Building a Modern Data Platform
In order to function efficiently, every business must have a data platform. However, having a traditional data platform is no longer enough. In fact, it can hinder an organization’s ability to make data-driven decisions. The lack of centralization and cooperation can make having a unified view of the data a challenge. The solution lies in building and integrating a modern data platform. What makes a modern data platform, and how can you effectively develop and incorporate it into your business? This article gives you an overview; you can check out siffletdata.com for a deeper dive.
The Building Blocks of a Modern Data Platform
The following are the main components, or building blocks, that make up an effective modern data platform.
Unified Ingestion
You cannot create a modern data platform without unified ingestion. It is essential for bring data together from various sources. When gathering data, you can choose between batch processing for large chunks of data or streaming, where data is processed in real time as it is received. Effective connector patterns are also necessary so that these data can move effectively between different systems. These can either be pre-built or customized. Lastly, your ingestion system must be scalable to handle increasing volumes of data.
Processing and Storage
The next bricks are storage and processing. For storage, you have two main options: data lakes—storing raw unstructured data in its native format—or data warehouses—storing structured data. Each method has its purpose. Data lakes are ideal for data exploration and AI/ML applications, while data warehouses are suitable for business intelligence and analytics.
For processing, ELT (Extract, Load, Transform) pipelines can be used to process data into your warehouse or lake. Other real-time frameworks can process your data as it is being received.
Monitoring and Observability
Careful monitoring of your data platform ensures its reliability and performance. You should start from the data lineage; understanding its origins and transformations will give you a clearer picture and provide context for your data. Quickly identify any anomalies or unusual patterns and take action. Use reliable metrics to track your progress.
Security and Governance
You must not let your guard down; governance and security are vital to maintain data integrity and compliance. Establish clear policies and use these to govern access to data. This will protect critical data and prevent data leaks.
Operationalization
This involves automating specific workflows to ensure efficiency. Testing data quality and reliability is one aspect that can be automated. Doing this can also help you manage expenses.
Tying It All Together
Each component or brick mentioned above all comes together to create an effective modern data platform. Integrating these systems will streamline your data platform operations and reduce manual errors, increase efficiency, and improve data quality.
In conclusion, after seeing what is involved, can you classify your data platform as modern? Does it tick off these components on a checklist? If not, then your platform needs an evaluation. With the information provided in this article, you can give your data platform the upgrade it needs to turn it into a modern data platform that meets your needs and boosts your productivity.
