In today’s business environment, particularly the business-to-business environment, a great emphasis has been placed on digital transformation initiatives. According to Synergy Research Group, through the first quarter of 2020, corporate spending on cloud infrastructure services reached $29 billion, a 37 percent increase over the same quarter last year. Why? There are likely many reasons but one is clear. The coronavirus pandemic.
With companies moving mostly, if not completely, online during this time period, digital transformation timelines accelerated and, in some cases, inadequately rushed. Those who weren’t prepared when investing in SaaS solutions for such initiatives didn’t accurately identify their “non-negotiables.” All SaaS solutions must contain the ability to be flexible, personalize data, and scale. This comes down to the type of data model powering the software.
The best option is clearly the graph database.
In naming the graph database one of the biggest data trends, Gartner predicted 100 percent annual growth through 2022, showcasing its adaptability, flexibility, and potential across all industries, especially financial services, pharmaceutical, health care, telecommunications, retail, and government.
But, what exactly is a graph database?
Like a library where books are placed and categorized based on their content — sci-fi, biography, mystery, etc. — SaaS solutions store and categorize data sets. Relationships can be drawn between these categories via the database being used. When SaaS solutions are built on a graph database, back-end processes can be easily tweaked and relationships between different data sets are drawn, unlocking new insights. Conversely, relational databases have pre-defined relationships set up so they’re less flexible and unable to unlock those insights gathered via a graph database.
Social media sites were among the first to realize the power of the graph database. So, there could be more in common with your SaaS solution and Facebook than you may think.
After being originally built using a relational database, in 2009, Facebook did realize the scale to which they could improve its platform by moving it onto a graph database. Like other social platforms, Facebook did it so it can more easily communicate relationships between its different users and data sets.
So, bringing it back towards business use cases, organizations, for example, require flexibility, personalization and the ability to scale for its solutions within enterprise-critical programs, such as Governance, Risk Management, and Compliance (GRC). They need SaaS solutions to have the ability to change in accordance with today’s data-based processes in those enterprise-critical programs. And, the graph database does this better than any other type of database because all back-end processes work together in order to create new levels of flexibility and visibility for all users.
Additionally, because it unlocks insights in real-time, despite programs with a high number of necessary data relationships, like GRC, it adds new relationships easily without diminishing processes. With it, organizations can bypass a lot of manual spreadsheet work, saving time and money.
Though it does create additional data relationships and allows software and platforms to pull and reorganize data sets, it’s not necessary for every type of solution. But, for an enterprise-critical area like GRC or for a data-centric use case like social media, it creates the additional flexibility and visibility required by users and organizations, alike.
About the Author
Jon Siegler is the Co-Founder and Chief Product Officer at LogicGate. He has over a decade of experience in designing customer-centric enterprise risk and compliance systems, delivering value for organizations by reducing their risk, improving efficiency, and automating processes. Jon is driven by a passion to connect deeply with our customers’ problems in order to build an amazing product that makes the challenges of risk and compliance easier.
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