A Partnership Approach for Turning Data Into Insights
Many organizations are pouring time and money into data and analytics initiatives, only to remain stuck in first gear. Others can’t marshal the entire data estate to generate the insights they need for more intelligent decision-making and positive business outcomes.
There are several reasons why data initiatives aren’t living up to their potential business value. Among them:
1 – Data silos that impede cross-business-unit enterprise visibility. Those siloskeep critical data out of the reach of key business stakeholders and transformative digital initiatives.An IDG/HPE survey found that companies leverage only about half (49%) of their data sets to derive direct business value; 34% of the respondents said they are falling short of strategic data goals.
2 – People constraints created by the landscape of data silos. Because of these, analytics users and data scientists spend too much time trying to locate and integrate the right data, versus interpreting data to surface optimal business insights. Those with the most knowledge about the systems and where data resides operate from their own silos, further hampering insights and undermining intended business outcomes.
“The siloed nature of systems means we often have people operating within those silos who don’t communicate with each other, which drives inefficiencies,” explains Matt Maccaux, global field CTO – HPE Ezmeral Software. “We also have technical debt that accumulated as these systems matured, which makes the concept of modernizing these analytics systems and bringing data together a very expensive proposition.”
3 – Technical debt, accumulated through system updates and integration initiatives over the years. Although this prolongs system shelf life, it also creates a large quantity of custom code and logic, which, in turn, significantly increases overall system complexity. In addition, many of these workloads and systems are unable to run or be adapted to modern cloud-native technologies such as Kubernetes, microservices, or devops-like automation. This puts the foundation for data-driven business farther out of reach. Alternatively, organizations might stand up a modern environment specifically for data analytics teams but end up with yet another silo that begets additional complexity.
At the same time, many of these legacy systems remain crucial to business, today and for the foreseeable future. “You can’t just delete these systems unless you have something that has exactly that same functionality that is going to replace it,” Maccaux says.
Although some remain stuck, many organizations see what’s required to move ahead and maximize data’s full value. According to the IDG/HPE survey, this includes access to better analytics tools and services (cited by 61% of the respondents), seamless integration of multiple data sources (46%), and finding a trusted partner with high-performance-computing expertise (38%).
Having the right partner and platform is key to getting the most mileage out of the current data estate while recalibrating and reinforcing the organization with the tools, skills, and talent required to fully execute data-driven business.
