Automated Data Synchronization

In the private sector, data synchronization across platforms plays a critical role in the success of many industries - including retail, healthcare, finance, manufacturing, and logistics. Each of these industries relies heavily on their ability to make real-time decisions with consistent data across multiple systems. The Falkn team has direct industry experience solving this simple, yet complex problem.We understand the mission critical need to establish architecture for a central data store as a single source of truth with a unified data structure. Each data entry must have data most important to understanding the defects such as location, priority, classification, and more based upon user research. Further, the system entries must include meta data and additional data fields as determined by the needs of the customer and feasibility. For this system to automate data synchronization to support real-time decision making, we believe the best course of action is to leverage event driven architecture to create atomic data cleaning transactions. This will allow custom data transformation techniques for each data feed to the central store as well as discarding, flagging, or combining redundant data. Further, this system must include a secure deployable interface allowing pre-built, customizable, and saveable queries.Our team of experts leverages an iterative agile process where we regularly solicit feedback while providing transparency to our solution. Utilizing a sprint level process (2 weeks per iteration), we are able to consistently evaluate security or performance concerns while better understanding the scale of the problem. Further, as we collaborate on this unique problem set, we will evaluate, when appropriate, the leveraging of Artificial Intelligence in order to streamline the understanding of potential data inconsistencies.Following a collaborative, agile process delineated in 2 week sprints and further outlined in our Statement of Work, in Phase I, we aim to:Understand the data shape, time sequence, and technical interface of each individual databaseUnderstand the application environment and deployment methods for said environment, including performance constraints and network protocolsCreate the architecture for a centralized databaseCreate architecture for individual data cleaning pipelines using event driven principlesIdentify and plan for failure pipelines and remediation techniques for each data storeScope functionality and create wireframes of a database query application