Managing data effectively has always been important for any company. Businesses have always needed to know which months see higher demand or which sales channels convert best. But with technological advancements, the amount of data available for analysis can be enormous.

Many consider big data to be the oil of the 21st century because effective data management allows any company to unlock its full potential. Not only can you know the smallest details about any area of the business, but you can do so with complete accuracy.

Interpreting information correctly is vital for good business results. Data doesn’t lie—but you need to know how to read it in order to make the right decisions, verify hypotheses, or answer key questions. This requires extracting data efficiently, streamlining decision-making, and focusing on the information that’s truly relevant.

This is a complex task because the amount of data handled by businesses has multiplied. And it could be even larger—so good data management starts with filtering which data should be collected: which adds value, and which doesn’t?

Not only is the amount of data growing, but the number of data sources is also multiplying. That’s why identifying what is relevant, establishing a fast extraction process, interpreting data correctly, and providing quick, reality-based responses are key success factors.

A trendy new term has been coined for this process: Smart Data. In other words, it’s not enough to have a large volume of data—you need to squeeze all the value out of it. That’s what truly matters, because a huge amount of data without context, interpretation, or cross-referencing can simply be noise.

Managing data effectively is a real challenge, especially for SMEs, which may have more limited capacity to bring in the right people, tools, and processes. But it’s far from impossible.

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How to Implement a Proper Data Management Process

For knowledge to be useful in a company, several key aspects must be kept in mind—always starting from one basic premise: compliance with legal requirements, protection of personal data, the principle of confidentiality, and ethics.

From there, a proper data management process is within reach for companies and businesses of all sizes, regardless of how much data they collect or the resources available.

1. Put people at the center of the strategy

The customer must always remain at the heart of data management. The goal is to make decisions—not to collect data for its own sake—so you avoid gathering unnecessary information that adds no value.

The “customer” at the center isn’t always the end consumer. Depending on the type of data being collected, in which areas, and for what purpose, the “customer” could also be a supplier or an employee. As mentioned, people must be the focus. This also means having specialized professionals in data management, analysis, interpretation, and/or visualization—because data and technology are useless without someone to apply them.

2. Seek a global perspective

Don’t collect data just because you can. More is not always better. Instead, aim to gather information from all available sources, because these can complement and refine each other. Once collected, you can process and analyze the data—but it’s important to get multiple perspectives, just as it’s better to consult different news sources to avoid bias.

Also, business processes should be oriented toward data analysis. Every area of the company should understand its importance, both to facilitate collection and to use the data for better decision-making.

3. Use the right tools

It’s physically impossible to process large amounts of data without technology—and even if it were, it would be far more expensive and less effective. That’s why it’s essential to rely on data analytics tools to gain the deepest possible insights.

A good Business Intelligence tool should be powerful, up to date, and easy to use. Its design should go back to point one: people at the center. The user experience is as important as the information itself, so that it can be accessed, worked on, and shared effectively.

Equally important is having a provider who supports the client throughout all stages of implementing the technology and guides them through the process.

4. Embrace evolution

Information is dynamic, so the system must always be monitored to ensure the quality, reliability, and currency of data, sources, information, and results.

In a constantly changing world, what works today might be improved tomorrow. Innovation means being open to new data, sources, and technologies that can improve processes and results. The best approach is to set up mechanisms that allow you to incorporate any innovation that enhances the process itself.

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Efficient data management in a company is a clear competitive advantage, with a direct impact on the bottom line. There’s nothing better for a business than knowing every detail of its activities, competitors, customers, processes, suppliers, and both immediate and future needs.