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Creating scalable infrastructure is essential for any modern digital platform.
How your data is stored and accessed should be the foundation for your architecture, as this directly impacts both internal and customer facing business practices. Ineffective data storage results in slow performance, service unreliability, and loss of revenue. Each business’s data is unique and how they serve and store that data should be individualized to your needs. Sannsyn has a proven track record in deploying data-lake and data-warehouse solutions for clients of all sizes. We provide expertise in all modern cloud storage platforms including: AWS, Azure, and BigQuery.
Your data storage should be driven by your business practices and not the other way around. When implementing a data lake solution we work with our clients to identify the core purpose of their data and in what ways that data will be ingested and served. Once this has been identified our team will then look at the size of your data and how frequently and in what ways it is accessed. Sannsyn has expertise in implementing microservices such as Apache Spark, Kafka, and AmazonGlue in order to aggregate, clean, and prepare data for API endpoints.
When considering implementing a data-lake solution, we encourage our clients to think about how they will gain access to their raw data. Will the data be ingested via streaming, API pulls, or user file interaction such as drag a drop? Often times it is a combination of these options and it is important to have an experienced team to ensure a robust solution that will be the backbone of your platform. Sannsyn has deployed data-lake solutions for clients of all sizes, ranging from the GB to TB scales, for customers in a variety of segments including advertising, medical, business intelligence, and mobile/web applications.
Sannsyn has experience working in both structured and unstructured data formats and creating robust ETL pipelines to transform unstructured and semi-structured data into useful structured formats such as SQL-based databases. In addition, we are experts in big data and No-SQL environments and have implemented custom data engineering solutions using Hadoop and HDFS environments, Cassandra, and Elasticsearch.