At the enterprise level a lot of different types of information handled, either operational data, marketing, business parameters, etc. Which not only have a great significance for us, but also have the disadvantage that they tend to be quite extensive.
However, we remain at the forefront because we have a team of experts in data management. They perform an ongoing evaluation of the information we receive in real time using software specifically designed to determine hidden patterns and correlations, market trends, customer preferences, among other information that is usually immersed in the ocean of information we receive.
Big data requires exceptional technologies to efficiently process large quantities of data within tolerable elapsed times. The suggested suitable technologies include A/B testing, crowdsourcing, data fusion and integration, genetic algorithms, machine learning, natural language processing, signal processing, simulation, time series analysis and visualization
Big data can be described by the following characteristics:
- Volume: The size of the data determines the value and potential insight.
- Variety: The type and nature of the data. This helps to effectively use the resulting insight.
- Velocity: In this context, the speed at which data is generated and processed to meet the demands of both our customers and the company.
- Variability: Inconsistency of the data set can hamper processes to handle and manage it.
- Veracity: The quality of captured data can vary greatly, affecting accurate analysis.
The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits.