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Data is the currency of the modern economy. Last year, every human on the planet created an average of 1.7MB of data per second. Some estimates show that 7.5 septillion (that’s with 20 zeroes) gigabytes of data are generated daily across the globe (sources: Priceonomics and Tech Trend). 

There are a lot of amazing tools available in the market to capture and store data in a way that is fast, easy and inexpensive. But for most organizations, the hardest part is transforming that data into meaningful information and actionable insights. While subtle, the difference between data and information can represent whether you are making the right decisions rooted in fact or the wrong ones based on assumptions and potential misinterpretation.   

Data vs. Information: Dissecting the Difference
Factual by nature, data is raw and unprocessed containing no meaning on its own. As I like to say, “Data without context is just data.” It represents raw materials, like lumber or siding used to construct buildings or the individual parts used to run a car. In technology terms, data is the input in a system. It is either qualitative (“what type?”) or quantitative (“how much?”) and delivered in a structured (CSV file) or unstructured (PDF) format. 

In contrast, information is the output that presents contextual meaning from the data provided. It is the delivered product which provides justification for why the data was acquired in the first place. There is no information without data, but ironically data on its own may not result in usable information that can help shape business strategies. 

Information can be delivered many ways, and the most common is in reports and dashboards. Given the intent of information is to make more informed decisions, it’s important to provide metadata along with the information that helps those who view it—from employees and C-level executives to customers—to better understand the meaning and context around the information. 

How To Get Information from Data
Businesses cannot effectively operate without quality information. As a result, it is important to have solid processes and procedures for turning data to information. Below are the three key components to bring your data to life: 

  1. Experienced Data Architects and Analysts
    Data can be complicated, convoluted, misleading and tedious. As a result, it’s important that organizations either staff or consult with experienced data architects and analysts. They are solely responsible for the identification and acquisition of data (the input) as well as the delivery of information (the output). In addition, they will accommodate for any conflicts in sources of record, address any data quality issues that might exist and ensure data is stored and formatted in a manner suitable for the type of information extracted.

  2. Data Governance and Metadata
    Borrowing from an earlier example, a house is only as good as its foundation. The need for policies that govern data quality, compliance and accessibility cannot be overstated nor an afterthought. Unfortunately, this is a step that is all too often overlooked. An organization’s data governance policies define all aspects of how data is managed and converted to information for improved decision making.

    Tightly coupled with data governance is the definition of metadata. Metadata is defined as being the data that describes the information presented. It is critical in assisting the consumers of information to understand exactly what they are seeing, helping them to avoid any potential misinterpretation.

  3. Executive Sponsorship
    Data and its transition to information should be a cultural mainstay of any mature organization that relishes fact-based decision making. Executive sponsorship is the only way to ensure informational and actionable insights are woven into the day-to-day operation of the business. Whether this be through the establishment of a Chief Data Officer or another executive, leadership will set the tone on how the organization behaves and consumes information. 

The combined components above give organizations the power to transform data into meaningful information that can shape business strategies, drive critical decisions, inform marketing, and guide better engagement with customers. The result is a data-driven organization that turns information into value. 

It’s time to unlock that value, and we can help. Don’t worry; we got this.