Big data applications demand the highest performance in computing power, with sporadic and unpredictable surges. Adding another layer of challenge is the fact that Hadoop and analytics environments are complex to configure, deploy, and manage. In many cases, the volume of users and data ingested grow at a faster rate than physical hardware can be scaled. This creates increased workload demands on existing infrastructure causing overall degradation of user experience and data processing.
We deploy our Big Data Service on Bare Metal Cloud Servers specifically designed for big data application workloads to enable your business to quickly expand in response to constantly changing demands. We’re able to provision and manage physical machines fast, without the delays associated with provisioning traditional physical dedicated servers. Bare Metal servers also provide better performance than their public-cloud counterparts since there is no hypervisor or multitenant overhead. And the single-tenant nature of bare metal clouds delivers compute isolation and consistent performance – essential considerations when mining demanding data scenarios like recommendation engines, machine learning and fraud detection. With all local storage and high capacity – 24TB on the configuration designed for Big Data workloads – these dedicated servers deliver the response times your analysis demands.
But getting it right is as important as getting it fast. With our end-to-end, fully managed and supported Big Data-as-a-Service, the entire engagement starts with high-touch, customized Data-to-Decisions Workshops where our expert Data Scientists and Big Data Architects consult with your management team. We take the time up front to clearly align your business objectives with your Big Data strategy. This expedites time-to-value and eliminates problems commonly associated with moving too fast. By delivering a comprehensive needs assessment, pilot platform scope, BI use case and phased roadmap, you will be able to see your data deliver actionable insights faster.
Enterprises amass reams of data every day, and the expectation to access and process data in real-time has become the norm. Meanwhile, the very nature of business data consumption is evolving. Organizations need to combine old and new data from a broad range of sources, interact with that data in multiple ways, aggregate and analyze that data intelligently, and rapidly iterate on the results. Internal data from business transactions and operations often needs to factor in external data, such as weather, traffic, geopolitical events, currency conversion rates, stock market pricing, social media activity, and so much more. Moreover, different groups and business units are each collecting vast quantities of data, frequently with less concern for security and compliance than for business agility. Conflicting with the express desire to share information across an organization is the inherent challenge of transforming data for analysis, made increasingly complex when so much of this data resides in silos.
With the CenturyLink Big Data-as-a-Service, all these challenges can be overcome. The self-service, elastic nature of the cloud in combination with Managed Cloudera is ideal for advanced data analytics, including security information and event management (SIEM), financial end-of-trading-day number crunching, log analysis from machines or sensors, collecting and responding to social media data to manage customer experience, and so much more. Add the high-touch, white-glove attention of a dedicated team of Data Scientists and Big Data Engineers, and even the largest data sets can be honed to deliver insights that drive competitive advantage for any business.
Internet of Things (IoT) is one of the top drivers for the pursuit of Big Data by organizations today, according to a study by Dresner Advisory Services. Other industry analysts report there will be 28 billion IoT connected devices in use by 2020 worldwide, with a $1.7US trillion economic value. That amount of data represents an order of magnitude greater than anything previously approached, in terms of both scale and value.
Enterprises of all sizes are trying to get ahead of that. They’re starting by looking to Big Data to aggregate, analyze, drive decisions and act on the massive amount of data generated today. And then building out models to anticipate the data needs of tomorrow. But all of this means upgrading their entire Business Intelligence infrastructure to accommodate the taxing demands of Big Data. And it’s not just a matter of adopting new technologies for greenfield opportunities, but also a call for integrating a wide array of existing databases, applications and data sources to fully embrace the information and transform it into actionable business decisions.
The primary concerns from an architectural standpoint for cloud Business Intelligence applications are support for relational databases, connectors to on-premises data and applications such as ERP and CRM. Following closely are open client connectors (e.g., ODBC, JDBC), multi-dimensional database support and automatic updates. And although multi-tenancy was of less concern to most respondents, the assumption is that Big Data would always be a managed service, part of a larger Enterprise Cloud platform.
For any organization where information is the key to success in the marketplace, having a well-developed and easily scalable Big Data strategy in place is paramount. That is the fundamental value offered by the CenturyLink Big Data-as-a-Service: a scalable, intelligent, secure and easily provisioned solution to the Big Data challenges enterprises face today.
Images and data copyright 2016 Dresner Advisory Services.