We spoke to 13 executives working on Big Data projects and asked them what they saw as the future for Big Data.
Dr. Greg Curtin, CEO and Founder, Civic Resource Group | Mikko Jarva, CTO Intelligent Data, Comptel Corporation |Matt Pfeil, CCO Co-Founder, DataStax |Dan Potter, CMO, Datawatch |Gena Rotstein, CEO and Founder, Dexterity Ventures, Inc. | Puneet Pandit, Founder and CEO, Glassbeam | Philip Rathle, VP Products, Neo Technology, Inc. | Guy Kol, Founder and V.P. R&D, NRGene | Hari Sankar, VP of Product Management, Oracle | Ray Kingman, CEO, Semcasting | Scott Sundvor, CTO, 6SensorLabs | Vikram Gaitonde, Vice President Products, Solix Technologies | Paul Kent, SVP Big Data, SAS | Margaret Roth, Co-Founder and CMO, Yet Analytics |
Here’s what they said:
- Big Data has really make it possible for people creating to do what’s never been done before. People are now able to do other things - they need to evolve their thinking. People shouldn’t be doing things a machine can do. People should be doing creative things.
- The possibilities are literally limitless to change business models and the benefits products and services can provide customers.
- I see it as being very central technology in every aspect of human existence. Every aspect of human behavior will evolve with the analysis of big data: weather, rockets, food, roads based on populations. We’ll have better tools which result in easier decisions.
- We’re building a charitable stock exchange to incent charities to do better. We will encourage tax and trade policy shifts with regards to cross-border giving. NAFTA agreements will be opened and reinforced for the nonprofit sector. This is not currently the case.
- Health, energy, transportation - are just a few of a huge range of opportunities for improvement.
- Predictive analytics give us the ability to anticipate needs. The more data you have the better predictions you can make. We’re going to have plenty of data with which to make predicitions.
- Analytics is the future of Big Data and will be for the foreseeable future.
- Fast data first. Unlike 2009, all data is not valuable. The thought of collecting everything (data) and then doing something with it afterward is outdated. Analyze and decide if any there are any actionable opportunities with the data before you decide to keep it. Only store what’s needed. Most data processing is real-time. We need to automate adoption to reduce data janitorial work. It’s necessary and tough to solve. Right now, 70 to 90% of the time is spent preparing the data versus generating insight.
- In five years years every relational database management systems (RDBMS) will be obsolete. We’ll have real-time data for everything. The rate at which this is happening leaves no doubt this is the direction we’re headed very quickly. Oracle is investing in big data solutions because they know it’s a threat to RDBMS. We collect, store and analyze the data making it easier for buyers to adopt.
- Changing business models and processes with the visualization of real-time data.
- Transitioning to cluster computing - analytics on a group of computers. We’re building around a Hadoop cluster to move all data into one system. A financial institution is able to store 10 years of transaction data across all systems rather than just three years’ worth. This will take two to 15 years depending on the company. We are rewriting algorithms to work on a cluster. Every algorithm is different. Few are meant to work across a cluster of computers. I don’t see a lot of companies scrapping what they have and starting over. They are transitioning.
- Two things:
- Data scientists crunching data and doing interesting reports. What happens to the insights in the report? We need to operationalize the analytics and decision making rather than leaving it up to people to implement what needs to happen.
- Use connections. All technology of the last five to 10 years has been using individual points of data versus looking at all data together. The Google search algorithm looks across relationships. It’s time for other enterprises to look across relationships. IoT may drive this as we will have 50 billion connected devices by 2020. Connect in the right way while everything is moving. The human brain has 68 billion neurons with 200 to 300 trillion connections between neurons. That’s where Big Data is going next.
- I think the opportunities are everywhere. I expect insights driven by big data to be an endless source of competitive advantage for every kind of organization. That’s really what makes big data the most exciting area to be involved in.
Where do you see the future for Big Data?