Features

Features

• DBA skills must evolve, morph to cope with big data technologies

  Big data tools are changing data architectures in many companies. The effect on the skill sets required by database administrators may be moderate, but some new IT tricks are likely to be needed.  Continue Reading

• Mullins: Changing DBA responsibilities highlight profession in flux

  Author Craig Mullins discusses the evolving responsibilities of database administrators due to NoSQL systems and a growing need for mixed database management system environments.  Continue Reading

• Hadoop fuels TrueCar's data-driven business model

  Piles of "messy" data meet inexpensive storage as e-commerce website TrueCar builds a data-driven business with the help of a Hadoop cluster and data analytics tools.  Continue Reading

• For Hadoop architecture, 'a lot of maturity' still needed

  Hadoop has yet to be as widely adopted as consultant Joe Caserta expected -- and maturity issues are a big reason, he says in a Q&A on the much-discussed big data framework.  Continue Reading

• Ten years on, master data management software market comes of age

  It has been 10 years since the master data management industry emerged. MDM technology is maturing, and project success rates are on the rise -- but there's still a long way to go.  Continue Reading

• Is it too soon for unstructured data governance?

  Data industry veteran Anne Marie Smith discusses pressing issues, including the barriers to unstructured data governance. Part one in a series on data matters.  Continue Reading

• Varied NoSQL technologies need careful weighing and sorting

  The number of NoSQL database options is vast, and distinct product categories occupy separate niches. That makes it imperative to understand what works best for specific applications when evaluating NoSQL software.  Continue Reading

• MongoDB founder on dynamic schemas and caching as a crutch

  The train to NoSQL rode the rails of agility and scalability, according to Dwight Merriman, MongoDB co-founder.  Continue Reading

• Perspective and preparation: Data modeling concepts still vital in business

  In this book excerpt, data modeling instructor Steve Hoberman discusses the importance of using modeling for business success and the variety of implementations for data models.  Continue Reading

• NewSQL database sends NoSQL technology packing at logistics exchange

  DropShip Commerce went from SQL to NoSQL to NewSQL software to run its B2B platform, settling on a NuoDB database to help support its business growth.  Continue Reading

• NoSQL databases dent relational software's data processing dominance

  NoSQL software has broken the IT monopoly of relational databases, but it isn't likely to completely break the bonds between users and SQL technology.  Continue Reading

• Chief information architect: A compass for information management

  In a Q&A, author William McKnight discusses the importance of building a robust information architecture -- and having the right person in the lead.  Continue Reading

• Hadoop YARN adds more application threads for big data users

  Hadoop 2's new YARN resource manager ends the distributed processing framework's marriage to MapReduce. And that broadens what Hadoop systems can do.  Continue Reading

• Data quality assessment requires business ties -- and a human touch

  In an interview, author and data quality architect Laura Sebastian-Coleman discusses steps organizations should take to improve data quality levels.  Continue Reading

• Identifying data quality issues via data profiling, reasonability

  In a book excerpt, author Laura Sebastian-Coleman explores data profiling, data issue management and using reasonability checks in assessing quality.  Continue Reading

• Dissecting data measurement: Key metrics for assessing data quality

  In a book excerpt, data quality architect Laura Sebastian-Coleman explains data assessment terminology and details a framework for measuring quality.  Continue Reading

• Hadoop 2 FAQ: Upgrade spins new YARN, breaks MapReduce bonds

  Hadoop 2 is a big step forward for the distributed processing framework, now freed from its reliance on MapReduce. Get details on its key features.  Continue Reading

• Integrating data warehouse architecture with big data technology

  This book excerpt discusses considerations for the physical integration of big data technologies into the data warehouse architecture.  Continue Reading

• In relational database design, don't shortchange requirements stage

  Requirements gathering shouldn't get short shrift in the database rush, says Michael J. Hernandez, author of 'Database Design for Mere Mortals.'  Continue Reading

• Graph database powers Onefinestay's room accommodation platform

  Onefinestay CTO Jackson Hull led a team that used a graph database to help make vacationers feel at home with its online house-booking service.  Continue Reading

• 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

• Big data architecture adds integration options -- and tool needs

  Mixing data warehousing and big data technologies creates new opportunities for data integration, but also calls for new types of integration tools.  Continue Reading

