Data protection modernization is among the top five most critical IT priorities for 73% of organizations. The primary objective of traditional data protection solutions has been data backup and recovery. However, today’s digital world is increasingly complex, meaning IT environments are more dynamic than ever — and their needs are anything but traditional.
Organizations now expect data protection solutions to deal with exponential data growth and new workloads, recover quickly in the event of a cyberattack, and improve the efficacy of analytics and efficiency of development.
To meet expectations, organizations must move beyond backup. They need to unify data recovery, retention
and reuse across their hybrid multicloud environments, including for physical, virutalized and container-based workloads. And, they must support cybersecurity objectives. Having this solid foundation drives the
key capabilities that propel today’s modern data protection agenda:
• Management simplicity
• Greater performance
• Lower storage costs
• Ability to secure backup repositories
• More efficient and effective business operations
In short, the right modern data protection solutions can transform data protection from an insurance policy to business-centric solution that enables data-driven transformation.
This eBook examines the important business benefits that modern data protection solutions can provide. It also reviews the necessary capabilities that make those benefits obtainable, and highlights IBM clients who have found success by modernizing their data protection.
IDC strongly believes that the days of homogeneous compute, in which a single architecture dominates all compute in the datacenter, are over. This truth has become increasingly evident as more and more businesses have started to launch artificial intelligence (AI) initiatives. Many of them are in an experimental stage with AI and a few have reached production readiness, but all of them are cycling unusually fast through infrastructure options to run their newly developed AI applications and services on.
The main reason for this constant ove ...
Clients can realize the full potential of artificial intelligence (AI) and analytics with IBM’s deep industry expertise, technology solutions and capabilities and start to infuse intelligence into virtually every business decision and process.
IBM’s AI & Analytics Services organization is helping enterprises get their data ready for AI and ultimately achieve stronger data-driven decisions; access deeper insights to provide improved customer care; and develop trust and confidence with AI-powered technologies focused on security, risk and ...
Le damos la bienvenida a la era de la inteligencia artificial (IA), donde los negocios se ven supeditados a tecnologías de uso intensivo de datos, como el aprendizaje automático y el aprendizaje profundo. Para aprovechar las ventajas de estas nuevas herramientas de IA, debe asegurarse de que el “hogar” en el que almacena los datos de su organización está ordenado.
A continuación dispone de una lista de comprobación para comenzar a limpiar los datos almacenados, que se desglosa en dos fases clave del proceso de limpieza: formación e inferenc ...
Benvenuti nell’era dell’intelligenza artificiale (AI), in cui l’operatività dell’azienda dipende dalle tecnologie ad alta intensità di dati, quali machine learning e deep learning. Per utilizzare al meglio questi nuovi strumenti di intelligenza artificiale, è necessario assicurarsi che il luogo in cui risiedono i dati dell’organizzazione sia in ordine.
Ecco una lista di controllo per iniziare il percorso che consentirà di mettere ordine nei dati, suddiviso in due fasi fondamentali: preparazione e inferenza.
Seguire questi passaggi per di ...
Welcome to the era of artificial intelligence (AI), where the way you do business is reliant on data-intensive technologies like machine learning and deep learning. To take advantage of these new AI tools, you need to make sure your organization’s data "house" is in order.
Here’s a checklist to get you started on your path towards a clean data house, broken down into the two key phases of housekeeping — training and inference.
Follow these steps to help you become an AI master. ...
Pressure Intensifies to Drive Digital Business in Europe. We are now in an era of multiplied...