Moving your Data to Delta Lakes, what should you consider?
As businesses deal with increasing data volumes, the need for organised data management solutions become important. Data lakes emerged as a recent advancement, to tackle the complexities of handling diverse data formats from various sources. Data lakes are designed to store and process both structured and unstructured data. Offering a cost-effective solution for retaining data in its native format while enabling in-depth analysis. The evolution of data management has introduced delta lakes, which enhance security, performance, and reliability using open standards like Kafka, JSON, Avro, and Parquet for real-time change data application. For businesses aiming to streamline data processing and exploration, integrating machine learning through platforms like Databricks can further enhance data structuring.
If you’re considering implementing a data lake house, here are key aspects to consider:
Source System Compatibility – Ensure compatibility with open standards like Kafka and Spark for seamless data replication. Stelo supports many source database products including Oracle, IBM Db2, IBM Informix, Microsoft SQL Server, MySQL, and others.
Destination Flexibility – Choose destinations compatible with open standards technologies to ensure efficient data transport. Once your data reaches its destination with Stelo, the possibilities for its utilisation are in your hands. Whether you choose to access it through Synapse, implement AI applications, or deploy ML models, the timely delivery of data transforms it into actionable insights, significantly reducing the time to gain valuable insights.
Change Volume Analysis – Understand the volume of data changes over time to size the application accordingly. Stelo’s capability can handle up to 100 million transactions hourly, although they note from experience that most common need ranges from under 100,000 to over 10 million transactions per hour.
Performance Expectations – Decide on performance requirements versus lossless data capture for optimal data delivery. It is important to find a data management partner that provides a balanced mix of performance and lossless data capture, customised to your specifications. At Stelo, they engage in a thorough discovery process and involve your data scientists in discussions. System adjustments are swift and often don’t involve extra costs, typically completed within a day.
Business Cycle Consideration – Consider your business’s data processing peaks and troughs to accommodate variable data volumes effectively. Stelo’s Data Replication service excels in real-time data ingestion and migration, adapting seamlessly to fluctuations in business volume. While data lakes have been in existence for some time, their evolution and management have posed challenges. As a trusted data management partner, Stelo has navigated these challenges cleverly, providing businesses with cutting-edge technologies that set new standards. Their solution ensures the efficient delivery of change data into delta lakes, prioritising accuracy, scalability, and cost-effectiveness.
The Bottom Line
Data lakes have been around for a few years now, and they have evolved a lot in terms of how we use and maintain them. Maturation hasn’t been easy. As a data management solution partner, Stelo avoided the growing pains, and today, we offer businesses the most modern technologies that are emerging as best-in-class standards. Our solution efficiently delivers change data into delta lakes with a focus on fidelity, scalability, and cost.