By Dharmesh Desai - Posted January 2, 2017
Imagine reliably asking Amazon Alexa, Amazon Echo Dot, Google Home, or a chatbot to run analytics queries against a big data platform. For example, “What were the top three revenue generating products last week?” or better yet “Start my Spark cluster” — all without firing up your computer, scrolling through a report, looking through spreadsheet columns, or asking an analyst or a data admin. Big Data at the tip of your tongue–pun intended.
The concept of conversing with a computer is very interesting and has been around for a while–think Star Trek’s “LCARS” and Hal from “A Space Odyssey”. While we might be a long way off from those realities, recent advancements from Amazon, Google, Microsoft, IBM and other natural language and AI technologies have brought us closer. We can expect a lot of new, creative services being built in the near future.
Meanwhile, in the big data space, with the massive amounts of data generated along with advancements in machine learning algorithms and the speed at scale of computing, it’s only a matter of time before Artificial Intelligence (AI) and Machine Learning (ML) will also power big data analytics. In ways and at speeds never experienced before. These systems will meld with the technological innovations in the peripheral areas like Internet of Things (IoT), cloud computing, and natural language processing.