With the number of discussions, reviews, posts, tweets exponentially increasing, the daily launch of the same query and the information collection manually is time consuming and painstaking.
So researchers & analysts need to find a way to mine the internet for nuggets of gold, that is to say that piece of information that will bring significance to their investigation and create valuable and actionable intelligence.
Social Media Monitoring solutions enpower you to look into the vast amount of data that is accessible on the Web. Millions of posts, messages, tweets, discussions get published every day. The question is: How to keep track of our subjects of interest (products, brands, campaigns, Leadership Image, Digital Identity ect.) in this information overabundance era?
The answer is simple but the implementation of this answer is challenging: You need to automate the process of collection, indexation, analysis and delivery (I will talk in another post about engagement & alerts, stay tuned).
However, you will do this only for a limited part of the web: Focusing on social media outlets that are relevant to you business or your specific interests.
Needless to say that the challenge is no longer getting information from the Web and other sources (API for instance), it has become sifting through the data. That's why a solution with sophisticated algorithms and Advanced Boolean Operators is paramount in order to get rid of the noise (noise refers to irrelevant information).
A Social Media Monitoring solution helps to bring order in this data chaos, the web is composed of unstructured content so we persistently need to Extract the data, Tranform the messages, posts, comments, tweets in a standard format for the processing and then Load the content into the database.
Powerful tools for Extracting, Transforming and Loading (ETL) data from source systems into a data warehouse are available today. They support the data extraction from internal applications in an efficient way. There is a growing need to integrate external data, such as product reviews, into these systems. The World Wide Web, the largest database on earth (Some would say that I'm wrong - largest network then) holds a huge amount of relevant information.
Advanced data extraction and information integration techniques are required to process Web data automatically. Increasing demand for such data leads to the question: How this information can be extracted, transformed to a semantically useful structure, and integrated with a "Web-ETL" process into a Business Intelligence system.
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