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5 Things You Should Know About Big Data Enterprise Architecture

Big Data has changed the way in which organizations understand and make use of the growing volume, velocity, variety and value of enterprise data. Any company, whether large or small, can take steps to analyze and make use of the disparate information it has access to, speeding up and increasing focus on initiatives that help drive and grow the company.

With the correct approach, enterprise architecture helps the business target the right market activities and fine tune marketing, sales and business operations. In fact, almost any business transformation initiative can be addressed by utilizing Big Data techniques. Techniques that can help enterprise architects ensure alignment with the business and maximize return on investment.

Architects typically already know the business capabilities they need to deliver and have a roadmap outlining the applications, technology, people, processes and resources needed to accomplish it. Big Data is different in that it enables architects to follow ideas where the outcome isn’t clear, and the data is often wont to trigger new questions or ideas.

A more agile approach to architecture development is required to handle this than what many organizations have in place today, to allow the organization to react and respond where needed to capitalize on opportunities when they arise.

With that in mind, here’s 5 key things you should know about Big Data Enterprise Architecture.

Big Data Enterprise Architecture in Digital Transformation and Business Outcomes

Digital Transformation is about businesses embracing today’s culture and process change oriented around the use of technology, whilst remaining focused on customer demands, gaining competitive advantage and growing revenues and profits.

By focusing on desired business outcomes, companies can target specific initiatives that are likely to yield high returns or deliver greatest business value based on digital adoption. Big Data may be incorporated into business strategies to help drive meaningful strategic adjustments that minimize costs and maximize results.

As more businesses become digitized, the amount and complexity of enterprise data grows, and so making use of it to better understand your customers, employees, operations, and how your products and services are performing has never been more challenging or essential. Some ability to understand and analyze Big Data can help identify the opportunities to reduce costs, serve customers better, or eliminate risks across the architecture of the enterprise.

In fact, it could be said that without any element of Big Data analysis, it’s hard to do digital transformation at all.

Enterprise Architecture Makes Big Data Easier to Digest

CRM and ERP tools are a hive of useful data. Enterprise Architects can use this data to highlight areas of opportunity and potential disruption.

Alongside this, the rise of social media has uncovered a new data goldmine, and online tools like Google Analytics provide deep insight into the consumer. Of course, this is implied by the term “Big Data”.

That said, businesses won’t find all of the data useful at any given time. The organization’s current goals and objectives should influence which parts of the data to hone in on in order to make things more manageable.

An Enterprise Architecture tool supporting a view manager can help achieve this. Organizing the same data into different views in an instant can make finding the best data thread to pull, much easier. Essentially, a view manager streamlines data into customizable, and easily digestable representations that can be updated in real-time. This allows Enterprise Architects to make comparisons far more readily.

A best practice in this instance, is to use EA to sift through Big Data, and find one metric that holds a clear influence on reaching your desired outcome. From here, EAs can branch out and find other useful data sets that can be applied to ensure decisions are as well informed as possible.

This can help eliminate guesswork and save time and cost by avoiding trial and error Big Data work.

Big Data Isn’t Just for Big Business

It can be an easy assumption to make that Big Data is best left for Business Analysts, and the typically lager organizations where they’re employed. However, in the current business landscape, its possible for any business to drill down into Big Data by leveraging the various tools available on the market.

These tools can help find, structure and manipulate data, as well as present them to the wider organization in order to influence strategy.

In EA specifically, the tools available can help you gain a deep understanding of your current-state and past-state enterprise data activity, and therefore can be used to help understand trends and make projections that influence your future-state enterprise.

Reports of this nature go along way, for example, by indicating whether a specific Digital Transformation workstream is worth pursuing or not, as well as steering it once the target future-state has been agreed upon.

Big Data Can Help Position EAs in an Advisory Role

A key objective of Big Data is to surface new value from extensive data sets, and as an Enterprise Architect you should be prepared to advise your business and IT stakeholders on how its possible to leverage Big Data techniques to achieve their objectives.

We’ve talked before about how EAs could in fact, be best place to be a front line in advising the CIO, due to their holistic view of the organizations assets and potential.

To properly leverage Big Data to position yourself at the ‘big table’, EAs should recognize that every enterprise is unique with its own goals – the drivers for each company differ, and near-term and long-term goals can and do change over time.

By understanding the business goals, key challenges and business outcomes, Enterprise Architects can start to break Big Data down into insights that will drive success.

The use of SMART (specific, measurable, achievable, realistic, time) based goals can allow you to have concrete criteria upon which to measure results and effectiveness.

Big Data EA and the Business Motivation Model

The business motivation model (BMM) in ArchiMate® can be used to describe the goals, drivers, assessments carried out, and stakeholders involved in decision making. It’s a way of putting factors of influence on the business in context, providing a language in which they can be discussed and used to better strategic planning.

An invaluable tool for Enterprise Architects and the wider business, the motivation model helps improve decision making by adding a structure and cohesion to the strategic planning process.

Most EAs agree that there is still work to be done in order to reach a perfect (or even near perfect) alignment between IT and the wider organization – something that CIOs across organizations are striving for. Much of the reason for this shortcoming, is a lack of effective communication.

The cohesion in planning achieved by a business motivation model, makes it far easier for plans to be communicated across departments and ensure everybody is working towards similar outcomes. This mutual approach is the driver behind this business and IT alignment.

The connection between the BMM, and Big Data Enterprise Architecture is simple. In short, Big Data provides additional and much needed context to build better informed BMMs. The more data you have surrounding a specific influencing factor, the more accurately you can predict the extent of said influencers, influence. Enterprise Architecture can help refine Big Data for this purpose, so analysts and other relevant parties can see a snapshot of only the relevant data, essentially cutting the fat.

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