Transactional systems aren’t meant for big data storage and analytics. They’re configured to perform specific functions and workflows well, with the expectation that data is changing all the time.
Combining data from multiple transactional systems into a data warehouse, lake, or lakehouse allows you to cost-effectively and securely store your data and obtain valuable insights across your business, all without compromising the performance of your transactional systems. Data warehouses are designed to hold discrete data that does not change often. This is especially important if you want to take advantage of automations or Artificial Intelligence.
Our approach to data management ensures data quality, security consistency, accessibility, and scalability.
Consider a Phased Approach: Data Lakehouse projects can be a massive effort, especially for growing or small companies, but taking a phased approach provides quicker wins and faster ROI.
Focus on Performance: We understand the initial data needs, and create an infrastructure that fits those immediate needs, as well as the current budget. The data management infrastructure will scale as the business grows to manage and forecast cost.