Enterprise data and analytics are unarguably the most significant differentiators for any successful organization. Irrespective of the size of an organization, from a brick & mortar to a booming enterprise, data is the most valuable organizational asset, especially during these times where organizations are bombarded with a plethora of digital channels.
However, is that data worth it if it isn’t available when you require them the most or even worse if it’s outdated, missing, or inaccurate? Data can be both a boon and bane if it isn’t utilized correctly. Therefore, it is crucial to implement a definitive Enterpriser Data Management Strategy that is driven by a robust Enterprise Data and Analytics practice.
What Does Enterprise Data Management Strategy Mean?
It is the process of planning and creating strategies required to handle data created, stored, and managed by the organization. Enterprise Data Management has become a priority for organizations; to meet the strategic objectives of enterprises is becoming more necessary than ever to have quality data.
Ways to Strengthen Your Enterprise Data Management Strategy
Let’s look at some ways that are key in building effective and lasting strategies for managing data:
1. Identify business objectives: this might sound a bit off-track, but the reality is data can’t serve its purpose if business objectives don’t match. Therefore, as a preliminary step in building a data strategy, it is crucial to explore business requirements and challenges and then use that information to define business objectives.
2. Understanding the potential of existing data: Research suggests that we produce over 2.5 quintillion bytes of data every day, and there are no signs of slowing down. Isn’t that mind-boggling! With the massive proliferation of digital channels and the data created via those channels, e.g., your customer preferences, behavior including your in-house operational data, are unimaginable. The chances are that you might not analyze the existing data to its full potential. Therefore, it’s crucial to analyze the existing data within the organization and identify opportunities to up-sell or cross-sell products and improve the overall efficiency.
3. Create robust data processes: It is crucial to have a complete collection, storing, and distributing the data. Here are some essential questions under each process that can help you align your data.
- What should be your data sources?
- Will you need access to both external and internal assets?
- Do you need structured data, unstructured data, or a combination of both?
- How will the data be collected?
- Is this a task that will be done manually as needed, or will you set up extract scheduling?
- Where should I store my data?
- Should I use XML, CSV, or relational databases for structured data?
- Do I need a data lake for unstructured data?
- How should I keep my data secure?
- How should I make access to data and analysis easier for the end-user?
- How can I communicate any data insights?
4. Adopting data governance policies: Data governance sets policies and procedures to ensure data is consistent and effectively used throughout an organization. It helps avoid errors, blocks potential misuse of sensitive data, and aligns your business with data-related legislation. Organizations often misunderstand assuming data governance comes only with technology. However, data governance is much more about people in terms of organizational change management than technology. Having robust and flexible data governance operating model can ensure the success of data as a strategic asset.
5. Managing metadata: As per Gartner’s prediction for 2024, organizations that use active metadata to enrich their data will reduce time to integrated data by 50% and increase the productivity of their data teams by 20%. Managing metadata and creating a consistent business information infrastructure is critical for referencing, accessing, and consuming business data. Organizations often miss out on keeping basic facts checked, including- who owns specific information, how important that information is, and how relevant it is to the business. Metadata helps to keep the above information.
Final Thoughts on Strengthening Enterprise Data Management
Data is necessary to stay competitive in today’s economy, but collecting, analyzing, and managing data is challenging. Therefore, creating a strategy for managing data is one of the fundamental principles of data management. Reaching a stage where data policies are applied across the organization is the first step to initiate and improve your data management.