Streamlining data evolution in a rapidly changing world

In recent years, the availability of data and the way we interact with it has grown and changed significantly. We live in an increasingly digital and data-driven world, and with rapid technological advancements, data production and collection has evolved. As the world continues to speed up, it is important to address the challenges associated with evolving datasets in a way that is secure yet efficient rather than using outdated programs and mainframes.

Organized and accessible data is at the heart of any successful business, and data management remains a priority as the business landscape evolves. With 2021 being a record year for mergers and acquisitions, companies must now adopt new technologies to ensure that corporate data is aggregated effectively and within compliance guidelines.

As these organizations merge, they are now tasked with bringing new data sets together in a way that enables them to perform seamless operations such as attracting and retaining customers, improving services, predicting trends and more. . Doing this in large scale situations like this makes it easy to lose quality, consistency, value and time. It can also lead to inefficiencies and risks, especially when companies don’t have a full understanding of what data they have, where it’s stored, and whether that data is secure.

If data is insecure or disorganized, it can jeopardize the well-being of an entire organization. Data remains one of the most valuable assets for a business. This gives them better business insights to drive the company’s success. Important 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.

In order to find a solution, you must first identify the problem.

During migrations, data across multiple systems can be fragmented and disjointed. When data is stored in separate locations, data can impact a company’s resources by creating caches of secondary data that negatively impact operations and storage capabilities. If data fragmentation across legacy, product-centric, and silo systems is not addressed, it can become difficult to leverage data in a meaningful way, let alone gain actionable insights.

Incomplete datasets are another common challenge that businesses face when collecting and moving data, as they can often be costly and time-consuming to address. Data sets are incomplete if they lack values ​​and context; it may have been complete at one point, but as businesses evolve and data needs change, it must expand to make minor changes or generate new data points.

How do we solve the problem?

When developing data sets that are fragmented or incomplete, developers can take advantage of 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 required through simple drag-and-drop functions. These platforms treat data as an API to query, understand, and combine it with other data. This makes for a simpler and more user-friendly process instead of using complex programming languages ​​that introduce the possibility of corrupting the data.

With low-code, new applications can interact with outdated data without having to change or replace it. Replacing legacy with new systems can take years. Instead, low-code takes advantage of the old data by combining the systems with new technology.

In addition to reducing costs and time, low-code technology also offers flexibility to easily adapt and reuse components. Given the rapid pace at which the world is developing, it is crucial to be agile enough to continuously adapt to changing times and technology. With low-code solutions, integrations can be changed quickly enough to stay on top of new operations, processes, and regulations.

In such a rapidly changing, digitally driven world it is crucial to have access to the right data at the right time. That’s why, as data evolves, it needs to be brought together in a reliable and efficient way that is a powerful asset, not a compliance challenge.

About the author

One of Appian’s first employees, Adam Glaser built a career from entry-level to senior technology manager, leading the product team from startup to IPO and ultimately to the 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-quality software development with a strong emphasis on predictable delivery and effective go-to-market. Today, Adam oversees the entire product development team which includes product management, user experience and training.

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