Between the massive volumes of data, new storage platforms, and latest processing and analysis methods, IT’s scope of responsibility has expanded dramatically.
IT leaders are left wondering how to manage the new technologies being thrown their way — especially when it comes to managing the new world of big data in combination with existing business intelligence (BI) initiatives.
Modern enterprise data architectures need to unite big data, which is stored and processed by platforms such as Apache Hadoop, with the cleansed and structured information traditionally held in the enterprise data warehouse (EDW).
Doing so will enable business users, like business analysts and executives, to make better decisions backed by the broadest, most recent and most detailed data.
A hybrid enterprise data architecture that combines big data, traditional EDW and BI is achievable, and some enterprise customers are already moving in this direction.
Keep these best practices in mind if you're trying to turn data into business-ready information:
Today, most organizations manage complex, multi-layered data environments that involve multiple data sources and a variety of data storage, warehouses and processes. With these current environments it’s challenging to gradually introduce Hadoop into data architectures without interrupting business processes, data access, user data flows and other things end users have grown used to.
Doing so requires architectures that can incorporate big data, while still leveraging existing investments in environment, processes and people.;