5 steps to create a scalable data analytics pipeline

Every application generates data, but what do those data mean? This is a question all data scientists are hired to answer. There is no doubt that this information is the most precious commodity for a business. But making sense of data, creating insights and turning them into decisions, is even more important. As the data keep growing in volume, the data analytics pipelines have to be scalable to adapt the rate of change.