With the focus shifting to distributed data strategies, the traditional centralized approach can and should be reimagined and transformed to become a central pillar of the modern IT data estate.\n\nDecentralized data strategies are gaining traction, due to the rise of the edge, where data is being collected in droves to fuel real-time insights and in-the-moment decision-making. IDC estimates that there will be 55.7 billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge. At the same time, IDC projects, worldwide spending on edge computing will reach $176 billion this year, an increase of 14.8% over last year.\n\nAlthough centralized data models and architectures, including data lakes and data-center-based warehouses and repositories, may no longer be the leading data strategy, elements of a centralized approach remain a critical part of the mix.\n\nSpecifically, the concept of having a centralized view of data and standardized data processes can help organizations bring order to the increasingly distributed IT data estate through proper governance. It can also ease data accessibility. In fact, Gartner estimates that by 2024, three-quarters of organizations will have established a centralized data and analytics (D&A) center of excellence (CoE) to support federated efforts and prevent failures.\n\nThis next manifestation of centralized data strategy emanates from past experiences with trying to coalesce the enterprise around a large-scale monolithic data lake. In many cases, this created a mostly unusable swamp. Alternatively, companies created data lakes that were centralized for a specific function such as product development but weren\u2019t centralized to support the entire company.\n\nMore often than not, these centralized data initiatives were built on a foundation with limited governance, which impeded data\u2019s usability; alternatively, they were designed with too many rules, preventing a broad constituency of users from deriving real business value.\n\n\u201cOrganizations struggled with centralized data strategies due to misuse of technology that was meant to scale but was deployed in a way that few in the organization could benefit from because it became unwieldy,\u201d says Matt Maccaux, field chief technology officer (CTO) of HPE GreenLake Cloud Services. \u201cToday centralized and decentralized data strategies are two sides of the same coin \u2014 modern enterprises have to adopt a dual strategy.\u201d\n\nReinterpreting the centralized strategy\n\nThe rise of 5G connectivity and more processing power at the edge has created new opportunities for machine learning (ML) and artificial intelligence (AI)\u2013based workloads that thrive on a decentralized data model. Yet that momentum doesn\u2019t negate the need for a complementary centralized data strategy, particularly as it relates to having a unified view and a set of governance policies even though data might be distributed throughout the organization.\n\nNow when companies consider a centralized data strategy, they need to think about it from a logical perspective in which there are multiple places to retrieve information, plus a layer of intelligence and automation that allows for data discovery and different use cases, from building AI and ML models to business intelligence and reporting.\n\n\u201cIt\u2019s more about centralized policies, access patterns, and taking advantage of centralization through federated queries,\u201d Maccaux explains. \u201cIt\u2019s not about physically bringing all that data together into a centralized repository.\u201d\n\nOne way to drive that transition is through an executive-level chief data officer (CDO) role, focused on aligning the data and analytics experience so that the organization can extract value from distributed data through effective governance policies. As part of the agenda, CDOs should lead an effort to create a data catalog that shows where data can be found and put tool sets in place that allow access to that data, preferably buoyed by automation. In addition, the CDO should be tasked with establishing policies to discover and qualify how data is used throughout the organization, with a focus on breaking down organizational and technical silos.\n\n\u201cIt\u2019s the role of the CDO that is going to bring this decentralized view of data into a unified view, done through policies, organizational processes, and some unifying technology,\u201d Maccaux says.\n\nWhere HPE can help\n\nAs an edge-to-cloud strategic partner, HPE can help organizations build bridges between the decentralized and centralized data worlds. Among the ways HPE can add value are the following:\n\n\u201cThat is a huge differentiator: our ability to deliver an entire solution as an SLA [service-level agreement]-driven outcome,\u201d Maccaux says. \u201cHPE, because of our expertise and ownership of the technology, will be responsible for delivering the business outcomes the solution provides.\u201d\n\nFor more information on what HPE has to offer, click here.