10. Develop and apply a technology strategy for big data management
The strategy needs to spell out a wide range of road maps, standards, preferences, and stewardship guidelines, depending on what your organization needs and has a culture for, said TDWI. For example, you could lay out a road map for maturing from structured to semi-structured to unstructured data, as noted above. Since big data comes in many forms, you need to determine the preferred platforms and interfaces for capturing, storing, and processing each form. You should design a workflow for managing big data forms in their original state, plus processing that into other states for customer intelligence, data warehousing, discovery analytics, and so on. Big data isnt the storage problem it used to be, but you still have to plan capacity carefully, as well as related issues such as the acquisition and upgrade of data management platforms. Assuming you have an enterprise-scope data strategy and data architecture, you need to determine the many places diverse forms of big data should take in those. Finally, all the above must be supported by influential business sponsors (through stewardship and governance) so that big data management aligns with business goals for maximum business value.