It’s the number-one goal of any company: creating experiences across channels to maximize the acquisition of new and the retention of existing customers. To do so, marketers must take a step back and look at the entire ecosystem that is part of the experience; make sure technologies are in place, communicate with each other, and then execute the experience. Data is the information and technologies are the tools that enable the experiences.
Modern applications generate data at incredibly fast rates from various sources within enterprises. This extends into the physical world and allows any device to easily capture meaningful signals for analysis. And the amount of data being generated is continuously increasing. Highly unstructured and unorganized; raw data can create an image of the entire operational ambiance as well as your customers in a manner that allows an efficient tapping at scale.
Since its inception, analytics and machine intelligence at web-scale have been in Google’s DNA. Google Cloud Platform (GCP) now offers the same technologies that Google has been using for nearly two decades, in a formalized platform that enables you to generate insights into your business and operational ambiance.
Fully Managed, Serverless Insight
GCP sits at the pinnacle of analytical industries. It is offered at a global level and allows you to analyze data at the level of the entire web. Google technologies are architected to be serverless and are fully managed (i.e., backend infrastructure is handled completely by Google on your behalf). The big data analysis products can scale at run time, automatically allowing you to focus on the aspect of your business you want to treat.
From managed Spark clusters and fast SQL analysis to the latest in machine learning, GCP empowers and facilitates data scientists to spend more time extracting value from data clusters and minimal time worrying about infrastructure.Regardless of how it’s stored, GCP makes it easy for you to analyze data. Take structured data for example; Google BigQuery is a fully managed, cost effective data repository with ANSI SQL compatibility, as well as integration with Python, R, and a plethora of other programming languages. For more general storage, Google Cloud Storage is powerful, simple, and can be accessed from any part of GCP. Ultimately, whatever method you prefer, you can access your data through Apache Spark running on a Google Cloud Dataproc stream, and then analyze it via Google Cloud Dataflow.
It doesn’t matter if the task at hand is predictive analytics, tactical optimization, nuanced learning, recommendation engines, or building automated decision engines, Google Cloud Platform helps data scientists work faster and smarter. The major challenge analysts face is that data is now more complicated and unpredictable than ever before. In its raw form, it is sometimes unstructured and unorganized. But this is no longer a problem, because GCP is flexible and adaptable, with the ability to sort any data complexity, no matter how stacked and indeterminable that data may be.
