Streamlining Data Evolution in a Rapidly Changing World

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In the last few years, the availability of data and the way we interact with it has seen significant growth and change. We live in an increasingly digital and data-driven world, and with rapid technological advances, data production and collection have evolved. As the world continues to accelerate, it is important to tackle the challenges that come with evolving data sets in a way that is safe yet efficient instead of using outdated programs and mainframes.

Organized and accessible data is at the core of every successful company, and data management continues to be a priority as the business landscape evolves. With 2021 marking a record year for mergers and acquisitions, businesses must now adopt new technologies to ensure corporate data merges effectively and within compliance guidelines.

As these organizations merge, they are now tasked with bringing new datasets together in a way that allows them to conduct seamless operations, such as attracting and retaining customers, improving services, predicting trends and more. In doing so in large-scale situations such as these, it’s easy to lose quality, consistency, value and time. It can also create  inefficiencies and risks, particularly when businesses do not have a comprehensive understanding of what data they have, where it is stored and if that data is safe. 

If data is unsafe or unorganized, it can jeopardize the well-being of an entire organization. Data remains one of the most valuable assets to a company. Through this, they are allowed better business insights to aid company success. Key pieces of data can include employee records, customer information, transactions, etc. When data is not secure, organizations can run the risk of that information being lost or falling into the wrong hands.

To find a solution, first identify the problem.

During migrations, data across multiple systems can be fragmented and disjointed. When stored in separate locations, data can impact a company’s resources by creating caches of secondary data that negatively impact business operations and storage capabilities. If data fragmentation across legacy, product-focused and siloed systems goes unaddressed, it can become difficult to leverage data in any meaningful way, let alone obtain actionable insights. 

Incomplete data sets are another common challenge companies face when collecting and moving data, as they can often be costly and time-consuming to address. Data sets are incomplete when they are missing values and context; it may have been complete at one point in time, but as businesses evolve and the needs for data change, it needs to be augmented to make small changes or generate new data points. 

How do we solve the problem?

When working to evolve data sets that are either fragmented or incomplete, developers can benefit from alternative platforms to bridge data between different systems and present it in a unified view. An example of this could be low-code – software that builds applications and processes with little to no coding necessary through simple drag-and-drop features. These platforms treat data like an API to query it, understand it and join it with other data. This provides a more simple and user-friendly process instead of using complex programming languages that introduce the possibility of harming the data. 

Low-code allows new applications to interact with legacy data without the need to modify or replace it. Replacing legacy with new systems can take years. Instead, low-code leverages the legacy data by combining the systems with new technology. 

In addition to combating cost and time, low-code technology also provides flexibility to easily adapt and reuse components. Given the fast pace at which the world is moving, it is crucial to be agile enough to constantly adapt with evolving times and technology. Low-code solutions allow integrations to be changed quickly enough to stay up to speed with new operations, processes and regulations. 

In such a fast-changing, digital-driven world, having access to the right data at the right time is crucial. That is why, as data evolves, it must be brought together in a reliable and efficient way that creates a powerful asset, not a compliance challenge. 

About the Author

As one of Appian’s earliest employees, Adam Glaser built a career from entry-level to senior technology executive, leading the product team from startup through IPO and ultimately to industry leader in a crowded and well-funded market. With nearly two decades of experience delivering enterprise web and mobile software, Adam is passionate about building, leading, and scaling high-performance software development with strong emphasis on predictable delivery and effective go-to-market. Today, Adam oversees the entire product development team consisting of product management, user experience, and training. 

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