Does big data really matter? TechAmerica’s new survey says a resounding yes.
“We found there is a lot of potential for big data. The government could save up to 10% a year. 10% is no joke, that is about $380 billion a year,” said Jennifer Kerber.
Kerber is the President of the TechAmerica Foundation. She told Chris Dorobek on the DorobekINSIDER program that big data could mean big savings for the government especially in times of budget austerity.
“Budgets are tight especially with the government trying to cut $85 billion in sequestration cuts. So I think there is a significant focus on how big data can help reduce waste, fraud and abuse,” said Kerber.
Big Data Highlights
- We are just now at a point where the amount of data that’s coming in and the ability to control that data is allowing us to have “Smart Data.”
- The potential is enormous. It’s evolutionary. It’s almost like the internet. These days nobody asks if you are on the internet anymore, it’s just a way of life. Eventually we see that same evolution in big data. The data analytics and the decisions behind it will just become a away of life.
- The ability to do some of this analysis in real-time allows you to better deliver services to customers. Public safety officers can now us big data to reduce crime and target criminal hotspots. One of the most exciting areas is healthcare. You can do targeted searches in cancer research for example.
Managing Big Data
“For a long time we have accepted the fact that we have to make decisions with incomplete information. And while we’re never going to have all the information all the time, the current big data environment has the ability to have as much information as you need for real-time, quick decision making,” said Kerber. “That goes back to delivering the right quality of care.We are no longer fighting on the back half. Making decisions before things happen.”
Concerns with Big Data?
- Justifying the initial investment can be hard for some agencies.
- Privacy.
- Definition of big data itself. We’ve worked hard to on the definition of big data because a lot of things that have big in front of it, aren’t perceived as good. Like “big oil,” or “big brother.”
- Data silos are also a big concern. Right now a bunch of smart people are working to make all the data able to talk to each other.
*All graphs and images are owned by the TechAmerica Foundation and SAP.
More Big Data Resources:
- Come listen to big data experts in our webinar next Thursday 3.21st at 2pm ET. Register for the free event here.
- GovLoop and Oracle teamed up to produce a guide: Big Data in Government.
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There’s a huge gap in relying on big data that is not presently getting addressed. I’ve spent the last 5 years working for SAP, the world’s leading business software company and the emerging leading in big data technology. I spent the past eight months blogging about big data.
Yes, there is an upside. We can access more insights and quickly organize these insights clearly. But, the query returns are only as good as the individual who is running the query. Meaning, that the information gleaned from big data is limited to the requester’s logic models, knowledge areas, and biases. Just like with managing a Facebook page, what matters — in the end — is not quantity, but quality. What matters is not getting insight into historical information and real-time events. These will only tell you what happened yesterday and what is happening now. This is really not a sound foundation for predicting future behavior, particularly when you are trying to decipher behaviors that are relevant for the public sector. It’s one thing to run advanced analytics software to track the sales of the latest generation iPhone. It’s a whole other matter when trying to understand the forces shaping diplomatic relations and political upheavals. Given the research and interviews I’ve conducted on the January 2011 Egyptian uprising, I highly doubt big data could have ever provided the information that a significant political upheaval was about to take place. Big data can provide value on matters involving commercial/trade activity. But I highly doubt it will ever evolve into the be-all, end-all solution to developing accurate predictions, which countless evangelists in the IT and marketing fields are propounding daily.