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.
Partnering for success
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. A partner such as HPE has global expertise, proven methodologies and intellectual property (IP), and foundational technology platforms. In combination, these can help organizations operationalize modern data initiatives while fully opening up and capturing the value of legacy data and systems.
An HPE partnership can help jump-start stalled data initiatives by delivering the following:
Access to specialized talent. Successful data initiatives require diverse talent, from technologists schooled in legacy data warehouse and reporting capabilities to experts in newer areas such as artificial intelligence/machine learning (AI/ML), AIops, cloud services, devops, and containerization. Many of these skills, particularly the coveted AI/ML, AIops, and data science competencies so crucial to modern data initiatives, have been in short supply and are now even more elusive, due to challenges related to the ongoing global pandemic and workforce trends, including the “Great Resignation.”
“There is churn everywhere,” Maccaux says.
HPE and HPE Pointnext experts can be deployed to cover any of these competency gaps. They can also augment the IT organization in order to shift focus away from operational and data management tasks and instead derive business value with data.
Bringing the cloud experience to data. Many companies simply lack the infrastructure and resources to adopt modern data constructs and don’t see the public cloud as a viable option for all workloads. The HPE GreenLake edge-to-cloud platform delivers the same speed, agility, and as-a-service benefits popularized by public cloud platforms wherever apps and data reside, whether at the edge, in a colocation facility, or in a data center. HPE Ezmeral MLops, delivered as cloud services through the HPE GreenLake edge-to-cloud platform, provides a Kubernetes container orchestration platform for deploying cloud-native and non-cloud-native applications along with services for data management, data storage, data analytics, MLops, and high-performance compute/AI.
Support for an open, extensible environment. Every company is different, with different modernization requirements and goals for data-driven business. The HPE GreenLake edge-to-cloud platform is part of a larger ecosystem of HPE and partner technologies, which means that organizations can quickly access and procure the services they need and not be hamstrung by a single-vendor environment. “HPE software uses 100% open source with open APIs, so companies can get their data in and out and not be locked in,” Maccaux says.
Delivery of managed services. For companies that lack IT resources or simply want to unburden IT from day-to-day operational responsibilities, HPE GreenLake Management Services offloads the heavy lifting of running modern IT, when and where it’s needed. Backed by unique IP and automation, HPE GreenLake Management Services offers comprehensive monitoring, operations, administration, and optimization across all areas of IT, freeing up the internal organization to focus on innovation.
There’s no easy way to flip a switch and turn data into insights. But with the right partner and tools, organizations can move forward with data-driven business at a pace that aligns best with their culture and business goals.
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