In the real world scenario at present, the challenges of dealing with big data can be grouped into three major dimensions, namely process, data, and management. Let us delve into the ins and outs of these challenges one by one.
In this specific context, the biggest challenge is how to analyze. According to business experts, it can consume tremendous paramount exploration to figure out the right model for analysis and to iterate very rapidly by means of numerous models at scale. In nutshell, process challenges can be broken into the following points:
The data challenges associated with big data can be pointed down as:
The prime management challenges are associated with data security, privacy, governance, and ethical problems. Here, the core lies in ensuring the correctness of data, which means following the intended usage and relevant laws of the data. Also, tracking the way in which the data is utilized, derived, transformed, and managed.
Apparently, numerous data warehouses comprise sensitive data, for instance personal and confidential data. There are ethical and legal concerns attached to the access of such kind of data. Thus, the data must be access controlled, secured, and logged for audits.
Big data has clearly hit the spot beyond the realm of buzzword status. It is emerging as an innovation carrying a huge potential for value creation. Along with colossal opportunities, such as location related data, social data, manufacturing or retail data, and healthcare, there are challenges, such as data volume, data capturing, data quality, and data management.
As more and more data becomes less expensive and technology becomes more advanced in terms of analysis and acquisition, the opportunity to render actionable information would augment. This can be termed as the common great challenge for big data.