Cloud allows us to focus on business issues rather than worrying about infrastructure, seamless access to new features of open source and managed services, faster time to market and so on. Every stage of data lifecycle google cloud platform gives services which can be selected, tailored to data application requirements. Google cloud platform offers a large platter of data analytics services.
Today we look more in detail about GCP data analytics and its components, its features etc.
What are GCP Data Analytics services?
Google cloud platform offers a complete suite of services most of which are embedded into Google tools. These tools are built for analytics, Machine learning and Artificial intelligence solutions which can be integrated into existing tooling to provide real time intelligence. Earlier days storage of data created ‘data silos’ or ‘data swamps’ which were tough to use for the purpose of analytics. Modern data architecture uses metadata to manage structured and unstructured data in a manner which is easier to query and analysis.
GCP Data Analytics Services and Solutions
Google cloud platform provides numerous services and solutions for analytics. We will discuss and learn more in detail about GCP Data Analytics Services.
- BigQuery – is an enterprise-wide data warehouse which uses Google infrastructure to support fast SQL queries. We can move massive data sets in BigQuery and it can handle large data volumes. Users have the control over access to data.
- BigQuery ML – uses standard SQL for building and deploying machine learning modules; it is used by data analytics and scientists to build ML queries in a quick manner. Models can be exported for referencing in future or to be used in online predictions using cloud AI
- BigQuery BI Engine – is a service which provides high fast in memory analysis. Users can use it interactively to analyse data sets which are big and complex in nature
- Connected sheets – are used to analyse millions and billions of rows of live BigQuery data without use of SQL.
- Data QnA – provides a natural language interface to perform petabyte scale data analytics on BigQuery and data sources which are federated. Data QnA can be integrated with tools like chatbots, Google sheets, and BI solutions. Post integration users can use natural language to leverage data.
- BigQuery Omni – provides fully managed and Multi cloud analytics. Users can analyse data across multiple cloud environments. Questions can be answered quickly and shared across data sets using SQL in the interface of BigQuery.
- Data flow – is meant for fully managed streaming analytics. It uses batch processing and auto scaling for cost reduction, reduction in latency and processing time. It has several key features such as a streaming engine to improve data latency and auto scale, Dataflow SQL is to use Google sheets and other BI Solutions to have real time dashboards, Auto scaling is used to automate scaling.
- Dataprep – It is developed by Trifecta. And has intelligent data capability to visualize the entire process of cleaning, preparation and exploration of unstructured and structured data. It is server less, and scalable so there is no need to deploy or manage infrastructure.
- Dataproc – provides fully managed cloud services to simplify APACHE Hadoop and APACHE Spark cluster deployment. Resources can be chosen per cluster node and leverage auto scaling for cost reduction, cluster optimization and high availability.
- Stream analytics – Ingestion, processing and event streams analysis in real time. It can stream millions of events per second into a data warehouse.
- Marketing analytics – let you apply Google cloud machine learning on all data. A complete picture of customer behaviour, mapping the entire customer journey, and prediction of business and marketing outcome. It can be used to create personalized experiences for users.
- Data catalogue – is a fully managed metadata management service to scale according to business requirements. Data catalogue is server less , provides a simple user interface with features of advanced structured search capability. It comes with built in cloud DLP integration to empower data governance.
- Google cloud analytics with NetApp cloud volumes ONTAP – is the leading enterprise storage management system , which delivers secure, storage management services on various cloud platforms – AWS, Azure and Google cloud. It supports 368 TB capacity and has a strong set of features such as high availability, data protection, storage efficiencies and Kubernetes integration etc.