Future will be, to put it correctly, present is of artificial intelligence, Artificial intelligence has moved far beyond the stuff of science fiction. And, for all the benefits AI provides today, we can only guess at what the future of artificial intelligence holds.
But data lakes help ensure that organizations are poised to take advantage.
Biggest trend we see today mainstream adoption of artificial intelligence. See can see it being used almost everywhere. One of the major used instances is, that is driving adoption (at least, in a generic sense) is that artificial intelligence engines can sometimes be used to spot trends and derive meaningful insight from an organization’s existing data.
But the crux is that for the artificial intelligence to this needs access to raw data. There are obviously a number of different ways of making this data available for analysis, but one of the best options may be to create a data lake.
What is Data Lake
Data lakes typically, is a large collections of data, structured or unstructured. In broader term it can contain data just about everything, from a filed data (unstructured) to the one created by IoT-enabled industrial sensors. Data lakes, by their very nature, are large and disorganized.
Which poses a questions, why create something as chaotic as a data lake, when it’s probably going to be easier to configure an artificial intelligence engine to analyse structured data instead.
Let’s take a look at the different reasons as to why data lakes
- Data lakes give you the opportunity to analyse data that might have previously been ignored. Structured data sets, by their very nature, are limited.
- Data lakes act as repositories for pretty much anything and everything. As such, there is a feasible path for analysing data that otherwise would not be usable.
- Data lakes act as a backbone for carefully tuned AI engine to extract hidden business insight from otherwise mundane data.
- data lake approach to storage allows an organization to be more agile and better positioned to take advantage of advancements in artificial intelligence. Data lakes can accommodate all data, independently of any schema.
Data lakes require IT pros to think of data storage in a way that is completely different from how they might have thought of storage in the past. Even so, this new approach holds great promise for making organizations more agile and better positioned to take advantage of advancements in artificial intelligence.
