Because customer relationship constitutes an important part of any strategic decision-making process, shifting towards Big Data technologies would enable executives to keep up with customer service expectations. A top concern for them is how to achieve faster access to data in order to overcome the many obstacles they would encounter.
Typically, data in organizations can be in the following three forms:
- Structured Data. Such data is stored in databases (in tables) and can be accessed by using database management systems such as Oracle, DB2 and MySQL. This data constitutes only 10% of the universal data today.
- Unstructured Data. Such data cannot be stored using traditional relational databases. Unstructured data, which usually comes in formats like text, image, video, document, etc. accounts for about 90% for all data created in this decade. The importance of unstructured data is the important interrelationships revealed that cannot be discovered otherwise.
- Grey Data. a perfect use of such data by enterprises is determined based on the specific business needs.
The variety and complexity of unstructured data requires the use of management systems other than the traditional ones that stipulate the presence of structured, normalized and densely populated data.
Moving towards Big Data is faced by:
- Lack of expertise: most organizations do not have the required level of expertise to design and implement Big Data solutions.
- Too many tools: vendors and developers have introduced a large number of tools and technologies to the level that it has become even confusing when deciding which tool(s) to use.
- Clumsy use: it can be a challenge for many organizations to move smoothly to Big Data world without considering issues like prioritizing use cases, allocating budgets, security issues, etc.
An effective use of Big Data can lead to successful market leadership. This requires ideal utilization of return-on-investment and time-to-benefit, given the limited size of human and financial resources. Unless Big Data challenges are solved efficiently and quickly, moving towards the implementation can be slower, more expensive and even harder.