White Paper: Quantum
More and more enterprises are faced with the complex challenge of managing the exponential data growth. Digital data hoarding is one of the biggest IT concerns for businesses globally. The plethora of new and improved tools for capturing, generating, analyzing and otherwise leveraging stored data has resulted in explosive data growth—and managing that data growth is a primary challenge for IT organizations in all industries. This whitepaper helps you develop a deeper appreciation for the dynamics of data hoarding. In this whitepaper you will learn why data hoarders behave as they do, and gain insights into strategies and tools you can use to meet their needs—all while adhering to your budget requirements. It highlights: -Common attributes of some example data hoarders -Use case requirements and storage technologies -Storage components and best fit uses -Best practices for the hoarders in your organization
White Paper: Stone Bond Technologies
The Data Warehouse (DW) has been around some thirty years as essentially a repository forstoring corporate data. The effort to define, design, and implement new data sets in a data warehouse results in backlogs that are prohibitive to support the fast pace of today’s data needs. Most companies will continue to use their Data Warehouse as they move to the more agile approach, but they will rely on it mostly as a historical data repository for reporting and analytics. The Logical Data Warehouse (LDW) is a new data management architecture for analytics which combines the strengths of traditional repository warehouses with alternative data management and access strategy. Read in this White Paper on Data Warehouse: An overview on Data Virtualization for Logical Data Warehouse Challenges with Classical Data Warehouse A case for a new generation of data access (LDW) Logical Data Warehouse for Business Intelligence Leveraging Data Virtualization for next generation Data Warehouses Data Virtualization for Logical Data Warehouse
White Paper: Service Objects
Collecting visitor and customer data through a variety of channels allows you to quickly grow your contact list. However, receiving high quality data isn’t necessarily a given. Whatever your touch points are with customers or prospects – including customer data, contest entry forms, phone surveys, lead generation and point of sale interactions – some data will be inaccurate, incomplete, or fraudulent. So how can your company avoid the challenges associated with bad data? Download this white paper and learn how to identify areas that could benefit from improved data quality, realign your data quality goals to improve your bottom line, optimize your human capital and even help the environment.
Mergers and Acquisitions: Best Practices in Orchestrating and Accelerating Data Migration Processes in a Standardized Way
White Paper: Analytix Data Services
The Mergers and Acquisitions (M&A) process brings with it a broad range of complexity, from contracts and accounting, to organizational structure and employee protocols. The primary reason many mergers and acquisitions do not deliver longer-term value is because they lack a strong cultural-integration plan. This whitepaper seeks to provide how the data related issues that come with combining disparate source data as is often the case in mergers and acquisitions can be addressed. Key takeaways from this whitepaper on Mergers and Acquisitions: How to avoid Common Pitfalls in Mergers and Acquisitions? More than 80 percent of all mergers and acquisitions fail. Why? Best Practices in Orchestrating and Accelerating Data Migration Processes in a Standardized Way Features of a typical merger or acquisition data project using a resource-driven approach Pain points in mergers and acquisitions that begin with basic decisions about how the organizations involved, align with one another Best tool to standardize the data migration process that can eliminate the error prone and costly manual process in managing complex data migration projects? Best features and functionality offered by AnalytiX Data Services’ flagship product AnalytiX Mapping Manager In this whitepaper, there are few out-of-the-box answers for streamlining this process, and though there are many system integration companies available to help, this can add significant cost and time to the Merger & Acquisition cycle.
Stubs :The Good, the Bad And the Ugly
White Paper: NTP Software
File Tiering and Stubs – What You Exactly Need to Know To Make the Right Choice. We’ve all heard the saying, “The devil is in the details.” Nowhere is this truer than it is when talking about the stubs used in tiering. Stubs require the cooperation of the storage hosts, the network, protocols, security, end-user applications, and client systems. What works for one may or may not work for another. This informative whitepaper addresses all of the following issues: How do you stub a file? When the stub is gone, how does an end-user find their tiered files? Do you care whether all of your data reaches Tier 2, or is it all right for the tiering system to throw some of it away? If compliance becomes an issue, can your tiering solution do what will be required? Read this whitepaper to learn how the right stubbing mechanism can provide end-users and applications with a seamless and unchanged experience as your organization moves to realize the benefits and savings from tiering your files.
Backups, Tiering, And Archiving: Do I Need Them All?
White Paper: NTP Software
Each one of backups, tiering and archiving addresses different aspects of a complete data management solution. Together they address legal, regulatory, information security, and economic concerns. What are the software tools available to address the complications faced in data backup and recovery? The purpose of this white paper is to help you understand how backups, tiering, and archiving technologies differ and how they work together to fight against data loss and meet your business needs in a cost effective manner. Backups offer protection against data loss by providing the means to restore your data after a hardware failure or some other data loss event. Tiering is a strategy for managing the cost of file data. By identifying unused or seldom used files and handling them accordingly, significant saving can be realized. Archiving is necessary for regulatory compliance, provides inexpensive long-term file storage and, if implemented correctly, offers a means of retrieving individual files. Read this White Paper to Dig Deeper on !
White Paper: Datos IO
To handle the data protection requirements of this new generation of real-time applications, enterprises are increasingly turning to data protection software for distributed and cloud databases. Data protection software provides automated, scalable, consistent and reliable recovery for big data and cloud environments. What are the new data protection requirements for cloud database security? How this fundamental shift raises the critical issues in the lifecycle of data management? This informative whitepaper brings you the key benefits of using Data Protection software: Scalable Versioning Reliable Recovery Semantic De-duplication Scale-out Software In this whitepaper, we will review different challenges for data storage security and privacy protection in the cloud computing environment.
White Paper: PROLIM
Do you want to ensure smooth high volume datacenter migration? Would you like to leverage etl during data migration? To know more on how to effortlessly manage the end to end processes for data migration, read this whitepaper which looks into queries like: how can organizations avoid data migration project failures? what are the best data migration practices for a successful erp project? can etl tools simplify the process of data migration
White Paper: Datos IO
Enterprise-grade recovery capabilities for distributed and cloud databases is a necessity. It is no exaggeration to say modern enterprises cannot run without business applications and underlying databases. To unlock enterprise value from their data, organizations must be sure that the data can be managed and recovered over its lifecycle. It is imperative that businesses fill these data recovery gaps to benefit from the best of both worlds and to scale their adoption across the enterprise and for their core applications. Knowing more about the perfect platform, which is rethinking recovery for the world of scale-out databases, is a requirement. What are some most common distributed database recovery issues? What are some best traditional database recovery techniques that are out in market? What are the trends that will shape application and infrastructure availability? What is the exact criteria for selecting the right database management system? What are the data warehouse disruptions in the database market? What are the major database-centric backup/recovery problems? How can you manage data for transactions and analytics? This whitepaper lays out five steps towards distributed database design to ensure your project matches up with requirements from inception, through the development life cycle and to deployment.
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