The increase in use of digital technology within enterprises is causing a massive influx of the amount of data produced from cloud, mobile, IoT, social media, and more. Because of this deluge, many companies are simply filtering data into holding grounds for native data they haven’t had time to process, known as “data lakes,” which often go unmanaged. This data that is of unknown origin, quality and context is untrustworthy for use in initiatives to increase revenues, decrease costs, and manage risk. In fact, rather than being a strategic corporate asset it becomes a business liability.
As organizations deal with an exponentially increasing volume of data, many feel that the industry is entering uncharted waters. With greater amounts of data comes larger quantities of “bad” data, and CIOs arguably struggle more than ever to know which enterprise information management (EIM) projects to prioritize as they seek to effectively manage and analyze data to make it actionable. The truth is, however, that the old EIM challenge of managing data is new again. For example, with the increasing demand for supporting IoT, Machine Learning, Artificial Intelligence and Big Data in all types of businesses, the importance of knowing where the data comes from and its quality is more important than ever before.
The Risk of Unmanaged Data
With so many aspects to the data equation, it’s easy to get bogged down by the minutia of a program and seek new technology and tomorrow’s solutions to get ahead of the pack. However, it’s important to remember the overall goal of the initiative, and ensure each decision made supports that overall goal.
For example, one organization I worked with was laser focused on using proprietary algorithms to gain a competitive advantage. They hired a data scientist, pointed her in the direction of years’ worth of data stored in Amazon S3, and told her to determine the best way to drive innovation with it. She was not given any metadata to show where the data came from, nor how the data lake integrated with the rest of the company’s data. There was also no infrastructure for data analysis, so he had to spend company time and money trying to find tools compatible with the technology stack and install them. The lack of architectural design and an information strategy resulted in the project not delivering business results.
Tailored Strategy and Architecture
The key to ensuring business innovation remains the same in EIM: to have an information strategy and architecture that serves the unique needs of the organization. CIOs must take charge of that strategy to keep it focused. A great way to start is to reinvest in enterprise architecture with an eye to security, data, integration, process and analytics. Then, layer on service-driven approaches that enable business agility, and innovation and support for improved decision making. Without a solid information architecture, just understanding where data came from will be a challenge, and using it to enable better business outcomes will be nearly impossible.
Data Governance that Drives Business Value
Another key to successfully managing today’s deluge of data, is to implement a data governance program with a focus on driving business value not just regulatory compliance. By standardizing terms, policies, and rules with clear linkage to business processes and outcomes, CIOs and Chief Data Officers will be able to not only prioritize data management investments based on business value and secure greater executive support, but also implement this program throughout the organization, permeating each level and department, creating a culture that contributes to the overall goal of valuable and useful information that can drive business decisions. It is no longer enough to manage information technology through the CIO and his or her department alone, it must be enterprise-wide.
Empower Your People
Yet another imperative piece of the data management puzzle is to make sure you are empowering business people with tools that give them the freedom to discover, prepare, analyze and share information through self-service capabilities. This is the best way to enable business agility, speed value realization and make business people accountable for their data.
Today’s data deluge demands that CIOs and CDOs show leadership and take charge of the information strategy and architecture in their company. The technology is better faster and stronger, but the principles are tried and true: by reinvesting in enterprise architecture, implementing a data governance program and empowering business user self-service they can help fulfill the potential of data to be a strategic corporate asset. With information easily accessed, analyzed, and shared for evolving enterprise needs, companies can run live and run simple.