Organizations are taking note of the power of building a data fabric, as enterprise shifts towards sleeker, holistic data platforms in an effort to adapt to the advancing tech environment.
The term “data fabric,” although relatively new, is just another way to address a problem that has been plaguing enterprises since the dawn of Big Data. For years, companies have struggled to fully manage and integrate their data solutions. According to a TDWI Pulse Report, 83 percent of companies have access to/use only 25 percent or less of their data. These issues are only going to be exacerbated as the amount of data we collect continues to scale, reaching upwards of 175 Zettabytes worldwide by the year 2025. Considering all of this, coupled with stagnating IT budgets, companies are searching for ways to consolidate their data solutions, streamline operations and cut costs. But is data fabric the answer to our woes? Or is it merely a fabrication of false hope?
Different solutions can go into creating a data fabric, but for it to be worthwhile and most effective, organizations need to understand the importance of having this interwoven pattern of technologies and tools fully integrated across the organization, under one common infrastructure. Once established, the data fabric essentially serves to create a throughline for the organization’s data ecosystem, tying together storage, preparation, analytics, visualization, high-performance data processing/computing, and access.
Why Does it Matter?
The rate of technological advancement — especially in the data management space — has been astronomical over the last five years. Enterprises find themselves in transit between legacy physical servers and cloud storage, all while streaming data in real-time from various sources in a wide array of formats and file types. These changes provide many unique challenges that can be difficult to navigate without the right data platform. This constant state of flux is the new normal, as technological advancements show no signs of slowing down. Enterprises need to not only adjust to the current evolving data ecosystem but future proof for what tomorrow will bring.
At the core of all of this has to be a strong foundation for building around, and adapting to various technologies, architectures, and frameworks. That’s where the idea of constructing a data fabric comes into play. Thinking about interconnectivity, ease of access, clean reliable data and data governance, it cannot be an afterthought. Companies that try to implement a patchwork approach will find themselves unable to adapt, adding new layers of complexity to their data ecosystem each time a new piece of technology is introduced.
We’re already seeing this in the current marketplace. As the TWDI report suggests, a large portion of companies is unable to fully utilize their data. Whether due to issues navigating the hybrid cloud environment or simply lacking the data preparation tools to tackle the volume, veracity, velocity, and variety of data available, companies are struggling to keep pace. Additionally, data deployment is quickly becoming a top concern for organizations. It’s not only important you are preparing your data correctly, but you’re able to get it into the right hands. Data is driving decisions and more than ever before… people need immediate access. That means toolsets that are user-friendly for everyone who touches the data.
A strong data fabric can help with all of that, allowing your company to scale your data infrastructure without fear of it collapsing in on itself.
Real Deal or Fabrication?
There is undeniable value in building a strong data infrastructure. Having the ability to inject, prepare, distribute, and visualize various types of information has never been more important.
Companies have been a bit slow to adapt, but they are finally starting to see the value in building a strong data fabric. The challenges of operating in a hybrid cloud environment with multiple forms of IoT technologies delivering a veritable cornucopia of different file types have illustrated the importance of having a flexible data platform. This will only become more important as organizational pursuits of business applications leveraging Artificial Intelligence, machine learning, and real-time and predictive analytics, drive an even greater need for vast quantities of clean usable data.