Companies generate huge amounts of data, growing exponentially with time. This implies large data collections, which traditional data management tools are not powerful enough to process. Big Data is the solution for these cases. As companies generate massive amounts of data, being able to identify business relevant information can be a competitive advantage.
What is Big Data?
Big Data is the blend of technologies and processes that make possible to work with huge amount of data. Besides Volume, it is possible that the data is generated in a high Velocity or data is too Varied. That is known as the 3 V's:
- Volume: When the amount of data exceeds the capability of traditional technologies.
- Velocity: When data is generated so fast that is impossible to give an answer. For example IoT or web performance.
- Variety: When apart from structured data (ERP, CRM, Excel...) there is also non defined data such as (video, sound, social media messages...).
Big Data is needed to process and analyze all these large amounts of data. From batch, to streaming
When is Big Data needed?
At Mistral, we develop and design Big Data projects for our clients, when it is needed. This happens when in Business Intelligence and Data Science projects, the traditional technologies are not empowered with enough technical capabilities to process or analyze the information caused by one of the three V’s.
What is not Big Data
Big Data is the muscle, and Data Science or Business Intelligence are the brain. In some cases, Machine Learning is enough to approach data analytic projects, without having the necessity to implement Big Data technologies.
Big Data systems are responsible for the interconnection between algorithms and the data. This information will be provided in, real time updated dashboards, ready to be used by decision makers or who it concern.
Real example of Big Data in Mistral
In one of our successful case studies, our client, dedicated to the rent a car sector, received millions of petitions per day, from final clients, to other companies such as airline entities.
We implemented a Big Data cloud solution that was able to ingest this quantity of data and transform it in real time. Once we could work with this data, we developed a dashboard containing all the information. With our solution, our client is aware of the request alteration during a year and thus adapt the prices to the demand.