7 Key Drivers for the Big Data Market
I attended the Goldman Sachs Cloud Conference and participated on a panel focused on “Data: The New Competitive Advantage”. The panel covered a wide range of questions, but kicked off covering two basic questions:
“What is Big Data?” and “What are the drivers behind the Big Data market?”
While most definitions of Big Data focus on the new forms of unstructured data flowing through businesses with new levels of “volume, velocity, variety, and complexity”, I tend to answer the question using a simple equation:
Big Data = Transactions + Interactions + Observations
The following graphic illustrates what I mean:
ERP, SCM, CRM, and transactional Web applications are classic examples of systems processing Transactions. Highly structured data in these systems is typically stored in SQL databases.
Interactions are about how people and things interact with each other or with your business. Web Logs, User Click Streams, Social Interactions & Feeds, and User-Generated Content are classic places to find Interaction data.
Observational data tends to come from the “Internet of Things”. Sensors for heat, motion, pressure and RFID and GPS chips within such things as mobile devices, ATM machines, and even aircraft engines provide just some examples of “things” that output Observation data.
With that basic definition of Big Data as background, let’s answer the question:
What are the 7 Key Drivers Behind the Big Data Market?
- Opportunity to enable innovative new business models
- Potential for new insights that drive competitive advantage
- Data collected and stored continues to grow exponentially
- Data is increasingly everywhere and in many formats
- Traditional solutions are failing under new requirements
- Cost of data systems, as a percentage of IT spend, continues to grow
- Cost advantages of commodity hardware & open source software
There’s a new generation of data management technologies, such as Apache Hadoop, that are providing an innovative and cost effective foundation for the emerging landscape of Big Data processing and analytics solutions. Needless to say, I’m excited to see how this market will mature and grow over the coming years.
Being able to dovetail the classic world of Transactions with the new(er) worlds of Interactions and Observations in ways that drives more business, enhances productivity, or discovers new and lucrative business opportunities is why Big Data is important.
One promise of Big Data is that companies who get good at collecting, aggregating, refining, analyzing, and maximizing the value derived from Transactions, Interactions, and Observations will put themselves in a position to answer such questions as:
What are the behaviors that lead to the transaction?
And even more interestingly:
How can I better encourage those behaviors and grow my business?
So ask yourself, what’s your Big Data strategy?
~ Shaun Connolly