Data science is not new. But now we need to do it with much larger datasets.
As the volume of data has exploded, we increasingly see organizations acknowledge that not all data belongs in a traditional database. The drivers are both cost (as volumes grow, database licensing costs can become prohibitive) and technology (databases are not optimized for very large datasets).Instead, we increasingly see Hadoop – and HDP in particular – being introduced as a complement to the traditional approaches. It is not replacing the database but rather is a complement: and as such, must integrate easily with existing tools and approaches. This means it must interoperate with:Existing applications – such as Tableau, SAS, Business Objects, etc,Existing databases and data warehouses for loading data to / from the data warehouseDevelopment tools used for building custom applicationsOperational tools for managing and monitoring