24 June 2022
HOW TO GIVE BIG DATA MEANING?
Every day there are 2.5 trillion bytes of new data stored. 90% of this data has existed for less than 2 years and 80% of them are unstructured (text, audio, image, video).
The main challenge that companies face today is no longer about the completeness of the data, but its relevance, meaning its validity, usefulness, precision, and consistency.
With so much information, how do you make sense of all this data? How do you isolate the signal from the noise? We can no longer sort and analyze such volumes, we need intelligent help that will lead us towards simple suggestions for validation.
The answer to this need lies in small data, which provides the necessary context to identify the most relevant information, capable of responding to a specific problem defined by us. Therefore, the way how we receive information has also evolved: we have gone from research to receiving notifications or alerts.
There is no longer time or patience to actively seek out information. We are getting used to web services giving us the information we need when we need it – or even before.
For example, as a music lover, I appreciate that the system automatically correlates my listening with other users’ playlists to offer me similar choices that I might find interesting.
As a driver, I expect a GPS application to notify me of abnormal traffic on my usual route and recommend an alternative solution.
HOW DOES IT WORK IN A PROFESSIONAL ENVIRONMENT?
Let us now position ourselves in a professional context.
- As a salesperson, potential actions can be planned as soon as the system alerts that a competitor is mentioned in an email sent to my organization by a client.
- As a customer support agent, I realize that minor anomalies could become critical when the escalation of several incidents is related to the fact that the customer has just acquired a new product. I can then proactively reach out to the customer and suggest solutions that worked for other similar issues saved in the database.
- As a manager of a sales team, I can avoid the departure of important customers if I am informed of the appearance of several converging signs that indicate memberships are in process of cancelation.
All this is possible thanks to an application able to integrate large volumes of raw data from a varied number of sources, then adapt them to correspond to specific and contextual use cases, bringing proactively shortcuts to our actions and decisions.