• Big data adds new complications for data stewards

  In order to accommodate big data and the needs of data scientists, data stewards will need to adjust to a more short-term view of data stewardship.  Continue Reading

• Big data systems shine light on neglected 'dark data'

  The processing power of Hadoop and other big data tools is making it more feasible for companies to tap into dark data, information that previously was left untouched in IT systems.  Continue Reading

• It takes more than technology to achieve big data success

  Organizations mulling a big data initiative should forget the hype, come up with a solid business case and put the right team together.  Continue Reading

• 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

• Data virtualization technology speeds up decision making at Pfizer

  Data virtualization technology is quickening the pace of drug development at pharmaceutical giant Pfizer.  Continue Reading

• MDM program needs business sense to be successful

  It is essential that project teams engage the support of business executives to ensure the success of a master data management program.  Continue Reading

• Enterprise master data management and big data: A well-matched pair?

  While the relationship between enterprise MDM and big data is uncertain now, analysts predict that they may be more closely linked down the road.  Continue Reading

• Business data quality measures need to reach a higher plane

  Consultant Andy Hayler says survey results show that data quality levels haven't improved in recent years, despite increased efforts by companies.  Continue Reading

• Data warehousing architect helps Pfizer make better business decisions

  Pat Saucier, a data warehousing and information architecture manager at Pfizer Inc., talks about how the relationship between data and business operations has changed during his career.  Continue Reading

• IT as a Service transforming traditional IT departments

  Today, end users can easily sidestep IT to get the app they need. This new competition is prompting IT to take action -- delivering IT as a Service -- to stay relevant.  Continue Reading

• Enterprise data quality efforts in good company with MDM, governance

  Combining data quality initiatives with master data management and data governance programs can help ensure that data remains accurate and consistent.  Continue Reading

• Better data quality process begins with business processes, not tools

  Efforts to improve data quality should start with procedural changes to help avoid data errors, then the possible addition of data quality software.  Continue Reading

• Pfizer swaps out ETL for data virtualization tools

  When a research and development division of pharmaceutical maker Pfizer Inc. ran into data integration struggles, it decided to go virtual.  Continue Reading

• Successful data stewardship framework needs solid plan, firm focus

  Stewarding data can be a tough nut to crack: lots of effort for a reward that isn't always apparent. To succeed, strong project management is needed.  Continue Reading

• Pella opens window of opportunity with database virtualization software

  Window maker Pella uses virtual databases for testing and development. Its advice: IT pros eyeing the technology should get elevator pitches ready.  Continue Reading

• Data stewardship program: Quality booster, but a hard step for many

  While data stewardship can help improve the quality of corporate data, analysts say there's more talk than action when it comes to adopting the concept.  Continue Reading

• Make communication, purpose priorities in a data governance program

  Data governance can be all bureaucracy and no benefit. To avoid that, managing the process effectively is a must, says consultant Danette McGilvray.  Continue Reading

• Decision time: Automated data integration tools versus manual coding

  In many companies, data integration remains a manual task -- by choice. But it might be time to automate that process, says consultant Rick Sherman.  Continue Reading

• Mission impossible? Data governance process takes on 'big data'

  Effective governance can help companies get the most out of their "big data" environments. But at this point, there's no formula for how to do that.  Continue Reading

• Internal data quality standards not just a game for business users

  Ensuring that business users follow corporate standards when entering and updating data is vital to the success of data quality improvement efforts.  Continue Reading

• Data quality process needs all hands on deck

  Data accuracy is critical in technology-driven business processes, making it a must to involve business users in data quality efforts, analysts say.  Continue Reading

• 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.  Continue Reading

• 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

• Transaction processing system examples and SOA approaches

  Learn about transaction processing systems, processing systems components, and different service-oriented architecture approaches including representational state transfer.  Continue Reading

• Key benchmarks for measuring transaction processing performance

  Find key benchmarks for measuring transaction processing performance at your company, and learn about XA two-phase commit and types of transaction processing.  Continue Reading

• Understanding and comparing six types of data processing systems

  Learn about six types of processing systems and how transaction processing systems compare with batch processing, real-time, data warehouse, timesharing and client/server systems.  Continue Reading

