Hardly a day passes without an article, a point of view or a news bulletin being released that talks about the importance and value of Data. Most of the big technology trends we see today are either directly or indirectly related to this new data centric business thinking including IoT, Artificial Intelligence / Machine Learning, Big Data / Analytics and Blockchain to name just a few.
Data is the main ingredient for enabling and enhancing a company’s Artificial Intelligence (AI) capabilities. A data centric business architecture that provides a reliable understanding of data sources, data quality and data value is therefore essential to drive AI adoption.
So, what does all this mean for the enterprise? How do you enable a data driven enterprise that utilizes the value promise of its data and the new emerging technologies that help harvest that value?
Architecting the Data Driven Enterprise
We see companies built around three main building blocks: people, processes and tools. While this is still essential, the meaning of tools in the past often was synonymous with applications which in term were defined as a static, programmed collection of capabilities that supported people in executing processes. Going forward tools will need to be thought of as flexible, technology enabled business capabilities that can be used, changed and disregarded like the apps on our mobile phones, often developed and maintained by AI.
One day you need access to weather data and information which makes you download the Weather Channel App. At the very next day this data and information might lose relevance and instead you are interested in the road conditions in Southern France. What would you do? Delete the Weather Channel App and download an app that provides access to data and information that is relevant for you at that point in time.
This paradigm shift requires enterprises to move from a static, application centric Enterprise Architecture (EA) towards a fluid, data centric Business Architecture (BA). Putting data into the center, the business architecture function will need to focus on managing and making available data to enable current and future services, products and business model.
So, what does this mean concretely? Traditionally, applications have represented main building blocks of every Enterprise Architecture. With the shift of focus to the business value of data as enabler of current and future business, the importance of applications starts to fade. While access, management and ease of usage of data is more critical than ever, it is not necessarily tied to a specific application. To clarify, there will still be a need for technology enabled capabilities but they will be more fluid and agile and will not necessarily reside in fixed, encapsulated applications that provide pre-defined capabilities but will rather be made available and be developed on an ad-hoc, agile basis e.g. through app stores, user friendly visualization tools, artificial intelligence or rapid development environments.
Successful companies will therefore build their business, enterprise and technology architecture on an open data platform combined with APIs, microservices and where value adding dedicated applications or PaaS services.
Enabling AI in IT and business
As described earlier, business and IT departments need to understand their data better and ensure data quality. This includes the business data itself as well as meta data and process data that describes how data is used and manipulated to deliver business results.
Our earlier blog post Sentient IT – artificial intelligence meets IT department, describes in more detail how collecting and making usable data about the operations of IT itself can drive the rapid automation of IT operations leading to increased efficiency, flexibility and business centricity.
At the same time, an in-depth understanding of business data can enable the adoption of AI in the context of business operations, processes and services as outlined in another recent blog post: Three Steps to #AI Powered Enterprise.
Enabler of a data drive enterprise
Cloud storage and computing capabilities provide a wide range of opportunities to make data available, accessible and usable whenever its needed and by whom ever requires access (inside or outside the company).
Microservices, PaaS solutions and APIs will play a critical role in this context:
- Microservices: instead of buying off-the-shelf applications, microservices provide a fast way of developing and provisioning critical capabilities without the “luggage” of large implementations and roll-outs. They are easily re-usable and can reside in the cloud.
- PaaS: Platforms, like the one provided by salesforce.com provide easy access to lean capabilities (e.g. through an app store) as well as the possibility to develop simple capabilities as required. As such, they can replace large production systems with smaller, fit-for-purpose applications at a lower cost point.
- APIs: As not all data will be made available in a single place, APIs will allow easy access and utilization of data through applications, visualization layer and user interfaces.
This and other elements in the lean data driven architecture will complement and / or replace existing applications that have become more and more a hindrance for true business development and innovation.
As data becomes the fuel of current and future business success, it will be critical to shift the enterprise architecture from its old focus towards a data centric business architecture. As such, BA will need to focus on making data available – easily accessible and usable for usage by business independent of capabilities and limitations provided by applications.
While traditionally we have seen big monolithic applications and IT services, the future will focus on modular, nimble technology enabled business capabilities that are powered by microservices and / or APIs.
The data revolution will provide great opportunities for incumbent companies in many markets, segments and industries as they have large amounts of relevant customer, product / service and market data to harvest and utilize as basis in their transformation towards data driven enterprises. In consequence becoming a data fueled platform rather than a traditional products or services company. But more about this in a later blog post.
For now, start looking at your data from a different perspective, shifting it to the center of your architecture.