Big Data is a compounding phenomenon: as more data is produced each second, more ways to collect, analyze and monetize that data are unearthed.  Understanding Big Data has helped companies, brands and retailers, determine what to do next in order to make clients happy.  But countless challenges remain in managing that data, and the luster of Big Data as a savior to the world’s problems has lost its shine.

No longer a buzzword, Big Data is becoming more deeply integrated with the underlying infrastructure of systems that collect and control disparate data sets, leaving us at a loss with what to do with it all.  Big Data is full of promise, but those dreams won’t be realized until we determine the details of where to go from here.

A popular thread on Quora seeks to answer the question of what comes next, now that we’ve established the benefits of Big Data.  We’ve compiled five of the top answers, including responses from data visualization platform provider Tableau, an event organizer from DataWeek.co and a Senior Partner at Collective Intelligence Inc.

5 Visions of Big Data’s Successor

• One step, two components

Robert Morton, Senior Software Engineer at Tableau Software, states that the next step consists of two components which are data integration, and “big little data.”  Data Integration enables disparate data to be combined along their common facets while big little data is the tremendous proliferation of small data sets across the web.

“These two components come together in an interesting way. As with databases, data integration has been around for some time but has not evolved at the same pace as data management systems. Data integration is currently not suited to blending massive data sets with numerous small data sets, since a big bottleneck in data integration is in requiring human involvement to help identify the common facets between two otherwise unrelated data sets. This requires data cleaning, entity resolution and other challenging tasks for which the human brain is still a better pattern matching system than algorithms. Improving our algorithms to make this scalable is an important challenge,” Morton wrote.

• Monetization

Geoff Domoracki, Organizer of DataWeek.co, explains that as more data gets accumulated and understood, the next step is to monetize.

“[W]hat technology revolution will next help giant corporations advertise to / sell to consumers? I believe it will be technologies that help consumers better manage and leverage their existing personal info,” Domoracki pointed out.

He also added, “$1000 of data value per consumer X 100 million users = the next revolution.”

• Power in the hands of the user

The next big thing in Big Data according to Quora user Kaushik Pattamadai is making Big Data accessible at a user level.  Big Data could be available in the palm of our hands – on our smartphones or tablets – and facilitate using Data Analytics in our everyday lives.

“[T]here is a good amount of scope for voluntary modeling of personal or external data sets. Enabling the average user to forecast for their own benefit using their own personal assumptions. Data Analytics at the user level is the next big thing. Small applications by making available Big data is the next big thing. Think about using your own life history as a economic data set to identify trends, investments choice and how to adjust for the future,” Pattamadai stated.

• New philosophies and technologies

According to Chuck Russell, Sr. Partner Collective Intelligence Inc., the next thing after Big Data is not just one thing but a series of new things such as better tools for managing, sifting and analyzing high velocity, high volume, unstructured data; new philosophies and technologies for  data cleansing, and data integration and transformation; more sophisticated map:reduce engines like Hadoop; more User Oriented map:reduce engines abstracting the map:reduce and providing more robust query parse, optimize, execute options; and managing Big Data in motion a move so that the big data fire hose can be consumed and analyzed.

• Automated machine learning systems

The next big thing for Big Data will be automated machine learning systems that are able to deal with Big Data sets without human intervention.

“This will require intelligent systems that can guess feature spaces, kernels, and regularizers, running in parallel on thousands of nodes, with amazing graphical user interfaces and super-easy human computer interfaces,” Consultant Charles H. Martin explained.

Martin added that if he had the funding, that’s what he would build because his clients are constantly asking him for such a product.