Guide to a Modern Data Strategy (2024)

Data has emerged as the cornerstone of business growth. Traditional data strategies no longer suffice in an environment where enterprises grapple with a deluge of real-time streaming data and management tasks such as database provisioning, patching, configuration, and backups.

The challenge lies in integrating the data lake, data warehouse, and all purpose-built data stores into a coherent, secure, and well-governed system. This is where a modern data strategy comes into play, offering the perfect blend of data lakes and purpose-built data stores.

A modern data strategy enables businesses to dismantle data silos, empower their teams with analytics and machine learning capabilities, and manage data with the necessary security and data governance controls. However, crafting an effective data strategy is a monumental task that demands the construction of a robust and scalable data infrastructure and the cultivation of a data-driven mindset within the organization.

This process begins with migrating data and workloads to the cloud, managing databases, developing data-driven applications, analyzing data, and initiating innovation with Artificial Intelligence (AI) and Machine Learning (ML).

The modern data strategy rests on five key pillars. These include the data itself, the tools used to manage and analyze the data, the analytics techniques employed, the collaboration between different stakeholders, and the documentation and auditing of the data strategy. Let’s delve deeper into each of these components.

1. Data: The Foundation of Your Strategy

The first and most fundamental pillar of a modern data strategy is the data itself. However, the subsequent advice will be futile if your data isn’t securely stored, well-maintained, and primed for use. The strategic value of your data must be built on a robust foundation of enterprise data management, which includes integrating and processing your data, validating its quality, governing its use, and auditing the processes that impact it.

Once these basics are in place, an enterprise data catalog is highly recommended as a crucial component of a data strategy. You can’t strategize around data if you don’t know what data you have. Data catalog tools are particularly useful for making data available to business users with detailed and descriptive metadata.

Moreover, breaking data silos to unify your organization and accelerate insights are the real important factors to a successful modern data strategy.

2. Tools: The Instruments of Your Strategy

The second pillar of a modern data strategy is the tools used to manage and analyze the data. Data management tools are almost always the domain of IT. There are some lightweight data quality and data integration tools designed for business users, but data management remains largely a behind-the-scenes function.

IT often also deploys the BI tools used to create data visualizations, dashboards, and reports. But data and business analysts may have their own preferences and choose different tools. That can work well so long as we put controls in place to govern data access and usage.

A good data strategy embraces that diversity but with sensible limits. In this case, we can ask another question: What tools are appropriate to use?

3. Analytics Techniques: The Methods of Your Strategy

The third pillar of a modern data strategy is the analytics techniques employed. Data visualization is a common example. We may also find uses for predictive analytics, text analytics, sentiment analysis, and cluster analysis, among other advanced analytics techniques. They can be powerful and useful but need careful oversight. Without it, we may fall foul of data governance and privacy laws.

Predictive analytics, for example, may show business value in optimizing equipment maintenance cycles. That’s an uncontroversial use. But predictive techniques could also be used to help automate hiring or manage marketing promotions. In those cases, employees and consumers may have concerns about the reliability, fairness, or openness of the process.

A data strategy has to recognize that governing only data and tools may not suffice. We need to understand — and train people to understand — that not all analytics techniques are neutral. Some use cases, especially ones that involve personally identifiable information, won’t be justified by their business ends.

4. Collaboration: The Teamwork of Your Strategy

In modern businesses, the use of data is typically more collaborative than in the past. Increased data literacy and easier-to-use tools mean more people can take part in analytics, as well as technical fields like data preparation and data quality.

Even closely controlled processes, such as data governance and the development of master data definitions, can be crowdsourced. For example, doing so can ensure that product names, error codes, and managed processes reflect the reality on the shop floor in a manufacturing company. Collaboration on master data can also avoid that most frustrating customer service response: “There’s no code for that.”

5. Data Culture: The Heart of Your Strategy

The final pillar of a modern data strategy is the data culture of an organization. This is the most difficult aspect to change, but it’s also the most rewarding. A strong data culture can make the difference between a company that uses data to inform decisions and a company that is truly data-driven.

A data culture is not just about having the right tools or the right data. It’s about how people in the organization perceive, value, and use data. It’s about fostering a mindset where data is seen as a valuable asset, where data quality is everyone’s responsibility, and where data-driven decision making is the norm.

Building a data culture requires commitment from the top. Leaders need to set the tone by demonstrating the value of data in their own decision-making processes. They need to invest in data literacy programs to ensure that everyone in the organization has the skills to understand and use data effectively. And they need to promote transparency and openness, so that everyone has access to the data they need to do their jobs effectively.

A successful modern data strategy is built on these five pillars: data architecture, data governance, analytics techniques, collaboration, and data culture. By focusing on these areas, organizations can harness the power of data to drive innovation, improve decision making, and create value.