“You can have data without information, but you cannot have information without data.” — Daniel Keys Moran
Without data, you have nothing. Data makes everything easier. Every technology implementation needs to begin with good data. Without good data, efficiency decreases, because employees can't find the information they need to support business operations in disorganized data sources.
As organizations grow, evolve and take on additional global market opportunities, change will be the constant for the people, processes and technology supporting business and marketing operations. Digital transformation plays a critical role in this change, serving as a focused center for content and operations management. Metadata, workflow, technology, governance and cultural context all affect operations and organizations must address them. Your data supports your technology, and the technology supports your process and people in the organization.
Alongside your program and product roadmaps, you also need a data roadmap. Data is growing exponentially. Quality data supports new technology platforms that provide opportunities for more effective communication, engagement and risk management. But you'll never obtain the full value of data until you establish business rules, policies and governance on how the organization collects and analyzes internal and external data.
Related Article: The Difference Between Quality of Data and Data Quality
Conduct a Data Assessment
A data assessment allows you to establish your current state of data and identifies gaps in your data structure. A data assessment is a survey of your current data that allows organizations standardize and build a foundation. Any technology implementation becomes easier after that. Conducting a systematic data assessment gives an organization insight into where it stands in managing its information effectively. It is the first step in creating a roadmap to consolidate data from various systems and apply consistent metadata.
These activities maximize efficiency, security and return on investment (ROI). All of this is done to determine whether the organizational data and content environment supports organizational objectives and meets regulations. The data assessment should explore:
- What is your data?
- What information is being captured in your data?
- What format is your data?
- Where is your data?
- Where is your data stored?
- Which teams are responsible for data storage?
- What are you trying to do with your data?
- What is the end goal for your data endeavor?
- Search? Analytics? Consumer Experience? AI?
- How will you access (identify, retrieve, distribute) your data?
- What will your data look like?
- How will you distribute your data?
- How are you able to use your data (rights management)?
- What state is your data in?
- What type of data cleansing needs to take place?
Data is proliferating, and that growth is will only continue exponentially. As it multiplies, organizations need refreshed, enterprise-level approaches to systematically create, distribute and manage data.
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Metadata Makes the Difference
Metadata matters. It is not just data about data, but is the spirit of an intellectual or creative asset. Metadata is the descriptive, administrative and structural (technical) depiction of an asset. Metadata is a strategic imperative in the endeavor to effectively manage a company’s knowledge. The successful implementation of any content-related strategy requires a holistic metadata schema at its base that is supported by technology, people and process. It increases the ROI of a content system by unlocking the potential to ingest, discover, share and distribute assets.
Metadata isn't easy. It takes time, money and resources to make it all work. Metadata is the key that unlocks the commercial potential of information, data and intellectual or creative assets. And yet, metadata is an “asset” unto itself — and an important one, at that. It provides the foundation and structure needed to make your assets more discoverable, accessible and, therefore, more valuable. This is meaningful data to have.
Related Article: Using AI for Metadata Creation
Roles, Responsibilities and Governance
Data requires management, and so controls must be placed on how, when and who can create, modify, delete and use data. Data needs governance, and if we understand that data is something that has value to the organization, then it is clear that controls should be placed on access to that data. If controls aren't in place, or they are insufficient, then the consequences can be embarrassing and costly. The company could sustain damage to its reputation and could even result in the loss of trust of clients or consumers.
Governance is a process and framework to ensure that program goals are met both during implementation and for the future. Ultimately, it is the only way to manage and mitigate risk.
The word governance is often misunderstood as a set of rules, when in fact it refers to practices of organization as well as processes for interaction and decision making. To be effective, data governance must be considered as a holistic corporate objective, going beyond IT governance; establishing policies, procedures, and training for the management of data across the organization and at all levels.
Related Article: DAM Governance Practices for the Long Haul
Data is the foundation for content, and all that organizations do in business and how they interact with their customers. As data multiplies, organizations need enterprise-level approaches to systematically create, collaborate and manage data.
Embrace your content and understand all that you can about what it can do. Never stop asking questions as a means to ensure data integrity. Creating the whole solution — and connecting it throughout your ecosystem — means your digital assets can be part of this innovation by generating revenue, increasing efficiencies and enhancing your ability to meet new and emerging market opportunities for your users.
Data is intimately associated with business transactions and in turn, associated actions by people. It demands all our attention. Data is not just a technical challenge: the way humans interact with systems and processes must also be considered, and good security is designed with people in mind. Data is in everything that we do and deserves our greatest care and responsibility in order to drive everything we will want to do in the future.