Data Management comprises all the disciplines related to managing data as a valuable resource. Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise.
Traditional datacenter perimeters are dissolving as users access applications from a multitude of environments on a variety of devices. Secure, centralized application management throughout the hybrid cloud network will give an enterprise greater agility to succeed in today’s digital world. Read the whitepaper to learn how.
In this report, you will be able to answer the following:
- What’s the value of a managed service & why should developers care about it?
- Why is a managed service preferred over DIY management?
- How does a managed service give you back hours in your day?
This Market Guide helps CISOs identify emerging data-centric audit and protection tools. IBM is positioned with a centralized management console approach across multiple silos and has coverage of all the key capabilities evaluated by Gartner.
The growth of virtualization has fundamentally changed the data center and raised numerous questions about data security and privacy. In fact, security concerns are the largest barrier to cloud adoption. Read this e-Book and learn how to protect sensitive data and demonstrate compliance.
As big data environments ingest more data, organizations will face significant risks and threats to the repositories containing this data. Failure to balance data security and quality reduces confidence in decision making. Read this e-Book for tips on securing big data environments.
The in-store experience is changing dramatically. Not long ago it was straightforward and transactional: consumers would go into a store and, if it stocked what they wanted, would buy. If it didn’t, they would walk out, but their options to go elsewhere were often restricted by distance, choice and convenience.
In this issue of Beyond Retail, we look at how the Point of Sale is changing to deliver a modern in-store experience, and how it can help retailers keep pace with the changing habits of their customers. We also explore how changes in PoS technology can affect store layout and the role of PoS in bridging the online and offline retail experience.
Until very recently, reporting teams have had few worthy alternatives for collecting, presenting, and analyzing complex data.
Finance professionals have been asked to do more with dated software and provide valuable insights with antiquated processes. Advancements in desktop software and use of the cloud may have shifted a dated process from pencil and paper, but they have also left us with too many moving parts and too many unconnected documents.
As the landscape of business reporting continues to evolve, it is critical for organizations to stay abreast of emerging opportunities to improve collaboration, increase productivity, tohelp them select the right solution for the job.
Information is the foundation of business analysis and strategy, and preserving the quality of information as it is gathered and shared is crucial to success.
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
This paper from Osterman Research, explores the origins of the "information problem" many organizations are now facing and presents a detailed discussion of how to calculate your current information costs as well as how to calculate the ROI of an information governance program.
Read this Forrester whitepaper to learn more about the critical, yet often overlooked, role that data classification and data discovery can play in reducing your organization’s risk and enhancing security.
Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
ENDPOINT DATA. It’s often one of the most forgotten aspects of an enterprise data protection strategy. Yet, content on laptops, desktops and mobile devices is among a company’s most valuable data even while it’s potentially at the greatest risk. According to IDC there will be some 1.3 billion mobile workers by 2015. However, only half of enterprises today are using some type of endpoint backup. That means that the volume of endpoint data that is in jeopardy is nothing short of significant.
Download to read the buyer's checklist on endpoint data protection!
How do you maintain the security and confidentiality of your organization’s data in a world in which your employees, contractors and partners are now working, file sharing and collaborating on a growing number of mobile devices? Makes you long for the day when data could be kept behind firewalls and employees were, more or less, working on standardized equipment. Now, people literally work on the edge, using various devices and sending often unprotected data to the cloud. In the 24 x 7 BYOD (Bring Your Own Device) time frame in which people now work, they also expect data recovery and access to be lightning fast, and expediency, rather than security, is the driver.
This dramatic shift to this diversified way of working has made secure backup, recovery and sharing of data an exponentially more difficult problem to solve. The best approach is to start with a complete solution that can intelligently protect, manage and access data and information across users, heterogeneous devices and infrastructure from a single console - one that can efficiently manage your data for today's mobile environment and that applies rigorous security standards to this function.
Today, nearly every datacenter has become heavily virtualized. In fact, according to Gartner as many as 75% of X86 server workloads are already virtualized in the enterprise datacenter. Yet even with the growth rate of virtual machines outpacing the rate of physical servers, industry wide, most virtual environments continue to be protected by backup systems designed for physical servers, not the virtual infrastructure they are used on. Even still, data protection products that are virtualization-focused may deliver additional support for virtual processes, but there are pitfalls in selecting the right approach.
This paper will discuss five common costs that can remain hidden until after a virtualization backup system has been fully deployed.
Data conversations continue to change as all businesses are trying to figure out today's reality of the move to the cloud, anywhere/anytime computing, and the explosive growth of data. These trends have drastically reshaped the IT industry and data management forever. With continued market innovations in storage, cloud, and hyper-converged infrastructures, there are six key modern IT needs that are increasingly the focus of CIO and technology leaders.
Enterprises today increasingly turn to array-based snapshots and replication to augment or replace legacy data protection solutions that have been overwhelmed by data growth. The challenge is that native array snapshot tools – and alternative 3rd party solutions – have varying degrees of functionality, automation, scripting requirements, hardware support and application awareness. These approaches can add risk as well as administrative complexity and make it more difficult to realize the full potential of snapshots – whether in single disk vendor estates or in heterogeneous storage environments.
This checklist will enable you to build a shortlist of the 'must have' features needed for snapshots to deliver exactly what you require in your application environment or Private Cloud.
The cloud is changing everything. It’s transforming IT organizations with agility and efficiency like never before, enabling them to realize new IT-as-a-Service delivery models. Yet, with change also comes new challenges. Read more to see how you can solve them so that you can realize the full potential of your next cloud project.