Modern Data Platform Customization

In terms of software positioning and messaging, “platforms” are all the rage. And, more recently, a new platform has emerged as the “platform du jour” – the “data platform” – as businesses struggle to handle an expanding quantity of data and an increasing range of data types created by an increasing number of applications on an increasingly diverse mix of infrastructure.Of course, under the hood, many of these so-called data platforms are more likely to be vendors’ old point solutions, capable of only managing one piece of the giant data management puzzle. Either because they only manage a specific subset of data – on-premise data, virtualization data, or specific types of application data. It May fail to provide complete data management capabilities – for example, merely replication but no data governance. 

The Modern Data Platform makes it possible to:

1. Optimal use of hardware resources. Rather than owning something, businesses pay for the privilege of using it. Customers control how much they spend about their consumption, which eliminates scalability difficulties. 
2. Security, monitoring, dependability, disaster recovery, and other cross-cutting problems are core concerns addressed early on. 
3. Use of technology in a fine-grained manner 

The following components will make up the platform:

1. Data warehouse: This is the most crucial component of our design since, no matter how clever the other components are, an inefficient data warehouse will cause us problems. Fundamentally, the data warehouse’s 40-year-old principles and paradigms are still valid today. 

2. Data integration: It should be no surprise that we need to get the data into our platform. Thanks to the contemporary data stack, what was formerly a time-consuming job of establishing and deploying connections is now a solved problem. 

3. Data visualization: This is where we get to truly study the data and develop value from it in various data products, such as dashboards and reports. One of the most significant advantages of this period is the availability of robust open-source data visualization tools deployed quickly. 

4. Metadata management: Because most of our platform’s capabilities (such as data discovery and data governance) rely on metadata, we need to ensure it is consolidated and used across the board. 

Conclusion

You must be able to comprehend, federate, mobilize, govern, and employ it. These basics provide you with the ability to build a comprehensive data management plan that ensures that your data is completely safeguarded and that you can use it to generate commercial value. 

To recap, updating our existing data lakes and warehouse is no longer an option but rather a need. And the cloud is the ideal alternative for deploying our next-generation modern data systems. By retaining transactional and more predictable loads that run all day on static resources and transferring all “few hours in a day” type loads to ephemeral resources. 


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