Data-Driven Apps – What are they and the easiest way to develop them

At the moment, we hear a lot about how businesses need to become data-driven to remain competitive, how business need to understand their customer’s needs and quickly deliver value to those customers.

But how do you do that?

You take advantage of data-driven apps that allow users to create value or insights from data in real-time. 

What are Data-Driven Apps?

Data-driven apps operate on a diverse set of data (spatial, documents, sensor, transactional, etc.) pulled from multiple different sources, often in real-time and create value from that data in very different ways to traditional applications. For example, they may use Machine Learning to make real-time recommendations to customers or detect fraudulent transactions. Or use Graph analytics to identify influencers in a community and target them with specific promotions or perhaps use spatial data to keep track of deliveries.

These apps are also frequently deployed on multiple platforms, including mobile devices as well as standard web browsers, which means they need a flexible, scalable and reliability deployment platform. Given the demands on these apps, they need to be continuously developed to adapt to new use cases or user needs, and all updates must happen online as they have to be available 24×7.

When building data-driven apps, developers need to leverage an ever-increasing set of data processing and machine learning algorithms to meet these requirements.

So how should you go about developing and deploying data-driven apps quickly, efficiently, and more importantly, in a maintainable way?

Data-Driven Techniques and Technology

You take a data-first approach, or as A. Neil Pappalardo put it ‘A Minimize Code, Maximize Data‘ approach. In other words, you bring the algorithms to the data, not the data to the algorithms.

In the video below, I explain how to take advantage of the built-in features and functionality of the Oracle Database to develop and deploy data-driven apps efficiently. I also share some easy to follow code examples to demonstrate how much simpler your application code can be if you use this approach! Continue reading “Data-Driven Apps – What are they and the easiest way to develop them”

How to implement Data-Driven Apps – Using many Single Purpose Database or with a single Converged Database?

There is an on-going debate in our community about the best approach for developing cloud-native or data-driven apps. On one side, you have folks who say use a single-purpose “best-of-breed” database for each data type or workload you have. While the other half say, you should use a single converged database. So, which approach is right for you and your projects?

Let’s examine some of the pros and cons of each approach.

Single-purpose Databases

Single-purpose databases or purpose-built databases as they are often as known, are engineered to help solve a single or small number of problems. Given their narrow focus, they can ignore the tradeoffs usually required when trying to accommodate multiple data types or workloads. It also allows them to use a convenient data model that fits the purpose and to adopt APIs that seem natural for that data model. They offer less functionality than converged databases, and therefore, fewer APIs, making it easier to start developing against them. Their simplicity means they do a few things very well, but other things not at all. For example, a lot of single-purpose databases scale well, because they offer no strong consistency guarantees.

At first glance, single-purpose databases appear to be a good option. Developers are happy because they get exactly what they need to begin a project. However, when you look at the bigger picture, single-purpose databases can cause a lot of pain and end up costing more in the long run.

Continue reading “How to implement Data-Driven Apps – Using many Single Purpose Database or with a single Converged Database?”

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