Data management strategies
Data is a corporate asset that helps make more-informed business decisions, improve marketing campaigns, optimize business operations and reduce costs. Learn data management strategies to ensure IT systems run business applications and provide analytical information that drives decision-making and strategic planning by corporate executives, business managers and end users.
Top Stories
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News
20 Feb 2025
Cube semantic layer eases data access from Power BI, Excel
New integrations aim to better enable Microsoft users to directly access data in cloud data warehouses, which has been problematic given how different query languages interact. Continue Reading
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News
13 Feb 2025
Confluent, Databricks partner to simplify AI development
With a new integration, joint customers can more easily access real-time streaming data to develop, deploy and maintain trusted AI models and applications. Continue Reading
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Tutorial
06 Jul 2010
Buyer’s Guide: Choosing and understanding MDM software
Read up on master data and master data management, plus get expert advice on choosing MDM software and tools and what to look for in an MDM product or service. Continue Reading
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Feature
04 Feb 2010
Making business transaction processing and applications work
Learn about making business transaction processing work in your company, find tips on transaction processing applications and get transaction processing definitions. Continue Reading
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Podcast
14 Dec 2009
Tips for a master data management (MDM) requirements gathering process
Embarking on a master data management (MDM) project? Get an expert's tips for the MDM requirements gathering process and ensure MDM implementation success. Continue Reading
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Answer
15 Sep 2009
Six criteria for master data management (MDM) tool evaluation
Starting to evaluate MDM tools and software? Know what six areas you should look at to make sure you choose the best vendor and tool for your business needs. Continue Reading
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Answer
15 Sep 2009
Is it better to have a centralized or decentralized master data structure?
Should your master data be centralized or decentralized? Get an expert's take, plus find out how different MDM architecture styles affect your master data and MDM hub. Continue Reading
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Feature
02 Jul 2009
Top 13 master data management (MDM) buzzwords and definitions
Get the top master data management (MDM) terms, definitions and concepts and learn how MDM can improve your enterprise data. Also get links to useful MDM tutorials, training, video, podcasts and articles. Continue Reading
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Answer
28 May 2009
Four must-have master data management project skills
There are four important master data management project skills needed for MDM projects and development efforts. Discover what they are and learn about MDM job roles and responsibilities in this tip. Continue Reading
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Feature
21 May 2009
The importance of managing data assets
Get an overview of data management and data lifecycle, learn how important managing data and data assets is and learn how to control data in this information management tutorial. Continue Reading
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Feature
26 Jan 2009
Designing an MDM project plan
Master data management (MDM) projects require enterprise buy-in and participation in order to be successful. In this chapter, learn how to identify the people in the organization that can benefit from MDM and how to assemble an MDM project team. Discover how to establish and communicate the MDM business case, learn tips for collecting and prioritizing data requirements, developing a plan for enterprise data integration and designing a migration plan for the participating applications. Learn how to tackle these key steps and how to develop a successful MDM project plan in this chapter. Setting the stage for assembling the right team for an MDM program involves determining the best opportunities to socialize the internal value across the enterprise landscape. As this chapter has shown, this socialization is performed along a number of avenues: Communicating the value of presenting a centralized master data asset to the business clients, application owners, and operations staff Identifying the key stakeholders that will participate in the MDM program Carefully articulating within a project charter what will be achieved by the MDM program and how the corresponding milestones will be reached Providing a means for coordinating the participants to reduce conflict and encourage consensus Carefully detailing roles and responsibilities Analyzing the data requirements to establish MDM feasibility ■ ■ ■ ■ ■ ■ 2.7 Summary Continue Reading
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Answer
14 Oct 2008
What's the difference between SOA and Web services?
How are Web services and service oriented architecture (SOA) different? Find out in this expert response. Continue Reading
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Feature
13 Mar 2008
IT project management: The cost estimating process
Learn about the cost estimating process in IT project management by reading examples and definitions of cost estimation terms, in this free chapter download. Continue Reading
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Feature
28 Jan 2008
Personal information management: History and details
Learn about personal information management and why managing personal information is especially important in today's data inundated world. Continue Reading
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News
22 Jan 2008
Active data warehousing explained and examined
Active data warehousing brings business intelligence to more operational decision-making processes. Find out how, and why, active data warehouses enable competitive advantages. Continue Reading
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Feature
01 May 2007
MDM-CDI project implementation guidelines
This chapter excerpt deals with the practical aspects of implementing MDM-CDI solutions as complex, multidisciplinary, enterprise-wide projects or programs. Implementing MDM-CDI solutions requires an approach that may be even broader than a single project, and should be managed as an initiative-level, enterprise-wide program. Continue Reading
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Feature
20 Apr 2007
Data governance: Information ownership policies and roles explained
Who owns the data? This chapter defines information ownership boundaries and best practices, and outlines the specific roles and responsibilities of all involved in the battle for data governance. Continue Reading