As digitalization advances and data continues to grow, business intelligence and analytics leaders are challenged to create state-of-the-art solutions that accommodate fast-evolving business models of digital transformation. Today, we are experiencing an explosion of data — in volume, velocity and variety. This accelerated growth of both structured and unstructured data has motivated many business intelligence and analytics stakeholders to modernize their inflexible data warehouses and consider newer technologies to accommodate these workloads.
According to the TDWI Best Practices Report, the main driver for data warehouse (DWH) modernization is increasing the scale for Big Data. In creating scalable, hybrid and clustered environments, more and more companies move toward concepts like Data Lake and platforms like Hadoop, NoSQL, etc.
The main challenge is: Modernizing analytical data management solutions with Big Data approaches on the one hand – Increase agility and flexibility on the other hand!
That is, where automation steps in. Data Warehouse /Big Data Automation helps you exceed the limitations of the traditional data warehouse and lets you improve agility, sandbox new approaches and iterate faster than ever before. As a result, automation reduces the time-to-market for new big data solutions to its minimum and unlock new potentials of your organization's data.