocity of Data
3 V’s Converge
How can organizations benefit from all this data rather than being swamped by it or have their useful data disconnected and slumbering away on various databases or storage media?
The Big Data Challenge
Integration tools - get all your legacy and real-time data into one place
Search tools - enable you to query and actually make sense of data
Unlocking Big Data
The 4th V of Big Data is Value.TrendsSentimentPerspectivesRisks
Finding Value – the 4th V
The ability to spot a key trend that was previously invisible.
Finding cost savings from looking at an initiative or line of business from a different logistical perspective.
Detecting a point of contact with customers or clients where small improvements could yield significant gains.
Value Includes Factors Like
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