Managed GCP Big Data services
Google Cloud Platform provides a wide range of powerful Big Data tools that can cater to any business need you might have. These features can help build and run comprehensive systems for real-time Big Data processing or for powering predictive analytics for your systems. IT Svit has handled more than 200+ Big Data projects and we have learned the best practices of using Google Cloud Big Data analytics tools. Gain instant access to skilled Big Data architects and empower your operations with data analytics from Google Cloud!
One of the most popular GCP Big Data tools is Google Cloud BI. This business intelligence platform is created to help any startup or SMB gain full control over their dataflows and utilize every aspect of their operations cost-efficiently. This cloud-based solution can absorb millions of various events each second, regardless if these events come from the cloud or from your on-prem data sources. GCP BI tool can validate huge data sets instantly due to working in synergy with powerful tools like Cloud Data Fusion, Cloud Dataflow and Dataproc, Big Query transfer API and others. as well as custom-tailored Big Data modules of your choice.
The most efficient way to store data during analytics is through an internal data warehouse. These systems can be build using Google Big Query, Google DataPrem and Data Catalog services to catalog and warehouse the data in transit, so it is ready for instant analysis using Google Big Query Engine to process the data and visualize the results using Big Query BI engine. The outcome of the analysis can come in the form of Google Spreadsheets, via API, via Google Data Studio or Big QUey BI engine interface. As a result, you get a powerful tool for ad-hoc analysis of your real-time data.
One of the most popular and discussed data analytics services from Google is the Big Query. It enables a multitude of actions, from data validation on the fly, creating catalogs of incoming data streams, processing data in batches or in streams and interact with a huge bunch of other Google Big Data systems. Big Query can accept millions of events a second using the Google App Engine auth server and quickly consume them with the help of asynchronous messaging from Cloud Pub/Sub service. The results can be delivered to Google Cloud Storage for keeping or pushed to a multitude of tools like Tableau, Data Studio, Cloud Data lab and other output points.
Apache Hadoop.with its Map-Reduce feature is a key component of various data analysis workflows. Google Cloud Platform has developed a wide variety of tools to integrate with Apache Hadoop and other parts of Apace Stack: DataProc, Google BigTable, Data Fusion and Dataflow, etc. Cloud COmposer will help you build CI/CD pipelines for interacting with these tools, and Google Functions are available through Big Query to provide serverless computing when it is needed in your Big Data systems.
We have already mentioned Google Data Fusion — a powerful tool for real-time data integration. It is a serverless feature with an intuitive GUI and a huge library of pre-configured connectors to simplify building ELT/ETL workflows to interact with other tools.
IT Svit has a thorough understanding of the DevOps best practices and Google Cloud Big Data analytics tools and workflows that can help your company reach the business objectives and gain a competitive edge through leveraging Big Data analysis.
