Data Engineering 🔨
Braxton Analytics has completed data engineering projects across various industries. From connecting to REST API’s, SFTP Servers, and Cloud Storage Locations, Braxton Analytics does the first major milestone in connecting to valuable data sources. From there, data engineering projects require a solid amount of cleansing and transforming the data to meet business requirements and be able to view the data in a simple format. The data is usually in a format that is ready for reporting and dashboards or to keep a data pipeline running.
Valuable data pipelines run automatically with zero manual intervention. Poor data pipelines create a bottlenecks within the business and lose trust with stakeholders.
Integrate & Capture data.
It all begins with the data source. How do we connect to the data? Whats the best way to connect to the data? How often is the data refreshed? Who is the main point of contact for the data source? How many endpoints do we need to connect to in order to get a full batch of data? What is the plan for if the data source goes down? Is there an existing integration tool in place or do we need to build one from scratch? Answering these questions will allow us to smoothly connect to the data at its raw source and build a sustainable infrastructure for the data pipeline to run.
Transform & Load data.
What do each of the fields look like? How much logic needs to go in place in order to get the data in a consumable format? What is the plan for tracking history? Are there any nested JSON fields? What is the key structure for each table? Answering these questions are the foundation for creating a curated and reliable data set for your data team and broader organization.