In today’s world, the ability to quickly create value from different types of data increasingly provides businesses with a competitive edge. An excellent example of this is how responsive, personalized and portable a food delivery app might be.

But how does a business become data-driven? 

The easiest way for businesses to generate this type of value or insight from data is to take advantage of data-driven applications built using modern development paradigms and deployed on flexible, scalable and reliable platforms. 

What is a data-driven application? 

Data-driven applications (apps) operate on a diverse set of data (spatial, documents, sensor, transactional, etc.) pulled from multiple different sources, often in real-time. To help businesses make faster, more informed decisions, these applications are required to create value from data in very different ways to traditional applications. For example, they may use Machine Learning to make real-time recommendations to diners or detect fraudulent transactions. Or use Social Graphs to identify influencers in a community and target them with specific promotions or perhaps use spatial data to keep track of deliveries.

To meet the demands placed on data-driven apps, developers need to leverage an ever-increasing set of data processing and machine learning algorithms. Ironically, getting the data to these algorithms can become cumbersome and fragmented. But, there is an alternative approach that is far easier, and that is to take advantage of a Converged Database. A Converged Database is a database that has native support for all modern data types and the latest development paradigms built into one product. By integrating data types, use cases, and dev paradigms as features within a Converged Database, you can support mixed workloads and data types in a much simpler way. You don’t need to manage and maintain multiple systems or worry about having to provide unified security across them.

You also get synergy across these capabilities. For example, by having support for Machine Learning algorithms and Spatial data in the same database, you can easily do predictive analytics on Spatial data. Making it more straightforward and faster to develop data-driven apps.

During the recent Oracle Database at Home virtual event, many of Oracle’s product managers and customers shared how easy it is to develop and deploy a data-driven, online food delivery app called GubDash using on a Converged Database in the public cloud. 

Across six sessions, the knowledgeable presenters demonstrated how the app took advantage of different data types, features and functional built-in to the core database to deliver a highly performant, scalable and reliable app.

If you didn’t have an opportunity to participate in last week’s Oracle Database at Home event, don’t panic. All of the sessions were recorded. Below are the links to the six sessions

1. 1 The Future is Data-Driven
   This session discusses the importance of data to an organisation and the need to build applications where the value within that data can easily be exploited. To achieve that aim we need to start building applications that benefit from the flexibility of new development paradigms but don’t create artificial barriers of complexity that stop us from easily responding to change within our organisations.

1. 2 Data-driven Microservices Architecture with Converged Database, Kubernetes and Helidon on the Oracle Cloud
   This session provides an overview of a data-centric Microservices architecture. It highlights some of the key concepts including, domain-driven design, event-driven services, Saga transactions, Application tracing and Health monitoring with different microservices using a variety of data types supported in the database – business data, documents, spatial, graph, and events. A running example of a mobile food delivery application (called GrubDash) is used, with a hands-on-lab that is available for attendees to work through on the Oracle Cloud in conjunction with this session.

1. 3 Loading, indexing and searching for recommendations in Text and JSON
   This session covers cover loading large JSON datasets into an Oracle Database, indexing the content and providing a RESTful search interface – all using Oracle Cloud features.

1. 4 Maps and Spatial Analyses: How to use them
   The first half of the session describes the rich set of spatial analysis and spatial application development features of the database. The second half explores a case study of how these features are used in a Marketing Analytics platform to help identify prospective customers and provide a compelling customer experience.
   

1. 5 Modern App Dev: the Path to Cloud Computing
   This panel of great Oracle experts discuss what it means to build modern applications and what is the recommended way to do so in 2020?

1. 6 From Low-code to Core-Dev, building Apps to make sense of the Data
    In this session, attendees are introduced to a low-code framework (APEX) and a core-dev one (JET) to see how the approaches and results differ.

Source: oracle