Data Management Strategies for the CIOEmail Alerts
-
Cloud data quality, integration open new vistas for managing data
Find out what opportunities the cloud could open up for data quality and integration. Advantages: scalability, reduced admin and costs. ETL, as a data quality sweet spot, lends itself to the cloud. Feature
-
A guide to cloud data management technology and trends
This guide is designed to provide readers with practical information and advice on trends, issues and developments involving cloud database, data warehousing and data integration technology. null
-
A must to avoid: Worst practices in enterprise data governance
Consultant Rick Sherman details 10 common data governance mistakes that can send governance initiatives down the wrong path – the one to failure. Advice
-
Data Quality Management Software Product Directory
Inside this data quality management software product directory you'll find basic information about the major vendors in the data quality market and the products they sell. Each listing is accompanied by a short description and a long description incl... Product directory
-
Data management industry event and conference calendar
Find listings and dates of upcoming data management industry events, conferences and seminars, in the Data Management Industry Event Calendar. Calendar
-
Information assurance: Dependability and security of networked information systems
Learn how information assurance involves efforts from both dependability and security areas of networked information systems, in this free chapter download. Book Chapter
-
Data quality and governance management quiz
Test your knowledge of data quality and data governance management concepts, trends and vendor news in this short quiz. When you are done, check your answers and read detailed explanations for each response. Quiz
-
Thirteen causes of enterprise data quality problems
Find out which 13 processes are most likely to cause enterprise data quality management problems, and learn how to deal with them. Book Chapter
-
Data governance and data stewardship strategies and best practices
This chapter examines key steps of a generic data governance strategy program as it may apply to the CDI Data Hub and discusses the concept of data stewards and their role in assessing, improving and managing data quality. Book Chapter
-
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. Book Chapter
- See More: Essential Knowledge on Data quality techniques and best practices
-
People, process issues offer path to improve data quality on the cheap
An emphasis on educating end users and upgrading internal processes can help enterprises fix data quality problems without dropping a ton of cash, according to analysts. News | 16 May 2012
-
As data demands speed up, information management tools pave road ahead
New research shows data virtualization, data governance and master data management initiatives provide higher levels of satisfaction with data quality and data integration. News | 15 May 2012
-
Intel offers up a 'silver bullet' master data management strategy
An IT manager at Intel Corp. sums up the chip maker's approach to managing master data in four words: Standardize, consolidate, optimize and utilize. News | 25 Apr 2012
-
IBM users reveal five data governance best practices to remember
IBM customers Nationwide Insurance and Cardinal Health reveal five rules of thumb they learned while implementing highly ambitious data governance programs. News | 28 Mar 2012
-
TDWI Solution Summit speakers share MDM best practices
TDWI Solution Summit speakers gathered last week to exchange MDM best practices and data governance tips. News | 15 Mar 2012
-
Data governance programs expose hills to climb on path to success
IT professionals from Sallie Mae and Fannie Mae offered insight on data governance challenges and tips on how to overcome them in separate sessions at two recent conferences. News | 08 Mar 2012
-
Poor reference data management causing headaches in financial sector
Regulatory pressures and the need to improve data quality are forcing financial institutions to rethink their reference data management strategies. News | 13 Feb 2012
-
Customer service is from Venus, data quality is from Mars
How can the two talk to one another? Forrester has a few ideas and some advice to get customer service on board with data quality and vice versa. Blog | 25 Jan 2012
-
Beta-tester evaluates the latest DataFlux data management software
An enterprise data architect with medical device maker SonoSite offers up details on the newest release of DataFlux’s flagship data management software platform. News | 28 Dec 2011
-
IBM explains how to make the case for a data governance program in 2012
The director of information governance for IBM’s software group, Sunil Soares, explains how to make the business case for data governance despite ongoing economic concerns. News | 30 Nov 2011
- See More: News on Data quality techniques and best practices
-
Data quality management tips and best practices
Get data quality management tips and best practices with expert advice and book excerpts. Learn about academic sources for data quality, key steps and common mistakes of data quality implementations, how much you should spend for data cleansing and m... Tip
-
How to improve data quality on a tight budget -- a guide
Many organizations may be tempted to forgo data quality management to save money, but it's important to assess the ROI of high-quality data, according to consultant David Loshin. Tip
