The next generation of big data technology will lead to insights and correlations that reveal new strategies and even new business models.
I recently wrote an article called Data Lakes: Insight from the Deep with SAP Big Data expert John Schitka. It includes best practices for implementing data lakes in your organization, which are complementary to traditional data warehouses:
“There have been so many millions of dollars going to data warehousing over the last two decades. The idea that you’re just going to move it all into a data lake isn’t going to happen” — Mike Ferguson, managing director of Intelligent Business Strategies, a UK analyst firm.
The article includes some real-world examples of Big Data usage and business models.
The Climate Corporation uses a data lake to collect massive amounts of agricultural data and applies machine-learning techniques to help farmers optimize their planting.
Predictive maintenance for trains
SAP Customer CSX is a transportation company in Florida. Previously, raw data from wheel bearings sensors could only be kept for 10 days because of volume restrictions. Using a data lake based on SAP HANA and Hadoop, the company is now able to keep it as long as it likes, and look for deeper correlations with information from other sensors.
Combatting insider trading
The Financial Industry Regulatory Authority (FINRA) regulates broker behavior in the United States. It uses a data lake and algorithms to find the patterns of fraud that human analysts might miss.