Organizations today capture, collect and organize vast amounts of data they hope to mine for a wide range of business insights. It rarely works out as expected, however. Gartner analysts have estimated that the overwhelming majority of data science projects — 85 percent — fail to produce anticipated business outcomes.
Legacy storage architectures can be a significant barrier to effective analysis of increasingly large data sets. Often based on designs predating cloud computing, the Internet of Things and artificial intelligence, legacy systems aren’t built to handle the extreme amount of data these technologies generate.
A decades-old storage management technique can help, however. Storage tiering is gaining traction as a way to optimize and organize huge data sets to facilitate advanced analytics. Tiering is the assignment of data to different storage and processing tiers based on the value of that data. By placing the right data in the right place at the right time, tiering allows organizations to access data most relevant to specific analytics initiatives quickly.
Storage tiering is particularly valuable for its ability to make unstructured data available for analysis. About 80 percent of the data managed by the average company today is unstructured data such as email, audio, video, social media content, documents, instant messages and IoT sensor data. However, a woeful lack of visibility into this data impedes analysis efforts.
Lacking traditional data structures that lend themselves to neat row-and-column databases, unstructured data can’t be searched and analyzed using traditional algorithms. As a result, nearly two-thirds of companies rely exclusively upon structured data for their analytics efforts. But evaluating only 20 percent of your data assets won’t provide an accurate picture.
Storage tiering allows organizations to match data to the most appropriate storage technology. That gives them the ability to move unstructured data off of traditional SAN and NAS storage arrays and onto a more appropriate tier. For example, object storage and cloud-based blob storage solutions use a flat organizational scheme that makes it possible to find and retrieve unstructured files without knowing their directory path or location.
Using this approach, an organization might implement the following storage tiers:
Moving data among tiers requires no human involvement and is invisible to end-users and applications. Management software automates the movement of data across tiers based upon business policies, predictive models and real-time access patterns. This eliminates the need to spend hours manually handling files and reconfiguring client systems.
In addition to eliminating costly management tasks, tiering delivers cost savings by ensuring that only the most critical assets are stored on the most expensive storage medium. It also improves compliance with industry and government data-retention requirements, and offers enhanced data protection with the option of copying critical data to a locked tier where it cannot be compromised.
Organizations today are eager to use their growing data stores to gain market insights, optimize operations and create personalized customer experiences. However, storing, finding and analyzing mushrooming amounts of data can be a complex and costly undertaking. Contact us to learn more about how storage tiering and other data management solutions can help you maximize the value of your data assets.