EA’s Three Big Views of Big Data

Nowadays, Big Data emerges to be part of business strategy as it has potential to provide foresight upon future of product & service, thus, EA is required to know Big Data based on Domain they are working upon and continue to make inquiry such as:  How is Big Data influencing strategic technology investment and choices? What are the implications for IT governance and data governance? Does Big data fundamentally change anything about your Enterprise Architecture, or is it just a modest tweak of the information architecture that's in place now? 

 1. EA View of Big “V” of Big Data 

Besides Volume, Variety and Velocity, the other "V" –Value which interests EA the most. Without the ability to repurpose and extract intrinsic value from the data and content to facilitate social innovation, the big data premise is useless. So EAs need to comprehend the "so what" factor and make the concerted effort to extract the business value behind big data and fuel its impact on social innovation.

• Big Data Influences EA Design: When you include Big Data as an essential driver / guiding principle to develop the architecture for a business capability (Example loyalty), it has a great impact on the way the capability is designed, developed and enabled. It can be leveraged to open up exciting opportunities and strategic advantages.  

• Enterprise Technology Architects need to understand how Businesses can benefit from Big Data and explain it in financial benefit terms to Businesses. Big-Data has huge potential in providing Business Intelligence and Analytics done on unstructured data (word, excel, .pdf, images, videos etc.) as compared to traditional BI technologies, to optimized management or finance reporting, in which case you may first go back to the strategy to find a driver 

2. EA View of Big Data Strategy & Technology 

The business perception is changing. Technology strategy is no longer a backseat after-thought of business strategy. We are in the era of technology strategy driving business strategy - a first at such a scale in our lifetime - and it will become more and more common in the future, as more often than not, technology is innovation disrupter cross-sectors. This allows technical minded individuals to push technology boundaries to achieve business capabilities that some business people won't understand but agree need to be done in order to survive. Is BIG data (or whatever it will be called then) one of those?

• Big Data & EA Mutual Decency: The business goal for Big Data is to optimize customer experience and gain insight upon future products and service, which is consistent with the purpose of EA to bridge the current state and to-be state of business, that said, on one hand, EA, DA or SA can help business craft Big Data strategy, framework and solution, on the other hand, the insight captured from Big Data can also feed back in designing more practical enterprise architecture So, in that context, it appears that Big Data is (1) opening up data sets to analysis where the business value is speculative and, (2) removing the need for technology workarounds that add complexity and reduce velocity.  

• An EA needs to know about basic concepts about Big Data such as No SQL database, column database, distributed processing, distributed file systems and the other emergent technology trend and framework:  1) There is a growing interest in analytics such as SaaS providers and data visualization services. 2) There is a big impact in the way these Big Data services and vendors are integrated and rationalized into the organizations  

3. EA View of Big Data Governance

 Governance becomes very important when Big Data drives critical business processes impacting customer experience and financial.

• Big Data Impact Process and Architecture: Doesn’t that fundamentally change something about the organization and its architecture? Obviously it affects the processes involved in acquiring, managing, storing and analyzing that data. But more broadly, how about innovation strategy, information governance, and risk management 

• EA’s Role in Governing Big Data Project: Although in reality, most of forward-thinking businesses work hard to get benefit from the amount of data, very few achieve expected result. More than 75% of BI projects fail to reach expectation, lack of architecture consistency is one of pitfalls, from EA/DA perspective, how to become part of team, in order to to improve project success rate?  How to leverage limited resource to deploy Big Data? What are strategy and best practice in deploying Big Data projects 

Thus, EA’s view upon Big Data is not about “cool” or catching the eye of management as such, but the true business value it can capture and turning “Big Data” into “Big Insight/Foresight” and gold mine of digital businesses. 

Posted in: Big Data,EA