Big Data 2.0

The first phase of big data (Big Data 1.0) was all about “getting it.” The more data we had, the better the targeting, measurement and insights capabilities we could attain.

The big data ecosystem has now reached a tipping point where the basic infrastructural capabilities for supporting big data challenges and opportunities are easily available. Now we are entering what we would call the next generation of big data — big data 2.0 — where the focus is on three key areas:

1. Speed: Data is growing at an exponential rate, and the ability to analyze it faster is more important than ever. Even the analytics providers are realizing the importance of speed and have built products that can analyze terabytes of data within seconds.

2. Data Quality: Data quality becomes more important with data growing at an exponential rate. The speed at which decisions are made has already reached a point where the human brain can’t keep up. This means that based on defined rules, data is cleansed and processed and decisions are made, all without any human intervention.

3. Applications: Big data has created so much excitement that everyone wants to use it, but the technical challenges prevents greater adoption. Applications help overcome this challenge by making it easy for everyone to benefit from big data.

Big data 2.0 is delivering advanced analytics and visualization tools that allow users (who aren't data scientists) to derive timely, meaningful insight from their data assets is the key to helping organization "see" the value from big data. These tools help to fill in the "last mile" of big data by presenting the complex relationships found within unstructured, structured, and even multi-structured big data in ways that make it easy to turn insights into action. The tools query and model the underlying data sources (in many cases, via the power of in-memory computing) before presenting a visual analysis of the data.

Such systems are particularly suitable for an exploratory style of analysis demanded by big data by virtue of their ability to recognize patterns and communicate data in a way that business users find more tangible and meaningful than picking through reams of tabular data.

The message is clear. We need to position ourselves carefully to avoid the fallout from the impending big data "hype hangover." Meanwhile, we need to look closely at how best to achieve real payback for our big data investments. The best way to do just that is to operationalize analytics by focusing on high-value use cases -- and use intuitive and engaging data visualization tools. That's a combination that provides a sensible way forward for next-generation big data 2.0, producing new ways to drive brand loyalty, improve profitability, and give customers the targeted, useful service they expect.

Future of Big Data 2.0

There are four undeniable trends accelerating the shift from Big Data 1.0 to 2.0.

1. The world has changed.We now live in the digital age. Everything is made up of bytes and pixels. Billions of devices, sensors, and apps create a constant flow of data. All things digital are now connected by the Internet of Everything (IoE).  People now use devices with hundreds of apps utilizing all of the sensor technology embedded in the device and creating new data and new patterns just waiting to be discovered.

2. The world will keep changing.The only thing we know to be constant is change.  Two elements drive unprecedented change. First, the entire world is in flux. We are in unchartered territory and no one really

knows what might happen next. Second, technology innovation is exploding on four vectors all at the same time. The internet connects everything, everywhere.  Mobile device adoption outpaces traditional desktop and laptop computing. The Cloud is taking over the corporate data center. And big data continues to explode. Change will no longer be measured by seasons or eras, it will happen constantly at a much faster pace than ever before.

3. Time is the new gold standard.As the speed of change continues to accelerate, time becomes the most valuable commodity.  You can’t make more of it, you can only move faster or use it more wisely. Everyone expects instant access and immediate response. Speed becomes an unfair advantage to those who possess it. Anyone who wants to survive in the new age must combine speed with intelligence in order to come out a winner.

4. Data is the new currency.You’ve heard it said that data is the new oil, but we say that data is the new currency. With the dropping cost of storage and new technology designed to capture, store, and analyze data at ever decreasing costs, companies are holding on to more data than ever before. Hidden in the data are the secrets to attracting more customers and keeping them, shaping their behavior, and minimizing enterprise risk at levels never before possible. The combination of massive amounts of data and new analytic algorithms creates a new global currency.

What do these trends mean for the shift from Big Data 1.0 to 2.0? They define the need for a generational shift in technology. They become the prescription for an accelerated platform that scales to handle massive amounts of data and increasing sophistication of analytics. It’s a chasm that can’t be crossed using old software technology forced into new hardware advances. The next-generation of analytics and big data platforms must be accessible to the masses, agile for immediate response, and accelerated at every point.

References

http://www.actian.com/about-us/blog/big-data-2-0-driving-big-shift/http://venturebeat.com/2013/12/28/big-data-2-0-the-next-generation-of-big-data/http://www.adexchanger.com/data-driven-thinking/big-data-2-0-valuing-connecting-protecting-and-embracing-it/http://www.actian.com/about-us/blog/big-data-2-0-happened-big-data-1-0/http://tdwi.org/Articles/2014/05/06/Seeing-Big-Data-is-Believing.aspx?Page=1http://www.customercentric.info/wp-content/uploads/2013/05/Big-Data-2-1000x750.jpg