"Every business is an algorithmic business."

That was a phrase that Microsoft's Joseph Sirosh used in a keynote at SQL Nexus, talking about the future of software and data. Rather than managing data, many of us will move to manage algorithms, which will determine how data is interpreted, used, processed, and potentially returned to users as information. There are starting to be too many sources of data, too much data itself, being generated at too quick a rate, to the point where algorithms become more important than the actual data in examining, grading, interpreting, filtering, and more.

This is exciting on one hand, with new opportunities for those that can develop, choose, write, tune, or enhance algorithms. I can easily see greater influence from both developers and DBAs as we work to better manage the floods of data. Especially with 50 billion sensors, IoT devices, and more that are predicted to be online in the 5 years. That's potentially a tremendous amount of data being generated.

On the other hand, this is a bit scary as separating good data from bad in the ocean of bits, and choosing helpful rather than hurtful algorithms might create lots of stress, and perhaps even fewer opportunities if few algortihms are reused. This also means we will need algorithms that can help us determine if data is actually good enough to use. After all, in the deluge, there will be bad data, that potentially needs to be excluded from queries. Will software developers become more important than DBAs as we end up with more unstructured data stores, data lakes, or other constructs that might require less administration?

I'm not sure how things will change, but it will be an interesting world the next few years as we work with larger and larger, more diverse sets of data in our organizations.