Big Data: Small Insights - Essay Example

Big Data: Small Insights? Big Data: Small Insights? Increased digitization and the emergence of Web 2.0 have revolutionized the landscape of the internet. The shift from static to dynamic, multimedia content has given rise to an explosion of content on the web. As a result, Web 2.0 has given rise to new forms of content creation, content distribution, and content consumption. The most visible impact of this has been a rise in the volume of data. Data has become voluminous and more complex, which is why it is referred to as ‘Big Data’.

In essence, there are three main concerns in terms of ‘Big Data’: volume of data, latency or delay in data processing, and the varieties of data formats. Social media as a communication channel also has a large role to play in the generation of ‘Big Data’. The immense popularity of social media has engaged, not only the young tech-savvy generation, but has also attracted the attention of online marketers looking for a cheap and effective way of involving their followers and potential customers.

Regardless, social media as a content distribution channel has resulted in huge volumes of data being managed. Now marketers are more involved in how to derive meaningful insights from the large sized data. Metrics such as engagement rate, conversion, impressions, and so on, have been developed so as to measure the performance of the marketing efforts. However, the extent to which these analytical metrics are really meaningful has not been fully established. Recently, the inadequacy of click-based analytical metrics have resulted in a greater trend towards time-based metrics focusing on the time an individual pays attention on a web page.

In addition to social media, the arrival of cloud computing has ensured that much of this data finds home, literally “online”, i.e. in the virtual world. The availability of cloud computing has enabled users to synchronize their data between various devices including their laptops and mobile phones. This means more and more data for data scientists to analyze. However, since the domain is in its infancy, analytics cannot be considered to be definite as there still are loopholes. Many businesses depend on ‘Big Data’ analytics to provide them valuable information however there are issues with applicability of the methodology and the trustworthiness of the analytics.

That said, ‘Big Data’ analytics have a great scope for future organizations as the world becomes more digitized and operates in the cyber space. Though there are a few limitations and challenges pertaining to the validity and generalizability of the ‘Big Data’ metrics that have been defined.