Nubax’s work with Helpinghands - the next big in the healthcare delivery industry
In today’s time of desire for accessibility at a faster pace, the need for affordable and easily attainable medicines and other pharmacy products is ever increasing. Helping Hands is the newest healthcare delivery app that aims to offer medicines through doorstep service. It is breaking into tier 2 cities' markets primarily, a target market not probed into much by other healthcare ventures yet.
Post inception, Helpinghands approached Nubax for the data architecture of their app. Determining the needs is crucial for resilient and agile data architecture. Before jumping to the actual setup for the architectural foundation, our team determined the business objectives and requirements such as data shape, collection of data records (individually or micro-batches) and scalability of the data.
Nubax proposed a dimensional data model enabling transaction processing as well as analytical processing. For this, our experts chose Microsoft Azure which is a cloud computing platform for databases with features like remote access, data resilience and alignment to business scalability. In the framework, data from the applications is ingested in the hubs.Another reason for this opting is enhanced data security with password encryption and much more.
Whenever an event occurs at the data source i.e, application of Helpinghands, data streaming happens. Post ingestion, the data is streamlined and loaded into the systems for the users to access and utilize for the business processes. Malicious data security threats is another aspect to be looked upon in data-centric environments. Cloud resource managers not only ensure efficient data management but also data security. Cloud cuts the cost and provides reliability along with the scalability analysis. Clearly defined data framework supports the flexibility making sure it is easier to fix the errors.
Unstructured and structured data is collected and stored on the cloud on multiple serves to avoid downtime while processing the queries. Well joined paths provide for quick and smooth query performance through real-time analysis of data that is continuously updated. For instance, if a certain patient has bronchitis, the app user has two options. Either the user could place the order considering the listed medicines or upload their prescription. In option two, the personnel from Helpinghands collects the medicines in prescribed quantity from the local drugstore or chemist in adherence to the guidelines and precautions. Post the collection, the medicines are packed and delivered to the address put in the app by the Helpinghands delivery agent.
The application would also have health records i.e, prescriptions, diagnostic records and other relevant details of the users who are continuously engaging with the app. Based on the existing medical records and new data fed in the application, the application would be given the recommendations for the customer base. Offering discounts and other incentives on the desired products of the app users on the basis of predicted needs of the existing customer base could act as a competitive advantage over the larger counterparts in the market.
The framework synthesizes historical data, product characteristics and seasonal demand of the pin code in question to create demand predictions linking this up with the data warehouse that will service that Pincode. The data warehousing ascertains that the inventory could be maintained based on the data lakes and reports of the specific geographical areas. We strive to transform this complex data into a form that is user-friendly and convenient. The final outcome is a data-rich application gathering the data as per the user's engagement with the app and then processing and storing the data in lakes. The user base of Helpinghands is approximated at 6 million with 50k retailing partners at the pan India level with 12.5k prescription drugs and healthcare products for health ailments of almost all kinds.
The data framework modulated by the Nubax team was not only aimed at easing operational processes in data-driven aspects but also to enable Helpinghands to ace up in already bursting applications in the pharma domain by making healthcare available to the masses effectively through accelerated data-driven strategic solutions by our experts.