If you google the use cases for Big Data, you will usually find references to scenarios such as web click analytics, streaming data or even IOT sensor data, but most organizations data needs and data sources never fall into any of these categories. However, that does not mean they are not great candidates for a Modern Big Data BI solution.
What is never mentioned in the use cases above is the cost, which can get astronomical. Most businesses do not require that level of horse power but can still leverage the new technologies to create a data lake and data warehouse for a fraction of the cost. If done right, we can have a solution that is more scalable and cheaper than traditional server-based data warehouses. This allows organizations to future proof their data needs as they may have “medium” data right now but expect to grow into the big data space later.
In the next series of blog post, were going to investigate the steps on creating the basic building blocks of a modern Business Intelligence solution in AWS as well as keep an eye on cost and resourcing. As a current production server VM with 1TB of space and 8GB of RAM, including database licensing runs around 20K a year, we will set this as a baseline to see if we can build out a solution that is close or cheaper. Check our the first blog post for the first in the series!