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Ten Challenges Keeping Businesses From Maximizing Big Data

Big data includes data sets with sizes beyond the management ability of most developers, business managers, and software technology. The collection, understanding and use of this type of data was not possible, nor imaginable, until just a couple of years ago.

According to Wikipedia, big data can be described by the following characteristics:

“Volume – The quantity of data that is generated is very important in this context. It is the size of the data which determines the value and potential of the data under consideration and whether it can actually be considered Big Data or not. The name ‘Big Data’ itself contains a term which is related to size and hence the characteristic.

Variety – The next aspect of Big Data is its variety. This means that the category to which Big Data belongs to is also a very essential fact that needs to be known by the data analysts. This helps the people, who are closely analyzing the data and are associated with it, to effectively use the data to their advantage and thus upholding the importance of the Big Data.

Velocity – The term ‘velocity’ in the context refers to the speed of generation of data or how fast the data is generated and processed to meet the demands and the challenges which lie ahead in the path of growth and development.

Variability – This is a factor which can be a problem for those who analyse the data. This refers to the inconsistency which can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively.

Veracity – The quality of the data being captured can vary greatly. Accuracy of analysis depends on the veracity of the source data.

Complexity – Data management can become a very complex process, especially when large volumes of data come from multiple sources. These data need to be linked, connected and correlated in order to be able to grasp the information that is supposed to be conveyed by these data. This situation, is therefore, termed as the ‘complexity’ of Big Data.”

Working with big data can be intimidating and challenging. Because of this, we often see businesses shy away from tackling this monster. Below are 10 common challenges we see:

  1. Getting departments to share information throughout the organization.
  2. Handling the large amount, speed, and complexity of the data.
  3. Deciding what data – internal & external – to use in different situations.
  4. Developing operational trust in the information at the manger levels.
  5. Training & time to manage large amounts of data so insights can be created.
  6. Getting high level management on board from an investment point of view.
  7. Forming big data into manageable presentable formats for decision making.
  8. Being certain to not become overwhelmed by data interpretation.
  9. Understanding where to focus the time and money allocated.
  10. Fear of implementation of insights once the data is understood.

Big data is a force to be reckoned with, but it shouldn’t stop your business from taking on the challenge of working with it. Over-communicate on strategies and methods to share the information, and spend adequate time researching how to specifically organize and work with it.

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