Big Data Solutions
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 is capable of capturing 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 in your business and operational environment.
Fully Managed, Serverless Insight
Google Cloud Platform leads the industry in the ability to let you analyze 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. Our big data analytics products are able to 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 our 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-minute billing ensures you only pay for what 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.
Big Data Guides
In-depth guides and resources for your big data development.
Discover new insights and learn from public datasets hosted on Google Cloud Platform.
Access and analyze commercial datasets hosted on Google Cloud Platform.
Use Google Cloud to manage data throughout its entire lifecycle, from initial acquisition to final visualization.
BigQuery for Data Warehouse Pros
Learn how to use Google BigQuery as a data warehouse.
ETL from Relational DB to BigQuery
Learn how to extract, transform, and load data from an OLTP relational database into Google BigQuery for analysis.
Large-Scale Ingestion of Analytics
See an architecture for optimizing large-scale ingestion of analytics events and logs.
Mobile Gaming Pipeline
Examples for processing data from a hypothetical game that users play on their mobile phones.
Predictive Digital Marketing
Google Analytics Premium, the full featured website traffic analytics tool, has been integrated with BigQuery.
ML for Financial Time Series Data
Use machine learning to analyze financial time series on Google Cloud Platform.
Spotify chose Google in part because its services for analyzing large amounts of data . are more advanced than data services from other cloud providers.