In almost every organization, SQL is at the heart of enterprise data used in transactional systems, data warehouses, columnar databases and analytics platforms to name just a few examples. Additionally, a vast number of commercial and in-house developed tools used to access, manipulate and visualize data rely on SQL. SQL is lifeblood of the modern transaction and decision support systems.
An organization’s readiness for Hadoop is not a single state held by a single entity. Corporations, government agencies, educational institutions, healthcare providers, and other types of organizations are complex in that they have multiple departments, lines of business, and teams for various business and technology functions. Each function can be at a different state of readiness for Hadoop, and each function can affect the success or failure of Hadoop programs.
Businesses are discovering the huge potential of big data analytics across all dimensions of the business, from defining corporate strategy to managing customer relationships, and from improving operations to gaining competitive edge. The open source Apache Hadoop project, a software framework that enables high-performance analytics on unstructured data sets, is the centerpiece of big data solutions. Hadoop is designed to process data-intensive computational tasks, in parallel and at a scale, that previously were possible only in high-performance computing (HPC) environments.
When considering enterprise storage software options, IT managers constantly strive to find the most efficient, scalable, and high performance solutions that solve today’s storage performance and scalability challenges, while future-proofing their investment to handle new workloads and data types. Enterprise backup solutions can be particularly vulnerable to issues stemming from poor network performance to the storage array(s), and are often not designed with the scalability demanded by rapidly changing enterprise environments.
In conference rooms worldwide, enterprise IT departments are evaluating entry into ‘the cloud’. Armed with media reports and marketing materials, they are considering questions like, “Is the cloud appropriate for critical workloads? Will the cloud really save time and money? Does the cloud pose a security risk?”
There’s only one problem with such due diligence: there’s no such thing as ‘the cloud’. Instead, there are multiple clouds, with different configurations, offered by different providers and representing different degrees of benefit and risk.
Software defined infrastructure (SDI) enables organizations to deliver HPC services in the most efficient way possible, optimizing resource utilization to accelerate time to results and reduce costs. Software Defined Infrastructure is the foundation for a fully integrated environment, optimizing compute, storage and networking infrastructure to quickly adapt to changing business requirements, and dynamically managing workloads and data, transforming a static infrastructure into a workload- , resource- and data-aware environment.
Businesses are discovering the huge potential of big data analytics across all dimensions of the business, from defining corporate strategy to managing customer relationships, and from improving operations to gaining competitive edge. The open source Apache Hadoop project, a software framework that enables high-performance analytics on unstructured data sets, is the centerpiece of big data solutions. Hadoop is designed to process data-intensive computational tasks, in parallel and at a scale that previously were possible only in high-performance computing (HPC) environments.
Simply put, it’s an evolution. Cloud computing is following the same pattern of other technologies that have shaped business and society. Take electricity, for example. Even after the first public power supply lit the streets, it took time for businesses to learn how to really capitalize on this new technology. In those early days, people were enthralled by artificial lighting – one of the earliest applications of electricity. Very few could fathom the innumerable product innovations, business models and industries that would ultimately be built upon this technology.
This paper reviews the increasingly popular OpenStack cloud platform and the abilities that IBM storage solutions provide to enable and enhance OpenStack deployments. But before addressing those specifics, it is useful to remind ourselves of the “whys and wherefores” of cloud computing.
Analytics is a key enabler for life sciences and healthcare organizations to create better outcomes for patients, customers and other stakeholders across the entire healthcare ecosystem. While almost two-thirds of organizations across the healthcare ecosystem have analytics strategies in place, our research shows that only a fifth are driving analytics adoption across the enterprise. The key barriers are a lack of data management capabilities and skilled analysts, as well as poor organizational change management. To find out more download this white paper.