What is a Hybrid Cloud Data Platform?

Posted By: administrator
Posted On: 04 Jan, 2021
Last Updated On: 07 Jan, 2021

What is a hybrid cloud data platform?
It is the technology required for processing cloud data in a modern business environment. A hybrid data platform comprises cloud services or on-premise data warehousing. You can also consider the various data sources, data types, and data management as essential components of a hybrid cloud data platform.

Technology in a Hybrid Cloud Data Platform

In terms of technological aspect, a data platform should consider the following factors regarding enterprise data: 

1. Volume 
Volume indicates the storage systems that employ cloud technologies. Hybrid Cloud Data Platforms can be delivered on cloud service providers such as Amazon Web Services, Microsoft Azure, and Google Cloud. These data platforms offer the capability to expand support for increasing data volumes and maintain that data for more extended periods. 

2. Data sources & Types
Most businesses use multiple digital devices and with different sources. Data inputs may be from social media and mobile phone apps in structured, unstructured, or semi-structured data. 

3. Data acquisition velocity
Data arrives from multiple sources. The data consolidation from different sources becomes because all the variety of data needs to be in a single format; so virtual unity through data management is crucial. Effective data consolidation can be achieved through adaptive indexing and employing metadata. The use of various data analytics enables an organization to increase its understanding of enterprise data.

Data Usage in a Hybrid Cloud Data Platform

The goal for any organization is deriving data-driven insights for business operations and needs. Those insights are obtained through data pipelines that cleanse, format, and organize the data. Data pipelines are fed with data from business operations. These operations get input from workflows, data quality measures, and data governance. 

The relevant insights derived from the business processes need to be circulated to the entire organization. These insights can be in the form of reports, service layer APIs, or mobile device alerts for financial and operational performances. Dashboards, reports, information on stored data links with current data; would be useful while processing invoice data in a financial system. 

From the viewpoint of a business, data types are an essential component of a hybrid cloud data platform. Customer data can be considered the most significant data in a data warehouse. Businesses want to convert prospects into valuable customers and loyal customers into their product promoters. A rich customer data collection and processing is necessary to consolidate aggregated customer data to identify productive customer groups and segments. 

  • Best practices for customer data management can be listed as:  
  • Each customer should have an individual source record even if he is using multiple data sources.  
  • Customer data access should have standard governance and protocols for storage, retrieval, and deployment.  
  • Irrelevant and unstructured data that are not necessary for the business should not be stored or processed.  
  • Customer privacy concerns need to be addressed. 

Conclusion 

A hybrid cloud data platform needs to manage various types of data.  Transactional data is generated through customer interactions like product purchases, product returns, payments, subscriptions to newsletters, and other recurring information or donations. They have legal as well as business significance. Different essential types of data are operational data, contact center data, marketing, and sales data.  

Once an organization has decided on what data is important for their business to collect, then the data platform needs to be monitored and deployed. Data needs to be processed timely, appropriately governed, and protected. The data storage, along with data access and usage needs to be properly managed. 

Daton is an automated data pipeline that extracts data from multiple sources for replicating them into data lakes or cloud data warehouses like Snowflake, Google Bigquery, Amazon Redshift where employees can use it for business intelligence and data analytics. It has flexible loading options which will allow you to optimize data replication by maximizing storage utilization and easy querying. Daton provides robust scheduling options and guarantees data consistency. The best part is that Daton is easy to set up even for those without any coding experience. It is the cheapest data pipeline available in the market. Maintain a hybrid cloud data platform easily with a data pipeline like Daton.

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