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5 Pillars of a Modern Data Strategy
Data is an invaluable asset that enables modern businesses to make informed decisions, uncover market trends, anticipate customer needs, and optimize operations. But without a well-defined data strategy in place, many organizations struggle to realize the full potential of their data. As businesses seek to drive greater innovation and accelerate growth, it becomes increasingly critical that they implement a modern data strategy supported by data products.
What is a modern data strategy?
A modern data strategy enables organizations to harness the full potential of their data assets and drive meaningful business outcomes. It starts with a clear understanding of organizational goals and aligns data initiatives accordingly. Modern data strategies incorporate five key components:
- Data governance:
Robust data governance practices are an essential part of a modern data strategy. Not only do they ensure data quality, integrity, and security, but they also form the foundation for reliable and trustworthy insights.
- Data collection:
Organizations collect data from a myriad of diverse, internal and external sources. That’s why it’s critical that data collection is agile and scales as data changes over time.
- Data integration:
Modern data strategies also prioritize data integration, allowing for the seamless consolidation and analysis of data across various systems or platforms.
- Data transformation:
By transforming raw data into actionable insights using advanced analytics tools and techniques, organizations can empower decision-makers across all levels of the organization.
- Data culture: modern data strategies foster a culture of data-driven decision-making by encouraging employees to embrace data and use it to drive innovation and optimize processes.
How have data strategies changed over time?
Just as the role of data has changed over time, data strategies have changed, too. In the early days, many companies viewed data as a byproduct of business operations. They stored it in silos and overlooked it in the decision-making process. At this time, few organizations employed Chief Data Officers (CDOs), leaving the management of data to the IT organization.
Fast-forward to today and you’ll find that modern data strategies are much more sophisticated because organizations understand that a well-defined data strategy is crucial for remaining competitive in the rapidly-evolving digital landscape. Modern data strategies encompass a wide range of practices and technologies that enable organizations to collect, analyze, and use data in unprecedented ways. These strategies signal a shift away from approaches that focus on simply managing data to ones that acknowledge the transformative potential of data and its power to make data-driven decisions and drive innovation.
How to build a modern data strategy
- Understand your organization’s goals
Building a modern data strategy begins with understanding your organization’s goals and objectives so you can align your data strategy with your overall business strategy. It also involves conducting an assessment of your current data infrastructure, including the sources where your data comes from, how and where you store it, and how you make it accessible to people across the business. Chances are, you’ll uncover gaps and/or opportunities for improvement in each of these areas.
- Define your data governance framework
Once you have a clear picture of your goals, objectives, and infrastructure, you’ll move on to defining your data governance framework. You’ll need to document policies for data ownership, security protocols, and compliance measures. It’s also a good time to establish data quality standards so that you can ensure your data remains accurate, reliable, and trustworthy.
- Determine your tools & technologies
With this groundwork in place, you’ll now want to determine what tools and technologies you need to support your modern data strategy. It’s likely that, over the years, your organization invested in numerous tools and technologies to solve specific data challenges. For example, many organizations invested in legacy master data management (MDM) solutions to help solve challenges related to data quality and data mastering. And while those investments were significant in both time, money, and resources, now is the time to re-evaluate your approach.
Today, organizations are looking to AI-powered data products as a way to better manage the complex and dynamic nature of data. Data products differ from traditional MDM solutions in a number of ways. They reduce manual effort by automating the processes to match, standardize, and enrich data. And, they employ a blend of AI and human intelligence instead of rules, making it simpler and faster to curate, match, enrich, and clean the data. Data products also adopt a decentralized model where they manage and curate data across various teams and departments, and distribute it in a way that aligns with their specific needs and expertise. Using this approach, data products empower individual teams to assume greater ownership and control over their data so they can adapt and optimize their data practices based on their unique requirements.
As you evaluate your current data stack, it’s important to remember that you don’t need to “rip and replace” all of your existing technologies. Many times, as is the case with data products and traditional MDM, the two can co-exist, with each one focusing on delivering value against different use cases.
- Monitor, collaborate & communicate
The last steps when building a modern data strategy involve collaboration, communication, and continuous monitoring. To foster a culture that promotes data literacy, it’s important that you encourage cross-functional collaboration across the business. As well, through communications and training, you can onboard your organization to your strategy and secure their buy-in and support. Finally, by regularly assessing the effectiveness of your strategy, you can remain agile, identify opportunities to adjust, and more easily embrace new and emerging technologies as they emerge.
Building a modern data strategy is an ongoing process that requires adaptability and agility. When done right, organizations can realize the true potential of their data and use it to work smarter and exceed business goals. To learn more about how Tamr data products support a modern data strategy, please schedule a demo.
