Popular Google Big Data Products and Services for Enterprises
Using the Google Big Data products the organization can analyse the data trends and patterns and can take the decisions for implementation for the growth of the organization.
Big Data is the term which deals with a huge volume of data, both structured and unstructured. But it’s not the amount of data that is important. It is what the organizations do with the ever-increasing data, that is the only matter of concern. Big Data can be analyzed for insights that lead to better decisions and strategic business moves or some statistical analysis.
Big Data Products of Google are :
Big Query: It is a serverless data warehouse. It is a highly scalable enterprise data tool that helps the organization to store the massive data and query the data accordingly. Using the Big Query, the organizations can share the insights within their teams. The insights of Big Query are Real-time analytics, logical data warehousing, data transfer services, automatic high availability, geo-expansion, etc.
Cloud Dataflow: It allows the organization to build pipelines to monitor their execution and transform the data for analyzing the data sets in the cloud. It is a serverless execution that is free from planning, resource management, and performance optimization. It also allows the Apache Spark and Apache Beam for batch processing.
Cloud Dataproc: Cloud Dataproc is an easy to use cloud service where you can run Apache Spark and Apache Hadoop. The operations that usually take hours or days, with the help of Google Dataproc, it will only take a few minutes to complete the task. You need to pay only for the resources you use with per-second billing.
Cloud Pub/Sub: It is a highly scalable, reliable event-driven computing system used for stream analytics. It is used to send and receive messages among the independent event-driven applications. It arranges the data from different applications and projects running in the cloud. Messages published to any topic using pub/sub is automatically sent to all subscribers.
Cloud Data Fusion: It is a fully managed data integration service which helps to build data pipelines using ETL and ELT processes. It provides a graphical interface that enables better insights on integration and action rather than coding.
Cloud Composer: It is a service that has the power to monitor, schedule workflow orchestration across the clouds and on-premises data centers. It is supported by python programming at the back end of this service to build Apache Airflow open-source project. Very useful for auto-scheduling of jobs.
Data Catalog: Google Catalog is a fully managed and scalable metadata management service. Google Data Catalog offers a simple and very easy-to-use search interface for users. This is a very flexible and powerful cataloging system for capturing both technical metadata and business metadata.
Google Data Studio: It is a serverless data analytics product, used for analyzing the data. It helps to create interactive dashboards for visualizing the data and finds the relationships among them. For making the business in an innovative way.
Google Sheets: Sheets users use the data with spreadsheet formulas or perform deeper analysis with features like Explore, pivot tables, and charts for understanding the business insights.
Cloud Dataprep: It helps to prepare structured and unstructured data for analysis and cleans the data before the visualization takes place. It is a serverless approach and works on any scale. Moreover, no infrastructure is needed to deploy or manage this service.
Cloud Data Transfer: Data can be transferred to the cloud with blazing speed. The data may vary from gigabytes to petabytes with more security and no data loss.
Cloud Bigtable: It is a highly scalable NoSQL database like MongoDB, CouchDB which is very much suitable for low-latency and high-throughput workloads. It is mainly used for analytical applications like the IoT, IoB and Financial Analysis.
Cloud Storage: It provides storage facilities for storing website content and data for archival and recovery.
AI Platform Notebooks: Google AI Platform notebooks is an integrated service managed with JupyterLab to create certain instances for a machine learning framework for integrating with BigQuery, for analyzing the large volume of datasets.
