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
25 May 2023
Fivetran's new funding a hedge against economic uncertainty
The data integration vendor added $125 million in financing to not only fuel R&D but also ensure that operations remain smooth if there is a recession. Continue Reading
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News
25 May 2023
Snowflake acquisition of Neeva to add generative AI
The pending purchase will let the data cloud vendor infuse generative AI throughout its data management suite and potentially open the technology's use to a broader audience. Continue Reading
- 09 Apr 2018
- 09 Apr 2018
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Feature
09 Apr 2018
IT teams take big data security issues into their own hands
Data security needs to be addressed upfront in deployments of big data systems -- and users are likely to find they have to build some security capabilities themselves. Continue Reading
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Podcast
29 Mar 2018
Kubernetes container orchestration gets big data star turn
The new thing in big data is Kubernetes container orchestration. While it's still early, there are signs of activity, which are cited in this edition of the Talking Data podcast. Continue Reading
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Feature
21 Mar 2018
Kubernetes gains momentum in big data implementation process
Big data vendors and users are looking to Kubernetes-managed containers to help accelerate deployments and enable more flexible use of computing resources. Continue Reading
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News
15 Mar 2018
Streaming tool from StreamSets eyes data in motion for GDPR
StreamSets software for inspecting big data brings governance to data in motion. Such capabilities may find more use as the European Union's GDPR deadline looms. Continue Reading
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Opinion
02 Feb 2018
Data managers should study up on GPU deep learning
As GPU deep learning becomes more common, data managers will have to navigate several new layers of complexity in their quest to build or buy suitable data infrastructure. Continue Reading
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Tip
01 Feb 2018
Three ways to turn old files into Hadoop data sets in a data lake
Hadoop data lakes offer a new home for legacy data that still has analytical value. But there are different ways to convert the data for use in Hadoop depending on your analytics needs. Continue Reading
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Podcast
23 Jan 2018
How AI and IoT will influence data management in 2018
AI and IoT will alter the data management landscape in 2018, according to analyst James Kobielus. AI will need regular updates, and DevOps will become more prevalent as a result. Continue Reading
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News
03 Jan 2018
Apache Hadoop 3.0 goes GA, adds hooks for cloud and GPUs
Is this the post-Hadoop era? Not in the eyes of Hadoop 3.0 backers, who see the latest update to the big data framework succeeding in machine learning applications and cloud systems. Continue Reading
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Feature
26 Sep 2017
Bank sees ETL processes evolve from IT to front-line users
ETL jobs -- once the sole province of IT -- take on a new form as data wrangling and self-service gain greater traction with business users of analytics. Continue Reading
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Feature
21 Aug 2017
Data management processes take on a new tenor in analyst's view
Changes in data management processes -- including self-service data preparation, data lakes and real-time analytics -- create a new landscape in companies, according to analyst Matt Aslett. Continue Reading
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Quiz
11 Jul 2017
Quiz: What's your IQ on data lake implementation and management?
A data lake can provide lots of analytics value to an organization. This quiz can tell you if you know what it takes to deploy and manage one; it also contains info to help boost your knowledge. Continue Reading
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Feature
24 Oct 2016
Reltio master data management architecture rides graph analytics wave
An onslaught of unstructured data, social and otherwise may change the nature of master data management platforms. Reltio Cloud may stand as an indicator. Continue Reading
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News
15 Sep 2016
HPE sells Vertica analytics, thanks to the growth of open source software
HPE is paring down its software holdings, including analytical database software in the Vertica line and other big data tools. A sale to Micro Focus is due to close next year, leaving users in some limbo for now. Continue Reading
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Feature
26 Apr 2016
Inside the MapR Hadoop distribution for managing big data
The MapR Hadoop distribution replaces HDFS with its proprietary file system, MapR-FS, which is designed to provide more efficient management of data, reliability and ease of use. Continue Reading
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Feature
29 Oct 2015
Three ways to build a big data system
In a book excerpt, author Dale Neef outlines and compares different approaches organizations can take when trying to bring a big data system into their IT environments. Continue Reading
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Feature
13 Aug 2015
How to identify master data in a multi-domain MDM program
In an excerpt from their book on managing multi-domain master data management programs, Mark Allen and Dalton Cervo explain how to identify MDM domains and your master data. Continue Reading
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Quiz
11 Jun 2015
Apache Spark architecture quiz: Do you know Spark?
Apache Spark is an open source processing engine designed for use in big data applications. Take this quiz to see if you're up to speed on Spark's history and features. Continue Reading
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01 May 2015
Key criteria for deciding if a relational DBMS meets your IT needs
For many organizations, a relational database management system will get the job done; others need to keep looking to fulfill their needs. Continue Reading
- 01 May 2015
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Answer
19 Feb 2015
Five steps to implementing an MDM program
Instituting a master data management program involves discovery, analysis, construction, implementation and sustainment processes, according to MDM expert Anne Marie Smith. Continue Reading
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Feature
27 Sep 2013
Big data, fast: Avoiding Hadoop performance bottlenecks
A variety of performance issues can bog down Hadoop clusters. But there are ways to sidestep the pitfalls and keep your big data environment humming. Continue Reading
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Feature
15 Aug 2013
Gartner describes the building blocks for a strong MDM program
MDM teams should consider these seven building blocks, outlined by Saul Judah, research director on the information management team at Gartner Inc. Continue Reading
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Tutorial
14 Feb 2011
An introduction to enterprise architecture framework and MDM patterns
Get an introduction to enterprise architecture framework and MDM enterprise architecture patterns. Learn about MDM framework concepts and a definition of SOA. Continue Reading
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Tutorial
14 Feb 2011
MDM and SOA: An introduction to SOA and the benefits of SOA
Learn about MDM and SOA and how they relate. Read an introduction to SOA and learn about the benefits of SOA in this master data management and data governance book excerpt. 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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Answer
31 Mar 2009
What are the advantages/disadvantages of database abstraction layers?
Discover the advantages and disadvantages of using database abstraction layers, as opposed to database-specific coding, and learn why abstraction layers offer maximum flexibility. 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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Quiz
18 Dec 2007
Enterprise data integration quiz
Take this enterprise data integration quiz to test your knowledge of data integration terms, trends and technologies. 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
- Answer 05 Sep 2003
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Answer
21 Jun 2002
Difference between BI in the public sector and private sector
Find out the major difference between business intelligence (BI) in the public sector and BI in the private sector and get an expert's take on trends for those using BI in the public sector. Continue Reading
- Answer 20 Mar 2002