object Storage Helps Create Data- driven Business Models: Joan Wrabetz, HgSt
HGST, Inc. (formerly Hitachi Global Storage Technologies), a wholly owned subsidiary of Western Digital, deals with all-flash arrays, object storage, and hybrid cloud storage solutions. HGST helps enterprises with storage systems that supports data archit
—JOAN WRABETZ, VP Marketing, Datacenter Systems Business Unit, HGST
Where do storage technologies feature in the world of digital transformation? There is no argument that we live in a data-driven world spurred on by digital transformation. The challenges in digital transformation are fourfold: data monetization, data architecture strategy, best practices in managing data, and managing data in the cloud. Note that all the challenges of digital transformation have a direct implication on data. This connects the dots between digital transformation and data.
Now let me bring in storage technology and connect it to data. The value of data comes in when you can monetize it either directly or through the insights gleaned from the data. The right kind of storage determines the availability of data. The data that the organization already possesses is either on tape and hence cannot be accessed readily or that the data is in silos or that the data cannot be shared.
What kind of a storage solution would help with data?
The solution to this is to build a large-scale storage system, specifically a petabyte-scale object storage with cloud-native S3 interface, that lends itself to extreme durability. Such a system helps create data-centric business models.
Such as storage system is based on object storage. Legacy storage is designed for transactional purposes (frequent read-writes), while object storage is designed for archival; rare writes, very frequent reads.
Are organizations able to approach this in the right way?
Management is tuned to today’s storage, they have big investments in existing storage and managing the technology lifecycle of today’s storage products. This has huge implications on the data architecture strategy. What is needed is a change in the status quo, a new approach.
What is the new approach?
This new approach is predicated on the idea that data architecture strategy is different from storage architecture strategy. The suggested data architecture strategy should be amenable to implementing cloud scale operations that is run on a simple architecture that yields low TCO.
The benefits of such a data architecture include access to unstructured data with scalability, combine file and object storage, and move away from silos with capabilities like analytics and backup.
Where does cloud feature in the conversation about data and storage?
Flexibility with cloud is important. A hybrid cloud is inherently flexible; private cloud can be used for sensitive and active data and the public cloud can be used for data processing. In many new applications, data will live its entire lifespan in the cloud. Data is created, managed, analyzed, acted upon and archived there. Cloud providers keep up with the growing demand economically and cloud storage services offer high availability and consistent I/O performance.
How does this get used across verticals? Are there specificities?
Each vertical has its own use cases. Media and entertainment industry has the need for archiving, CDN, distribution, and rendering workflows. HGST solutions enable production, broadcast, and distribution companies to work more efficiently by delivering fast, flexible, and scalable storage for every stage of the workflow. It enables the M&E market to create, leverage and preserve data while improving productivity and lowering TCO for 2K, 4K, 6K, HFR and UHD workflows.
In life sciences, we enable genomic sequencing, medical imaging, and biological research labs to deliver fast, durable and scalable data for every point in the data analysis workflow using technologies from NVMe solid state drives, rack scale flash platforms to object storage and hybrid cloud storage solutions.
What would be some straight points of advice for CIOs on data and storage strategy in the era of digital transformation?
• Focus on the economics of data, not storage. • Assume that storage costs will go down, the value of data will go up. • Minimize data in legacy systems. • Build cloud-scale data architectures and move to cloud native applications. • Separate applications from data. • Assume that data and applications will move across clouds. • Build native support for analytics. • Drive TCO down with scale.