Many organizations invest time and money in data and analytics initiatives, only to get stuck in first gear. Others cannot pull together the entire data estate to generate the insights they need for smarter decision-making and positive business results.
There are several reasons why data initiatives fall short of their potential business value. Among them:
1 – Data silos that impede enterprise visibility across business units. These silos keep critical data out of reach of key business stakeholders and transformative digital initiatives. An IDG/HPE survey found that enterprises only leverage about half (49%) of their datasets to derive direct business value; 34% of respondents said they were not meeting their strategic data goals.
2 – Human constraints created by the landscape of data silos. Because of this, analytics users and data scientists spend too much time trying to locate and integrate the right data, instead of interpreting the data to surface optimal business insights. Those who know the systems best and where the data resides operate from their own silos, further hampering information and undermining intended business results.
“The siled nature of systems means that we often have people operating within these silos who don’t communicate with each other, which leads to inefficiencies,” said Matt Maccaux, global technical director, HPE Ezmeral Software. “We also have technical debt that has accumulated as these systems have matured, which makes the concept of upgrading these data analysis and aggregation systems a very expensive proposition.”
3 – Technical debtaccumulated through system updates and integration initiatives over the years. While this prolongs the life of the system, it also creates a large amount of custom code and logic, which, in turn, greatly increases the overall complexity of the system. Additionally, many of these workloads and systems cannot work or scale with modern cloud-native technologies such as Kubernetes, microservices, or DevOps-style automation. This puts the basics of a data-driven business further out of reach. Alternatively, organizations may set up a modern environment specifically for data analytics teams, but end up with another silo that introduces additional complexity.
At the same time, many of these legacy systems remain critical to businesses today and into the foreseeable future. “You can’t just remove these systems unless you have something that has the exact same functionality that’s going to replace it,” Maccaux explains.
Partner for success
While some remain stuck, many organizations are seeing what is needed to move forward and maximize the full value of data. According to the IDG/HPE survey, this includes access to better analytics tools and services (cited by 61% of respondents), seamless integration of multiple data sources (46%), and finding a trusted partner with expertise in high performance computing. (38%).
Having the right partner and the right platform is key to getting the most out of today’s data estate while recalibrating and empowering the organization with the tools, skills, and talent needed to fully execute data-driven businesses. A partner like HPE has global expertise, proven methodologies and intellectual property (IP), and fundamental technology platforms. Together, these elements can help organizations operationalize modern data initiatives while opening up and fully capturing the value of legacy data and systems.
An HPE partnership can help jump-start stranded data initiatives by providing the following:
Access to specialist talent. Successful data initiatives require diverse talents, from technologists trained in legacy data warehouse and reporting capabilities to experts in newer areas such as artificial intelligence/machine learning (AI/ML), AIops, services cloud, devops and containerization. Many of these skills, especially the coveted AI/ML, IAops, and data science skills so crucial to modern data initiatives, have been in short supply and are now even more elusive, due to the challenges of the ongoing global pandemic and workforce trends, including the “Great Resignation”.
“There’s churn everywhere,” Maccaux says.
HPE Experts and HPE Pointnext can be deployed to cover any of these skill gaps. They can also augment the IT organization to divert attention from operational and data management tasks and, instead, derive business value from the data.
Bringing the cloud experience to data. Many enterprises 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 benefits as a service popularized by public cloud platforms wherever applications 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 applications as well as data management, data warehousing, data analytics, MLops, and high-performance computing/AI.
Support for an open and extensible environment. Every business is different, with different modernization requirements and goals for data-driven businesses. The HPE GreenLake edge-to-cloud platform is part of a larger ecosystem of HPE and partner technologies, which means organizations can quickly access and procure the services they need and not be inconvenienced by a single-vendor environment. “HPE software uses 100% open source with open APIs, so companies can get their data in and out without being locked in,” Maccaux says.
Delivery of managed services. For businesses that lack IT resources or simply want to offload day-to-day operational responsibilities from IT, HPE GreenLake Managed Services offloads the heavy lifting of running modern IT, when and where it’s needed. Backed by a single IP and automation, HPE GreenLake Management Services provide comprehensive monitoring, operations, administration, and optimization across all areas of IT, freeing up internal organization to focus on innovation.
There is no easy way to flip a switch and turn data into information. But with the right partner and the right tools, organizations can push forward with data-driven activities at a pace that best suits their culture and business goals.
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