Automation Compliance Data Lineage Data Quality

Expanding your business using External Data

The concept of businesses has been around for as long as we can remember. Some businesses have outlived quite a few countries across the globe, and still, continue to register profits to this day. Japanese construction company Kongo Gumi was founded in 578 AD and was dedicated to the building of shrines thousands of years ago, and still stands as an organization. Having carried out operations for thousands of years, one can only imagine the amount of internal information and statistics they have recorded over their numerous years of operation. Although we have only recently discovered ways to use internal data to our benefit, businesses that have been around for so long have an inherent advantage when it comes to the internal data they possess.

The edge these companies have, over startups and new businesses, is not limited to companies that are thousands of years old. With the kind of technology available today, even a business that was founded a year before its direct competitors must have access to considerably more internal data. Businesses can ascertain beneficial processes to improve effective marketing, help boost sales, and make smarter business decisions due to the insights provided by their internal data. In the age of metadata prevalence, smaller and newer businesses have a deep-rooted disadvantage.

Nevertheless, the abundance of data that we speak of today encompasses not only internal data collected by a business for running and improving itself but also consists of data generated outside the four walls of its processes and operations. If data were to be compared to a pie, external data is probably the pastry base; looks good and completes the pie but is nothing without the filling.

Advantages and drawbacks of using external data

Data collected from third parties can be linked to internal data to obtain keener insights and help build more solid predictive models, and the potential benefits of this are often missed. An example of this would be the drastic changes in consumer behavior because of the Covid-19 pandemic, changes that rendered past predictions and run-of-the-mill business models unsuccessful. Just the right amount of foresight could have been, and still can be, the reason your business flourishes in the volatile markets of today.

Unlike businesses that carry out their operations and simultaneously collect internal data for later use, organizations that operate with the sole purpose of collecting information can maintain highly consistent data of high quality. External data providers are judged solely based on their data, so one can expect quality and quantity, aiding the data discovery process.

External data providers tend to keep a watch over the industry itself. Whether they are in a contract with you or not, high-level data on competitors should be available to you. Apart from enabling you to make direct comparisons based on historical data or otherwise, these data providers can offer tailored services that help you benchmark KPIs against rival organizations, paving the way for growth in the future.

Data-driven organizations are at the forefront of the expanding data ecosystem that the world is coming to terms with. While the old-school manager will still view the use of statistics as a job for the IT department, modern businesses can quite easily go overboard in the hunt for external data, as finding business-critical external data can be expensive, especially if you don’t know where to look. Using external data from multiple sources also works against you, as various sets of data might not match up due to different sources, resulting in erroneous outcomes that business decisions should not be made upon.

Finding the right data is only a part of the problems you can face with external data. A lack of data literacy in your organization would make it tough to convert statistical data into useful information. In turn, linking internal and external data turns into a different ball game altogether. One requires a solid, structured plan at the very least to make the most out of external data.

Applying external data to your business’ benefit

Extracting value out of external data takes more than just a primary assessment of the current data environment. Apart from knowing just how able your environment is to take on more data, you must have an adaptable data framework. To meet the requirements of successfully integrating and exploiting external data, an organization needs to establish data governance. As an executive of your organization, you are responsible for the direction in which your business goes, making you a core part of your data governance policies. While the data you have can suggest where you would find insights, it is best monitored and controlled by human thought.

Every step along the way to establishing data governance is of utmost importance, right from the discovery of the data assets to data cataloging and classification. To find the best external data to support the direction in which your internal data points you, there can be no mistake in finding or linking the data required. Moreover, the use of only human resources limits your organizations’ ability to achieve data governance, and the help of artificial intelligence to help automate the process brings about the added advantage of scalability. Not only does this help businesses of any size but contributes to controlling metadata management costs effectively.

By introducing alternative datasets into a closely governed data environment, your organization gains keen insights concerning the most current markets, a virtue of using more regularly updated external data. In turn, the availability of a vaster range of data, both internal and external, assists in carrying out more effective business decisions, fueling the right kind of growth for your company, whether your focus is to maximize profits or boost operability and versatility for a better future position in the industry.

Data Governance with Global IDs

At Global IDs, we endeavor to improve the field of enterprise data management by focusing on the right aspects of metadata management to promote constant business growth as a result of realizing the best possible insights. These insights can be realized with increased efficiency when the data governance is driven by the data itself. Our advanced algorithms link physical data to business concepts across the industry and can help add value with the use of external data as they automatically identify critical data elements. For growing businesses, the automation of data governance processes helps scale data governance, ensuring quality insights and top-notch enterprise data management.