• William McKnight's contributions to SearchDataManagement.com

  Access all of William McKnight's data warehouse and business intelligence advice and best practices.  Continue Reading

• Top eight data and application integration definitions and buzzwords

  Get the top data and application integration definitions, terms, buzzwords and concepts in this guide. Also, find links to helpful integration tutorials, training, articles and expert advice.  Continue Reading

• Master Data Management (MDM) Platform Product Directory

  This MDM software product directory provides information about major MDM, PIM and CDI vendors that can help improve MDM in your organization, as well as expertise advice on choosing the right MDM tool.  Continue Reading

• Data modeling concepts: How settings can increase application success

  In this book excerpt, learn how four camera settings translate directly to the data model, and how understanding these data modeling concepts can increase the chances of a successful application.  Continue Reading

• How to shred XML with the DB2 XMLTABLE function

  In this XML guide, learn how to shred XML using the DB2 XMLTABLE function with detailed examples. Find out when you should store XML in a hybrid fashion and how to create relational views over XML data.  Continue Reading

• Shredding XML docs into relational tables with annotated XML schemas

  In this XML tutorial, find out how to shred XML documents into relational tables with annotated XML schemas with 14 examples. Plus, learn how to define schemas visually in IBM Data Studio.  Continue Reading

• Advantages and disadvantages of XML shredding

  Learn about the advantages and disadvantages of XML shredding and different shredding methods, plus find out when shredding is and isn't a good option for your company.  Continue Reading

• Guidelines for managing data updates to optimize ODBC performance

  Looking to optimize your ODBC applications and functions? Find guidelines for updating data and managing your data updates efficiently and how to improve ODBC performance.  Continue Reading

• Selecting ODBC functions for optimized SQL statements

  In this book excerpt, you'll find best practices guidelines for deciding what ODBC function to use when executing SQL statements and how to use bound columns.  Continue Reading

• How to capture metadata information, ETL rules with CA Erwin Data Modeler

  Learn how to capture and retrieve metadata information such as extract, transform, load (ETL) rules by using CA Erwin Data Modeler. This data modeling excerpt also covers step by step of how to capture the ETL information using and the generating of...  Continue Reading

• Static SQL vs. dynamic SQL for database application performance

  Learn the difference between static SQL vs. dynamic SQL and the benefits and drawbacks of each for database application performance. Get a definition of stored procedure, find out about database drivers and wire protocol database drivers and how the...  Continue Reading

• An introduction to database transaction management

  Find out the performance advantages of using one connection for multiple statements in this database tutorial. Get a definition of local vs. distributed transactions and learn how to manage database transactions.  Continue Reading

• Executing SQL statements using prepared statements and statement pooling

  In this database tutorial, find out about executing SQL statements using prepared statements and statement pooling. Learn what a statement pool is and how to retrieve long data types efficiently.  Continue Reading

• 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

• Best practices for data warehouse access and reports

  Get best practices techniques for querying and accessing data warehouses with reports, OLAP and dashboards. Learn about common OLAP operators including roll-up, drill-down, and slice-and-dice.  Continue Reading

• Similarities and differences between ROLAP, MOLAP and HOLAP

  Find out the differences between ROLP, MOLAP and HOLAP and their advantages and disadvantages. Learn about data quality and the evolution of data warehouse applications.  Continue Reading

• Data warehouse architectures, concepts and phases: What you need to know

  This tutorial explains the different types of data warehouse architecture including bus, federated and hub-and-spoke. Learn about ETL processes and data staging and data warehouse phases.  Continue Reading

• Advantages of the multidimensional database model and cube modeling

  Discover the advantages of the multidimensional database model and find out how data warehouse cube modeling, data restricting and data slicing work. Learn the role meta-data plays and get a definition of functional dependency.  Continue Reading

• An introduction to data warehousing and decision support systems

  Get an overview of data warehousing and learn data warehousing concepts and techniques, including how data warehouse technologies are used. Read a decision support system definition in this data warehousing book excerpt and tutorial.  Continue Reading

• 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

• Data modeling for the business: What is a data model?