-
Data governance success: No pain, no gain
Data governance isn't easy, but it is necessary for success in data-centric projects. Rick Sherman commiserates and offers expert advice for getting started with data governance. Tip
-
Five steps for weaving data quality management into your enterprise data integration processes
Data quality management is critical for effective enterprise data integration (EDI). Expert Rick Sherman shares five strategic steps (and potential pitfalls) of data quality management. Tip
-
Data quality management: Follow the doctor's orders
Get expert recommendations for data quality management in business intelligence and data warehousing projects. Tip
-
Why data governance projects fail
Expert Rick Sherman discloses the top reasons why 90% of data governance projects are doomed for failure. Read his advice to make sure that your projects are not! Tip
-
XQuery and XML data: DB2 helps manage the era of unstructured data
The arrival of IBM XQuery and XML data is simplifying users' decisions in this era of unstructured data, just as the arrival of the relational database and SQL simplified IT buyers' decisions twenty years ago. Tip
-
Data manager best practices: Dear Santa, I've been a good data management manager
T'was the night before Christmas, when all through the database, guest columnist Rick Sherman was asking Santa to make the world of data management a better place... Tip
-
Data quality management for business intelligence projects
Poor data quality can blindside an organization's BI or data warehouse project. Guest columnist Rick Sherman explains how to avoid common pitfalls that can derail that effort. Tip
-
The state of enterprise information management technology use in 2011
Get expert insight on whether there likely will be any strategic shifts during 2011 in how companies use enterprise information management technology. Answer
-
Common enterprise information management strategy mistakes to avoid
Learn about four common mistakes that companies make when creating an enterprise information management strategy and starting an EIM program. Answer
-
Implementing data quality software but ignoring governance policies
Is it OK to implement data quality software but ignore your data governance policies? Learn more about the relationship between data quality software and governance processes. Answer
-
Open source data quality software to help with name matching
Learn what to consider before adopting open source data quality software to help with identity resolution and name matching. Answer
-
How often should you update your data quality strategy?
Learn how often companies should update their data quality strategy. See how changes in data quality problems create new challenges and how revising your data quality strategy can help. Answer
-
Data governance trends for 2011: Scorecards and data governance tools
Learn about emerging data governance trends for 2011, including more use of data governance tools and data quality metrics and scorecards. Find out what’s useful and what’s not. Answer
-
Are the data quality issues worse in real-time data integration apps?
Find out if real-time data integration applications has more data quality issues than other approaches. Also, see if real-time or near-real-time integration are really useful. Answer
-
How enterprise information management (EIM) differs from ECM
Learn how enterprise information management (EIM) differs from enterprise content management (ECM) and unstructured data management as a data management technology category. Answer
-
Key components of enterprise information management programs
Learn which three components of enterprise information management programs are most important for a successful EIM strategy. Answer
-
Key steps for developing an enterprise information management strategy
Here you’ll find 12 expert tips on developing an enterprise information management strategy and roadmap for your company. Use the EIM strategy development advice to get started. Answer
- See More: Expert Advice on Data quality techniques and best practices
-
data scrubbing (data cleansing)
Data scrubbing, also called data cleansing, is the process of cleaning up data in a database that is incorrect, incomplete, or duplicated. Definition
-
raw data (source data or atomic data)
Raw data (sometimes called source data or atomic data) is data that has not been processed for meaningful use. Definition
-
data governance (DG)
Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures, an... Definition
-
synthetic backup
Synthetic backup is the process of generating a file from a complete copy of a file created at some past time and one or more incremental copies created at later times... (Continued) Definition
-
data
In computing, data is information that has been translated into a form that is more convenient to move or process. In other contexts, data has somewhat different meanings. Definition
-
fixed data (permanent data, reference data, archival data, or fixed-content data)
Fixed data (sometimes referred to as permanent data) is data that is not, under normal circumstances, subject to change. Any type of historical record is fixed data. For example, meteorological details for a given location on a specific day in the pa... Definition
-
data quality
In computing, data quality is the reliability and application efficiency of data, particularly when kept in a data warehouse. Data quality assurance (DQA) is the process of verifying the reliability and efficiency of data. Definition
