Impact of Big Data On US Economic Output
Source: McKinsey&Company
What I believe is missed here is the ability of Big Data to actually boost the effectiveness of the other 4 areas they mentioned:
- Shale Oil and Gas
- Trade
- Infrastructure
- Talent
Oil Industry Seismic Data
For instance, you may not be aware of it, but there exist a vast library of seismic data, collected over a span of decades by the Oil & Gas Industry. This seismic data is mostly on tape and has to be converted to digital data before it can used. That is a large task for the Petroleum Industry in and of itself, but the tricky part is that the characteristics of the seismic data varies for a variety of reasons:
- Different seismic noise generation methods employed
- Different data standards employed
- Different crews doing the data collection
- Different reasons for doing the collection in the first place
This means there is a huge issue with data quality as well as data conversion and in some cases, the seismic data will have to be reshot by the oil industry. Big data, i.e., HANA, can help, but just going faster in these scenarios just makes the problem bigger, faster.
That is why you also have the Talent part solved.
You need to combine skills with Big Data, 3D Visualization, and Engineering to fully solve the seismic data problem.
Big Data is part of the Infrastructure equation. When you start talking about planning or deciding which infrastructure projects to fund, you need functionality like Linear Asset Management, Portfolio Management and a whole host of others to make economy wide decisions.
Finally, Big Data will certainly come into play in the complex arena of Trade. The Retail Industry alone is something in the neighborhood 12 trillion globally. The number and types of transactions generated from this volume of trade demands something possibly even beyond the current understanding of Big Data.
Boosting the U.S. Economy Will Require Effort in 5 Key Areas
Obviously, there are many other scenarios that I could have addressed, and I will in the future.
However, the main point I wanted to make was the increasing importance of "Big Data" to a wide variety of critical fields.
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