Even before the IT elements of data optimization begin, aligning organizational culture around a data-driven mindset will be a major challenge. Making the case for data optimization is important.
After years of new technologies being introduced into IT departments and new roles being created to manage them, most enterprises now operate in siloed worlds. At the same time, we’ve seen a rise in the value of data in powering today’s businesses.
This reality has created a perfect storm in which siloed IT departments make it increasingly difficult to maximize the value of data. Today’s technology professionals are left trying to navigate data optimization across complex environments.
Compounding this challenge is a simple fact: The larger the enterprise, the more opportunities for data silos to exist. These silos often collect, curate, and store datasets, leading to overlapping and duplicate data across the IT environment. To optimize data, these inherent issues need to be addressed once and for all.
How to Achieve Data Optimization
Achieving data optimization isn’t just about removing silos and putting tools in place; it’s about instituting a data-driven mindset. The following are some best practices you should
consider in order to achieve data optimization at the IT level and throughout your business:
- Shift the organizational mindset: Even before the IT elements of data optimization begin, aligning organizational culture around a data-driven mindset will be a major challenge. Getting employees across the enterprise to understand the benefits and making the case for data optimization will be difficult, but
it’s important. - Prioritize a governance strategy: When thinking about maximizing the value of data, it’s critical to implement a proper data governance strategy. The first step in this strategy is eliminating redundant data feeds. Eliminating these silos will lead to a reduction in storage, processing, and the total cost of ownership. This won’t be an easy task—the volume and velocity of data increase every day—but building such a strategy helps expose the costs, benefits, and risks associated with your mission-critical data.
- Optimize across the tech stack: Once leaders understand the foundational elements of a data governance strategy, implement data optimization procedures and processes extending down into the application and database layers of the infrastructure.
- Optimize data integrity: Digital ledger technologies can help optimize the integrity of your data, ensuring your data is a source of truth and helping to make sure it hasn’t been tampered with in an unauthorized fashion. Historically, this has been called master data management. These days, it’s the same thing with a distribution of decentralized database nodes.
IT leaders need to bring their staff up-to-speed on the latest data optimization technologies and practices. The first step is getting everyone to understand the benefits, which means getting them to buy in to being truly data-driven. The next element is understanding how optimization reduces the total cost of ownership by removing the redundancies introduced by siloed IT departments. If tech pros can succeed in these areas, they can maximize the value of their data—not just today but into
the future.