While the importance of data is increasing day by day, business analytics has gained value as much as data management. Because if you can’t successfully turn it into knowledge, you won’t be able to grow your company even if you have all the data in the world. To do this, you need to separate the data that works and the data that doesn’t, analyze it, and create actionable insights. Google Cloud’s Business Analytics (business analytics); With a fully managed, multi-cloud analytics platform, it eliminates the constraints of scale, performance, and cost, enabling everyone to gain insights. You can use real-time insights and data applications to accurately manage your decisions and drive innovation.
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Data Warehouse Modernization
(Data Warehouse Modernization)
You can get more returns by modernizing your data warehouse. With a modern data warehouse, you can solve today’s most demanding demands. With built-in, advanced, multi-cloud capabilities, you can scale your business seamlessly.
Repository Modernization
(Data Lake Modernization)
You can achieve greater efficiency by modernizing your data pool. You can empower your team to ingest, store, and analyze large, diverse, and authentic data securely and cost-effectively.
Release Analytics
(Stream Analytics)
You can extract value from your real-time data using broadcast analytics. You can ingest, process, and analyze event streams in real time to make data more useful and accessible from the moment it’s created.
Business Intelligence
(Business Intelligence)
Using business intelligence, you can achieve data-driven experiences and better results. By unleashing the true power of your data, you can predict every situation you may encounter.
Marketing Analytics
(Marketing Analytics)
Using marketing analytics, you can strengthen your marketing infrastructure with actionable insights. By taking a clear, comprehensive picture of the customer journey, you can predict outcomes and create more personalized experiences.
Why Should You Choose Which Method for Infrastructure Modernization?
- BigQuery
- Looker
- Dataproc
- Dataflow
- Pub/Sub
- Cloud Data Fusion
- Data Catalog
- Cloud Composer
- Dataprep
- Dataplex
- Analytics Hub
BigQuery
Looker
An enterprise platform for business intelligence, data applications, and embedded analytics.
- Integrated end-to-end multi-cloud platform
- Common data model on top of all data
- Embedded data experiences
- Augmented analytics
- Customized data applications
Dataproc
A fully managed and highly scalable service to run more than 30 open-source tools and frameworks.
- Open: Create on-demand, fully managed open source clusters that are integrated with the data lake metastore.
- Flexible: With platform-wide integrations, you can connect to the operations support system (OSS) and Google’s cloud platform (Google Cloud Platform | Match GCP-specific services.
- Managed: Enable scalable, secure, cost-controlled open source data science.
- Secure: Configure advanced security.
- Cost-effective: Save with 57% lower cost of ownership compared to data pools on the server with per-second pricing.
Dataflow
Serverless, fast and cost-effective converged streaming and batch processing.
- Fully managed data processing service
- Automatic provisioning and management of compute resources
- Automatic scaling of workers horizontally to maximize resource utilization
- Operations support system innovations
- Reliable, consistent, one-time data processing