Lay the foundations for data-driven applications in your business by storing relevant information in scalable and cost-efficient structures.
Prepare your business to use data
In order to take advantage of state-of-the-art Machine Learning and Data Science techniques, your company’s data must be organized and available for prompt consumption. Exterior data sources might also be needed to more accurate algorithm result, and this requires the creation of dedicated ETL routines.
Scale properly as your business grow
Solutions should be based on each business needs, taking into account costs, requirements and the existing knowledge of the team. Projects also need to take into account how to scale up to meet demands created by the company growth.
Data Lakes and Data Warehouses
The modern approach do deliver data across organizations uses mainly two concepts, but there are many variations that might be a good fit for your case. They are the Data Lake and the Data Warehouse.
A Data Lake is the place to store data in a more flexible format. We suggest the use of files in the Hadoop file system in a cloud provider ( like the S3 from AWS or Cloud Storage from GCP ) because this allows retrieval of information in large scale using Spark but does not sacrifice flexibility.
Data Warehouses services are usually provided in a managed instance from the cloud provider. We suggest using Redshift in AWS or BigQuery in GCP, but this can be implemented in traditional relational or NoSQL databases as well, depending on your company needs.
