Today’s guest blogger is Simon Margolis, Senior Cloud Platform Engineer at SADA Systems.
Working in big data can provide a wealth of information for organizations of all sizes in all industries. The dramatic business impact big data analysis provides is unsurpassed and a growing number of organizations are rapidly realizing the benefits. That said, the immense cost and complexity associated with effective big data analytics often is a major deterrent.
Traditionally large volumes of storage, compute power, and support systems were required to get meaningful information from big data. Solutions such as Apache’s Hadoop required specialists in creating, maintaining, and running their offering. Beyond the personnel cost, massive hardware and infrastructure costs were applied up front in order to realize any meaningful intelligence. Google Cloud Platform (GCP) reduces the time, effort, and cost of getting real value from big data.
Most significantly, Google Big Query (BQ) offers big data analytics as a service. As opposed to procuring, building, and maintaining an analytics system, Google offers BQ as a frontend to their existing wealth of computing power. Not only does a pay-as-you-go model (and newly available “all-you-can-eat” model) eliminate up front spending, queries also run on Google’s industry leading infrastructure which offers results astonishingly fast. This means that an organization which may be skeptical of the benefits of big data analysis can determine impact with very little spending.
By using other elements of GCP, services can work together to provide lightning fast data transfer and results to big data queries. Data stored in Google’s Cloud SQL and/or Google’s Cloud Storage can move very quickly into BQ for analysis. Because all of these services are housed within the same Google infrastructure, huge volumes of data can move from service to service rapidly.
Furthermore, a frontend can be built in Google’s App Engine to provide a custom interface for which to work with this data. Using Big Query, App Engine, Cloud SQL and Cloud Storage, the options for workflow customization and integration are limitless. On top of this, all of these services run on Google’s top of the line infrastructure, the very same framework which runs Google Search. This means there is never a concern of reliability, speed, or availability across all services.
Learn more about how SADA Systems can help your organization leverage big data using GCP by visiting our website!
