Google Cloud platform provides seriously powerful data & analytics services. This data fuels amazing applications and helps businesses compete. Harness massive amounts of data with GCP’s integrated Big Data platform.
Big Data Analytics at Google Scale
Today’s applications are generating an unprecedented amount of data from diverse sources within your enterprise, extending out into the physical world where any device can capture important signals for analysis. The volume of data being generated is increasing at dizzying rates. Highly unstructured, raw data can tell a story of your operations environment and your customers in a way that we can now tap efficiently at scale. Analytics and machine intelligence at web-scale have been in Google’s founding DNA since the very early days. Google Cloud Platform surfaces the same analytical engines invented and used by Google for nearly two decades to help unearth insight into your business and operational environment.
Fully Managed, Serverless Insight
Google Cloud Platform leads the industry in the ability to let you analyse data at the scale of the entire web, with the familiarity of SQL and in a fully managed, serverless architecture where backend infrastructure is fully handled on your behalf. GCP’s big data analytics products can scale automatically while you focus only on the business insight you want to uncover.
Fast Queries on Petabyte-scale Datasets
BigQuery is Cloud Platform’s fully managed data warehouse that lets you economically query massive volumes of data at speeds one would expect from Google. Pay as you go, taking advantage of GCP’s pricing benefits and the scalability and security of Google’s world-class infrastructure to power your business insights.
Unified Batch and Stream Processing
Cloud Dataflow is an innovative, fully managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and stream analytics. Express your computation with no switching cost as you use a single tool and programming model for both batch and continuous stream processing flows.
Spark and Hadoop in the Cloud
Companies standardized on great open source tools including Spark, Hadoop/MapReduce, Hive, and Pig, will find a natural transition in Cloud Dataproc. Never worry about your data pipelines outgrowing clusters as Dataproc lets you create and resize clusters quickly at any time. Per-second billing on the underlying Compute Engine resources ensures you pay only for the resources that you use, and you can spin down to zero when your analysis completes.
Managed Databases, Object Storage and Archival
Specific business questions you might ask in the future are difficult to predict. Never discard events and valuable metadata in your business environment — store them economically to mine insight later. Choose from a variety of globally available storage products for your data, from managed SQL to NoSQL options, including our category-defining archival product Nearline.
The Next Stage of Machine Intelligence
The long-term opportunity for companies lies in applying Google’s heritage of machine learning and analytics at web-scale to real-world data relevant to your business. Cloud Platform enables modest-sized teams to aggregate and run machine learning workloads on massive data to do predictive analytics. To disseminate the use of machine learning, Google has recently opened-sourced its library for machine intelligence TensorFlow and launched Cloud Machine Learning products, including several pre-trained models usable out-of-the-box such as Cloud Vision API, Cloud Speech API, and Google Cloud Translation API.
Tap into Innovation
Google has led the industry with innovations in data processing technologies such as MapReduce, BigTable, and Dremel. Now, Google is making the latest generation of its data processing tools available to everyone, including industry-leading programming tools and programming models.
Article Source: Google Cloud Platform
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