Information architecture: The key to governance, integration and automation
We have always had information around us, and it likely always existed in large volumes. It was just presented in different formats such as paper or hard copy documents, postal mail, telegrams and wired messages, verbal conversations and recordings, posters and public notices, pictures and so on. A lot of data is still disconnected, and a lot of it still exists in silos.
Even if data is connected, we may not have a good understanding about it or what it really means, which can prevent us from seeing its value. This scenario recalls the broken phone game in which one person whispers a message to another person, who whispers it to yet another person and so on. When it reaches the last person, the message may be completely different from the one relayed by the first person.
Deriving deeper meaning
What has changed in the way in which we extract value from data? We talk about analytics and new insights, but the true question that needs to be answered is what are we going to do with the information? How will it help us to improve our business, our life and everything around us?
Consider the Internet of Things. We have objects connected with other objects, and they can communicate in intelligent ways. The Internet of Things is becoming a big information space that provides constant streams of data. And the collected data can reveal more information about individuals, their interests, their locations and many other particulars. Yet, much of the Internet of Things data we collect today is not used at all. Moreover, the data that is used is not fully utilized. We see only a small picture.
We don’t aggregate data efficiently, and the insights we generate may just provide a different representation of analytical reporting without triggering any future actions or business automation. In many cases, we do collect data with the intent for future processing and analytics, but it remains in the system and often forgotten. So how much information is actually useful?
Volume, velocity and variety of data increase the richness of the insights we can derive. At some point, information became a company asset and essential to the programs and services we deliver. But we really need to understand the information and know what to do with it. We all are looking for solutions that provide real-time analytics using integrated data from devices, ecosystems, people and other participants. Streaming unstructured data can be processed as we receive it and analyzed (on the edge) to generate structured data that will be stored. And based on the analytical insights, our processes can be changed for the better. But to reach this outcome, we do need a thorough understanding of the business and the underlying information needs, how to structure the information resources to support those needs and how to manage and maintain the architectures.
Developing an agile information architecture helps to establish the decision-making principles and standards for using information as a business resource, support business requirements, enable the enforcement of information governance and integrate and automate business processes. It can define the fundamental specification that connects the flow of information throughout its lifecycle.
Bringing people and technology together
To develop a successful information architecture and meaningful insights, we need to enforce collaboration across business units, IT, the CDO office and other parts of the organization. And perhaps more importantly, we need to change the culture to get people thinking of how new technologies help eliminate all the barriers and create an environment in which everything is automated and transparent.
Thinking about information taxonomy and classification isn’t necessary. Tools are just the tools, and we will continue to live in the past without proper collaboration, information sharing, knowledge base building and adoption of a new way of thinking about information. Technology is enablement; people need to understand, change the processes and do so using technology’s help.
When we are developing information architecture, we are looking into all aspects of the different data sources that provide structured, unstructured and other forms of data. Information architecture components such as classification, information lifecycle, metadata management, naming standards and security models provide the foundational layer and consistent specification for any enterprise. Information security is also a critical part of information architecture and needs to comply with legal requirements and protect information from unintended access or intentional misuse.
An information architecture model evolves as an organization transforms itself. New unstructured, semistructured and structured data from external and internal sources are introduced and captured to analyze and discover new patterns and knowledge for traditional reporting or advanced analytics. In this model, governance—catalogs, processes, views and so on—is a key element. Mobile and social computing requires a new approach for gathering and connecting data from private and public sources.
When a new data source is connected, its contents are linked to the business metadata. Decentralized systems can leverage cloud technology and encourage communication and collaboration across company boundaries to become more consumer oriented. Developing and supporting frameworks for systems of systems—including standards and applications and cognitive and non-cognitive software agents or systems—enables grouping, teamwork and combined effort by multiple entities across a wide range of tasks to improve efficiency. Information governance can start small and focus on the most important information, and then expand as it demonstrates its worth. It needs to evolve with the business and be responsive and accountable while seeking to communicate and educate people in the appropriate management of information.
With the increase and diversity of data sources, understanding the level of trust associated with a piece of information across all systems will be even more important. The future of successful analytics systems and insights is in a fully collaborative environment and architecture framework that enables information exchange and sharing among architects, data scientists, developers, the user experience, application tuning and performance.
Connecting people, processes...and information
The journey to becoming an organization that effectively leverages analytics solutions and practices to achieve information management maturity and efficiencies requires connecting the people, processes and information within an organization. The essence of sharing information in a controlled manner is vital to an organization, where information is leveraged to optimize business processes, analyzed for insights and managed according to organizational policies.
Learn how you can use the IBM Watson Data Platform to manage information effectively and put cognitive technology to work in your business.