Innovation in storage technology doesn’t end with bigger drives and cloud solutions; other technologies are poised to solve the complexities of data storage and its rapid growth, with software-defined storage (SDS) showing the most promise. SDS solutions could radically change the enterprise storage market. Significant research by leading vendors has indicated that the software-defined storage market is expected to be worth at least $5 billion by 2018.

The tangible benefits offered by SDS, which are realized almost immediately, are fueling this growth. As with other software-defined solutions, SDS enables network operators to better manage the storage, flow, and access to the incredible amounts of data generated by rich media, big data, business analytics, and wireless device adoption. SDS brings those benefits to bear by leveraging virtualization technology that abstracts data from the storage hardware, creating a virtual representation of the physical storage that eases the reconfiguration of resources and allows the pooling of dissimilar storage systems into a cohesive centrally managed representation of all storage resources available, regardless of the underlying hardware technology, physical location, and storage platforms in use.

With SDS, organizations are able to call on available resources and re-provision subsystems on the fly, creating a paradigm-shifting experience around storage ideologies. That has created excitement in the storage industry, driven some of the biggest tech names in the industry to buy startups focused on SDS, and led private equity and venture capital investors to funnel dollars to new players in this nascent arena.

While many look at SDS as the next big thing, the technology has its roots in the evolution of the cloud, where virtualization has become a key component for everything from server provisioning to networking to data center design. With that in mind, it becomes easy to understand why storage virtualization has become the next logical step for those interested in maximizing the value of their storage subsystems as well as adopting cloud ideologies and next-generation technologies.

The post Software-defined storage: benefits and migration best practices appeared first on Gigaom.

Early users are finding that software-defined data center (SDDC) technologies are introducing flexibility into their enterprise while reducing operational and management costs and also fueling the drive toward the cloud. SDDC can bring benefits to the modern data center, including reduced total cost of ownership (TCO) and the ability to repurpose or rescale in a matter of moments. Other benefits include reduced operational and management costs, as well as the ability to more quickly adapt to new technologies, speed integration projects, and launch new services.

Simply put, SDDC may become one of the most disruptive technologies to impact enterprise data centers, and it has the potential to rapidly change the market landscape as well as change the way data centers are funded, designed, provisioned, and managed. That disruption is driven by many factors, ranging from economic concerns to efficiency initiatives and furthered by data center operators seeking to leverage economies of scale while creating more-secure and adaptable environments, which are more manageable and less complex.

The potential impact of SDDC products should not be underestimated. These technologies offer an integrated architecture, which allows the consolidation of legacy hardware, cloud computing, and workload-driven architectures into a single manageable domain. Nevertheless, SDDC still has a long way to go before it is fully viable as a wholesale replacement for legacy data centers.

The post A field guide to the software-defined data center appeared first on Gigaom.

On the benefits side, careful location of processing to separate data integration and stewardship activities from operational and analytical activities is clearly required. The industry has moved beyond a single relational database to do everything. There are more choices today than ever before. New BI tools are arriving every day that take reporting and analysis to new levels of visualization, collaboration, and distribution. Embedded analytical processes in operational systems for decision making rely on fast, deep, and clean data from data warehouses.

Data warehousing can trace its antecedents to traditional information technology (IT). Big data and especially its most prominent tool, Hadoop, trace their lineage to search and e-business. While these two streams are more or less incompatible, they are converging. Data-warehouse providers are quickly adding Hadoop distributions, or even their own versions of Hadoop, into their architecture, adding further cost advantages to collections of extremely large data sets. Finding the talent to manage this newly converged environment will not be easy, but it presents tremendous opportunity for companies willing to take some risk.

The post The new economics of enterprise data warehousing appeared first on Gigaom.