Integrated data management (IDM) is a tools approach to facilitate data management and improve performance. IDM consists of an integrated, modular environment to manage enterprise application data, and optimize data-driven applications. It manages data over its lifetime, from requirements to retirement.

Data life-cycle

Data retention

Data retention

Data retention defines the policies of persistent data and records management for meeting legal and business data archival requirements. A data retention policy weighs legal and privacy concerns against economics and need to know concerns to determine both the retention time, archival rules, data...

Data governance

Data governance

Data governance is an emerging discipline with an evolving definition. The discipline embodies a convergence of data quality, data management, data policies, business process management, and risk management surrounding the handling of data in an organization...

Data quality

Data quality

Data are of high quality "if they are fit for their intended uses in operations, decision making and planning" . Alternatively, the data are deemed of high quality if they correctly represent the real-world construct to which they refer...

Agile data method
Data modeling

Data modeling

Data modeling in software engineering is the process of creating a data model for an information system by applying formal data modeling techniques.- Overview :...

Purpose

Produce enterprise-ready applications faster

• Improve data access, speed iterative testing
• Empower collaboration between architects, developers and DBAs

Consistently achieve service level targets

• Automate and simplify operations
• Provide contextual intelligence across the solution stack

Support business growth

• Accommodate new initiatives without expanding infrastructure
• Simplify application upgrades, consolidation and retirement

Facilitate alignment, consistency and governance

• Define business policies and standards up front; share, extend, and apply throughout the lifecycle

Example

Integrated data management lets you grow your business without growing your infrastructure. How is this possible? Let’s say you’ve just completed an acquisition, and you need to bring three new manufacturing facilities on board. Application consolidation and retirement is common in this scenario. Data archiving capabilities help to minimize cost and accelerate completion of such scenarios:

1. you can minimize the data that you migrate from the legacy system to the consolidated system accomplishing the consolidation faster and minimizing hardware and software requirements to support additional load.
2. You retain archived information for as long as needed on lower cost stire, immutable if needed, while providing flexible access to it for e-discovery.

Time to market is a critical imperative in today’s environment. IDM helps you produce enterprise-ready applications faster. For example, our pureQuery technology is built to give developers the productivity they need, while helping them adopt best practices for data access. It provides a collaborative environment for developers and DBAs to work together to optimize data access performance, maximize database security, and improve manageability. It makes service enabling vetted database assets as simple as a drag-and-drop gesture. Our test data management capabilities let tester leverage production-like data while safeguarding client privacy and corporate confidentiality. And we help to jump-start development and testing efforts based on accelerators for packaged applications, industry models, and compliance initiatives.

For production systems, the challenge is to meet increasingly strict and challenging service level targets yet still free up staff time for value creation activities. We’re focused on learning more about the environment enabling the tools to automate and simplify operations. And aggregating and contextualizing information across the solution stack so that administrators have the information they need to identify emergent problems, view relevant information about the problem, isolate the problem to its source, and get expert advice on resolution.

And we want to help business and IT work together towards business objectives such that there is a common understanding and transparent and consistent execution across the business. We are building out a capability to define business policies and semantics early in the design cycle and then share them via models and other data artifacts across the lifecycle. We call this idea model-driven governance. Not only will this improve alignment and governance, but also organizational productivity and effectiveness by facilitating seamless collaborate:
From analysts to architects to developers to administrators
From design to delivery to management

Related database technologies

• Information lifecycle management
  Information Lifecycle Management
  Information Lifecycle Management refers to a wide-ranging set of strategies for administering storage systems on computing devices. Specifically, four categories of storage strategies may be considered under the auspices of ILM.-Policy:...
  
  
• Computer data storage
• Data proliferation
  Data proliferation
  Data proliferation refers to the prodigious amount of data, structured and unstructured, that businesses and governments continue to generate at an unprecedented rate and the usability problems that result from attempting to store and manage that data...
  
  
• Digital preservation
  Digital preservation
  Digital preservation is the set of processes, activities and management of digital information over time to ensure its long term accessibility. The goal of digital preservation is to preserve materials resulting from digital reformatting, and particularly information that is born-digital with no...
  
  
• Document management
• Enterprise content management
  Enterprise content management
  Enterprise Content Management is a formalized means of organizing and storing an organization's documents, and other content, that relate to the organization's processes...
  
  
• Hierarchical storage management
  Hierarchical storage management
  Hierarchical storage management is a data storage technique which automatically moves data between high-cost and low-cost storage media. HSM systems exist because high-speed storage devices, such as hard disk drive arrays, are more expensive than slower devices, such as optical discs and magnetic...
  
  
• Information repository
  Information repository
  An information repository is an easy way to deploy a secondary tier of data storage that can comprise multiple, networked data storage technologies running on diverse operating systems, where data that no longer needs to be in primary storage is protected, classified according to captured metadata,...
  
  
• Records management
  Records management
  Records management, or RM, is the practice of maintaining the records of an organization from the time they are created up to their eventual disposal...
  
  
• System integration
  System integration
  In engineering, system integration is the bringing together of the component subsystems into one system and ensuring that the subsystems function together as a system...
  
  

External links

• Integrated Data Management: Managing data across its lifecycle from Holly Hayes
• Organizations thrive on Data by Eric Naiburg
• IBM's IDM Solutions