-
Top six data management software stories of 2011
From the rise of "big data" to office politics hampering MDM projects to Hewlett-Packard giving Neoview the ax, and more, there were plenty of notable data management stories in 2011. Photo Story
-
Common mistakes that can derail a data governance strategy and program
Learn about the common mistakes companies make in creating, implementing and managing a data governance strategy and program. Video
-
Tactical data quality projects deliver quick ROI
Tactical data quality projects can show quick ROI and have a definite impact on the bottom line. Get advice for deploying tactical data quality projects from Forrester's Rob Karel. Podcasts
-
Uncovering the new data governance trends, with Ventana Research
Learn data governance trends from Ventana Research -- including early results from a new research study. Podcast
-
Exec explains IBM's Information On Demand (IOD) initiative
Listen to IBM's Steve Mills discuss Big Blue's Information On Demand initiative and why he thinks it's in a better position to help customers than rival Oracle. Podcast
-
Effective data quality program management: Tips and advice
Learn how to structure data quality management programs, how to deal with data quality program challenges and more, from expert Even Levy. Podcast
-
Best practices for designing and implementing sustainable, long-term data quality programs
Learn best practices for designing and implementing data quality management programs. Podcast
-
Creating successful data stewardship programs, with Jill Dyché
Learn how data stewardship fits into data governance and data quality management programs, from Jill Dyché. Podcast
-
Data quality assessment helps identify, fix data quality problems
Data quality problems can't be fixed until they are identified. Learn how a data quality assessment can help pinpoint data quality problems. Podcast
-
How to develop and maintain an enterprise data quality management strategy, with Larry English
Expert Larry English discusses how to develop and maintain a data quality management strategy. Learn how to get started, structure teams, calculate ROI and get executive support. Podcasts
- See More: Multimedia on Data quality techniques and best practices
-
People, process issues offer path to improve data quality on the cheap
An emphasis on educating end users and upgrading internal processes can help enterprises fix data quality problems without dropping a ton of cash, according to analysts. News
-
As data demands speed up, information management tools pave road ahead
New research shows data virtualization, data governance and master data management initiatives provide higher levels of satisfaction with data quality and data integration. News
-
Intel offers up a 'silver bullet' master data management strategy
An IT manager at Intel Corp. sums up the chip maker's approach to managing master data in four words: Standardize, consolidate, optimize and utilize. News
-
IBM users reveal five data governance best practices to remember
IBM customers Nationwide Insurance and Cardinal Health reveal five rules of thumb they learned while implementing highly ambitious data governance programs. News
-
TDWI Solution Summit speakers share MDM best practices
TDWI Solution Summit speakers gathered last week to exchange MDM best practices and data governance tips. News
-
Data governance programs expose hills to climb on path to success
IT professionals from Sallie Mae and Fannie Mae offered insight on data governance challenges and tips on how to overcome them in separate sessions at two recent conferences. News
-
Cloud data quality, integration open new vistas for managing data
Find out what opportunities the cloud could open up for data quality and integration. Advantages: scalability, reduced admin and costs. ETL, as a data quality sweet spot, lends itself to the cloud. Feature
-
Top six data management software stories of 2011
From the rise of "big data" to office politics hampering MDM projects to Hewlett-Packard giving Neoview the ax, and more, there were plenty of notable data management stories in 2011. Photo Story
-
Poor reference data management causing headaches in financial sector
Regulatory pressures and the need to improve data quality are forcing financial institutions to rethink their reference data management strategies. News
-
Customer service is from Venus, data quality is from Mars
How can the two talk to one another? Forrester has a few ideas and some advice to get customer service on board with data quality and vice versa. Blog
- See More: All on Data quality techniques and best practices
About Data quality techniques and best practices
Learn the latest data quality management and data governance best practices from analysts, experts and a wide range of case studies. Find data quality techniques and best practices including templates for organizations in all stages of planning -- whether an organization is updating its data quality management processes or just identifying data quality issues and learning the business benefits of data governance and data quality management. Find out how companies use data profiling, reports and scorecards to monitor and measure data quality, or find out what data quality management controls, standards and processes have helped other companies reach their objectives. Finally, be sure to browse many data quality management and data governance case studies with real-world insight across a variety of industries.