Pentaho and Think Big Analytics have entered into a partnership they say will help users measure and analyze machine-generated data, a subset of Big Data.
If Moore's Law—which described the growth of computing power in the 20th century—has a corollary in the 21st century, it could be that Big Data keeps getting bigger. (If I were confident no one else has already said this, and if I were more proprietary, I'd call that Tozzi's Law—but I'm a modest guy.) And the channel is reacting, as a new partnership between Pentaho and Think Big Analytics highlights.
Both companies are already heavily invested in the Big Data channel. Pentaho focuses on BIg Data analytics for businesses, which it couples with a close relationship to open source. Think Big Analytics sells data science and engineering consulting services.
Now, the two organizations have joined forces in a partnership they say will help users measure and analyze machine-generated data—which means information such as computer logs, network logs, sensor information, GPS data, geo-location mapping data, image data, clickstream data, scientific data and medical data, all of which are a byproduct of the ever-increasing growth of digital devices and technologies.
That type of Big Data is different from other sorts, such as address databases, sales records or social media feeds, which humans have a more direct hand in producing.
Big Data Growth
There's no denying that Big Data as a whole is rapidly growing. But within that field, machine-generated data is likely to outpace other types of information in expansion, particularly as more people adopt newer and fancier hardware devices, apps and services that automatically output large amounts of data.
Pentaho and Think Big Analytics are paying keen attention to this area of growth. As they noted, for instance, the market for "smart connected devices"—i.e., smartphones, tablets and the like—expanded by 29.1 percent last year. That means more data to master.
In this environment, the partnership between Pentaho and Think Big Analytics seeks to leverage customers' demand for feasible ways of taking stock of and interpreting the vast quantities of information that bigger Big Data will impose.
The rest of the channel, meanwhile, should take note. Just as it would have been absurd to develop a business strategy in the 1980s or 1990s based on the expectation that computing power would level off, it would be major mistake today to disregard the rapid growth of Big Data that the continuing expansion of digital might is producing.