  Learn about high-level data modeling, what a data model is and how business and IT can use logical data modeling to plan a data design with these best practices from a data modeling handbook and guide.  Continue Reading

• 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. ...  Continue Reading

• Master data management as a service-oriented architecture enabler

  Learn how master data management provides service-oriented architectures a single location from which to manage data entities that are critical to enterprise processes.  Continue Reading

• Why do we need master data management systems?

  Learn how master data management systems can help companies manage "unmanaged" data, in a chapter from "Enterprise Master Data Management: An SOA Approach to Managing Core Information."  Continue Reading

• Business benefits of managed master data

  Learn three ways master data management systems can benefit a business, according to the authors of "Enterprise Master Data Management: An SOA Approach to Managing Core Information."  Continue Reading

• What is a master data management system?

  Learn the three dimensions of master data management (MDM) systems, as outlined by the authors of Enterprise Master Data Management: An SOA Approach to Managing Core Information."  Continue Reading

• Introduction to enterprise master data management

  Get an introduction to enterprise master data management (MDM) basics in this chapter excerpt from "Enterprise Master Data Management: An SOA Approach to Managing Core Information."  Continue Reading

• 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

• Understanding IBM DB2: Product history and strategy

  Learn the history of IBM DB2 development and get a list of DB2 information management products.  Continue Reading

• Database management: How to protect your electronic security systems

  Learn how to protect electronic security systems -- from a database management perspective -- by focusing on 10 vulnerable areas, in this free chapter download  Continue Reading

• 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

• 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.  Continue Reading

• How to define data, information and knowledge

  Learn how data, information and knowledge are defined, discover the difference between data and information, and find out how to turn data into knowledge.  Continue Reading

• Improving business agility with loose coupling and a Web services oriented architecture

  Learn how loose coupling between business and organization processes, and a Web services oriented architecture, affect business agility, in this free chapter download.  Continue Reading

• Agile information systems: How to align IT with business

  Learn about agile information systems and how to align IT strategy with business agility, in this free chapter download.  Continue Reading

• Developing quality metadata and designing workflow

  Learn how to design an efficient workflow and read about the role of quality metadata in workflow management, in this chapter excerpt.  Continue Reading

• 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.  Continue Reading

• Definitions of design and data modeling

  Get a comprehensive definition of data modeling and learn about the issue of "design" versus "description" in a data modeling context.  Continue Reading

• What is a data model?

  Learn the definition of data modeling and get data modeling basics in this downloadable chapter excerpt.  Continue Reading

• Introduction to network analysis, architecture and design

  Learn tha basics of network analysis, architecture and design, as well as various ways to characterize a network.  Continue Reading

• Introduction to service-oriented architecture: What is SOA?

  Learn the benefits of service-oriented architecture, and the structure of service-oriented applications, in this chapter excerpt, appropriate for business and technical readers.  Continue Reading

• Business process change: A guide for business managers and Six Sigma professionals

  Learn the history and various perspectives of business process change to better understand the current technologies available to business managers.  Continue Reading

• What is a certified business intelligence professional (CBIP)?

  Becoming CBIP certified is entirely dependent on passing three exams, and there are two levels of certification.  Continue Reading

• Continuous integration: The value of CI

  Learn about the value of continuous integration and get reasons why continuous integration can benefit the enterprise in this free sample chapter download.  Continue Reading

• Multiuser application design strategies for Microsoft Access

  Learn multiuser application design strategies for Microsoft Access in this chapter excerpt as the author weighs the pros and cons of various multiuser application design options.  Continue Reading

• Change management: Reasons for change resistance

  Learn about IT change management, read about passive and active resistance and get 20 reasons why employees resist enterprise change.  Continue Reading

• Change management and system implementations: Nine major risks

  Change management and system implementations have many risks. Learn nine specific areas where system implementations can go wrong.  Continue Reading

• Enterprise architecture components

  Seventeen components of an enterprise architecture are classified and described in this chapter download.  Continue Reading

• 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 ...  Continue Reading

• 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.  Continue Reading

• 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

• Data quality management: Problems and horror stories

  Data quality management is not easy, as is evidenced by these true horror stories of data quality gone wrong. Learn from (and wince at) these mistakes to avoid problems with your own data quality projects.  Continue Reading