Due to the cost of storing and analysing data, the usual approach to analytics has been to only make data that is of known value available to users. But it is now sufficiently cheap to generate, store and use data that organisations are now able to let those users experiment with different data sources to see which yield useful results, Teradata's chief analytics officer Bill Franks (pictured) told iTWire.
This applies to data that is generated or collected inside or outside the organisation.
That outside data doesn't only come from public sources - organisations are increasingly choosing to combine their data to gain a more complete view.
Combining these data sets along with others such as weather conditions provides a better understanding of effective farming practices.
"The lines [between internal and external data] are beginning to blur," Franks said.
There are also changes in the types of analytics that are being performed.
Graph analysis is one example. Already widely used to help detect fraudulent financial transactions, it is becoming commonplace in other areas such as cyber security and the telco industry (churn analysis), he told iTWire.
Teradata's contribution is that the price/performance ratio of its products "has gotten vastly better," and by embedding analytics within the storage platform the company has eliminated data transfer problems.
The Teradata Aster platform provides all sorts of analytics, and "that greatly simplifies and speeds up processing" by "getting the algorithms much closer to the data," Franks said.
But these products aren't for everyone. Teradata is targeting organisations with annual revenues of around $200 million and above.