- Though traditional business intelligence (BI) players have been slow to adopt the cloud, they are moving in that direction with alacrity, targeting both departmental buyers and CxO decision makers.
- BI solutions are beginning to combine a freemium data discovery and visualization user experience with pay-as-you-go data storage and processing, all delivered via the cloud.
The cloud reminds me of the sea. Not in the sense that it smells of brine and brims with mystery at what lies beneath those soothing waves, but rather in how the sea evolved into an economic engine, driving society forward through powerful but invisible trade routes. Like the sea, the cloud has evolved to carry commerce at scale. This is especially true with enterprise data and analytics. Only instead of mega-vessels carrying staggeringly massive numbers of shipping containers (think 18,500 of them on the Maersk Triple E class of ships), we have cloud platform providers like Microsoft, Google, and Amazon building mega-scale data repositories capable of storing, processing and carrying petabytes of information.
Recently, for example, Google productized its own rendition of HBase (Google Bigtable), putting 10 years of engineering effort into a cloud-borne NoSQL database that currently supports the company’s not insubstantial prosumer offerings, Google Maps, Gmail, et al. But unlike traditional, premises-based offerings (and also unlike large container ships, mind you), Google Bigtable doesn’t charge the same whether or not its hold is full. Customers pay for throughput, not storage, which promises predictable costs while better supporting ad-hoc usage patterns.
A similar transformation is taking place within the business intelligence (BI) and data discovery and visualization markets, where vendors like Oracle, IBM, SAP, and Microsoft are not merely pushing their wares into the ether, but also introducing new business models that emphasize both scale and flexibility. Take IBM, for example, which is currently moving its mature Cognos BI solution to the cloud and launching a freemium data discovery and visualization cloud service, IBM Watson Analytics. Like Google, IBM is also establishing large-scale data storage and processing capabilities to go hand-in-hand with these products with its own NoSQL offering (via Cloudant) and an internal data warehouse database, DashDB. And like Google, IBM is embracing flexible, tiered pricing plans based on actual usage (number of API calls, for example).
As with the evolution of global shipping routes, the cloud is rapidly evolving. There be fewer monsters there for large-scale enterprise use cases, and the price of entry is sinking, like a stone if you will. What this mix of freemium data discovery/visualization and pay-as-you-go data storage/processing means for enterprise buyers is quite simply flexibility and assurance: flexibility to allow departmental buyers and business users to explore data freely and affordably, and the assurance that the back end can keep up with business demands, all via the cloud.