Slashing time to insight with unified data analytics
As the world of business grows more complex and instantaneous, reducing time to insight with modern data analytics is the name of the game. In fact, the number one metric for every company today should be time to insight.How do you calculate time to insight? It’s a function of two measures: (1) How quickly you can make new source data ready and available for analytics; (2) How quickly you can segment your data and query it in different ways. [ Also on InfoWorld: How to choose a data analytics platform ] The first is difficult. Everyone wants real-time data for analytics, but that’s easier said than done – even today with the availability of cheap, infinite cloud storage and compute. The second is even harder still. Every time you add new parameters to analytical queries and segment the data in different ways, time to insight gets dramatically worse.To read this article in full, please click here
As the world of business grows more complex and instantaneous, reducing time to insight with modern data analytics is the name of the game. In fact, the number one metric for every company today should be time to insight.
How do you calculate time to insight? It’s a function of two measures: (1) How quickly you can make new source data ready and available for analytics; (2) How quickly you can segment your data and query it in different ways.
The first is difficult. Everyone wants real-time data for analytics, but that’s easier said than done – even today with the availability of cheap, infinite cloud storage and compute. The second is even harder still. Every time you add new parameters to analytical queries and segment the data in different ways, time to insight gets dramatically worse.
