As a process that encompasses collecting, filtering, and cleaning data before putting it in a warehouse or other storage solution, big data acquisition needs to satisfy the five Vs:
- Volume, which refers to the large amount of data produced and shared every second
- Velocity, which concerns the speed of data generation and movement
- Variety, which relates to the different types of data that can be used
- Value, which refers to the creation of utility from big data, based on the desired outcomes
- Veracity, which refers to uncertain data
Usually, data acquisition assumes high volume, high velocity, high variety, but low-value data. This highlights the importance of adaptable and time-efficient gathering, filtering, and cleaning algorithms. These ensure the data warehouse analysis process only covers high-value data fragments.
To make sure that happens, we look for big data solution providers who follow a specific performance pipeline. This involves the process of acquiring, validating, cleaning, deduplicating, and finally transforming the data.
Additionally, we make sure that the chosen companies adhere to these key principles: