Data management has become significantly more complex as big data analytics systems gain prominence in the business world. While companies could once count on using an established type of data warehouse software the field has picked up new options. According to TechTarget, new options are not replacing old ones, as leaders have decided to run different systems side by side.
The news source noted that companies need both structured and unstructured data, meaning that while complex NoSQL options have come into vogue for unstructured data storage, companies are joining them to traditional warehouses rather than separating the two.
"Within the hybrid data ecosystem that we're dealing with today, the data warehouse is no longer the center of our data needs," consultant Shawn Rogers told the source.
TechTarget reported that while information in Hadoop and other big data storage architectures is often wild and unsorted, classic notions of data quality
still apply in the classic data warehouses.
The lack of data quality processes within the big data archives themselves is perhaps unusprising. According to Information Management contributor Michele Goetz, the priorities for unstructured information are quite different than those applied to sorted data. She explained that companies should use big data quickly and without traditional cleansing.