The rapid spread of unstructured data is both an opportunity and a challenge as it provides the possibility of new insights at the cost of changing infrastructure needs and new approaches to managing, storing, and manipulating that data. The real value of Big Data lies in combining historically structured data with this new unstructured data. This combination results in better insights, more powerful analytics, and improved business performance.
Data Lakes take a store-all approach to data, providing a repository that retains all incoming data in its original raw format. This data can include both structured and unstructured sources, and the Data Lake architecture supports ingest and storage of the largest and fastest data sets.
Traditional Data Warehousing approaches are a standard approach for obtaining business intelligence from well-known classes of structured data. Data Warehouses can work well when paired with a Data Lake — for example, using an Enterprise Data Hub architecture. But a Data Lake offers a number of flexibility benefits in addition to the incorporation of unstructured data:
BigRio can work with your team to design a Data Lake that can grow with your organization’s data needs and utilize the investment that you’ve already made in existing Data Warehouses and other structured storage and analytics systems. Design parameters include:
A Data Lake may help your organization reduce cost and time-to-insight for new analytics and support exponential data growth. If you are considering building a Data Lake or recognizing some of these pains and benefits, talk to BigRio about how we can help.