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• SQL Server auditing best practices: 3 key questions for DBAs

  Acing a SQL Server database audit starts with careful monitoring of how sensitive data is accessed and used so you can answer the top questions that auditors ask. Continue Reading

• 5 best practices for managing real-time data integration

  Real-time data integration isn't like traditional data integration -- "it's moving, it's dirty and it's temporal," cautions one data pro. Experts offer up some best practices. Continue Reading

• 5 trends for SQL Server environments as SQL Server 2019 looms

  SQL Server is undergoing new changes, as Microsoft prepares to release the 2019 version of the database software. Other changes are also on tap for SQL Server users. Continue Reading

• Why organizations need a solid data governance strategy

  The flood of data flowing into data warehouses, data lakes and other systems makes effective data governance a must for successful business analytics initiatives. Continue Reading

• Data management trends for 2019: Governance, DataOps, cloud

  Better data governance, increased cloud use and wider DataOps adoption head the list of trends for data management teams to plan for in 2019, IT analysts say. Continue Reading

• How data duplication in healthcare is diagnosed

  Electronic health record systems have helped reduce duplicate patient data in hospitals -- but they haven't cured the problem. Find out how organizations are addressing the issue.Continue Reading

• 5 FAQs on SQL Server containers and how to manage them

  Running SQL Server in containers creates new challenges for database administrators. The answers to these questions can guide you through some of them.Continue Reading

• The most useful new features in Microsoft SQL Server 2019

  SQL Server 2019 includes welcome new features, particularly updates to its indexing and high availability capabilities and added SQL Server on Linux functionality.Continue Reading

• How to build a master data index: Static vs. dynamic indexing

  Expert David Loshin explores the differences between static and dynamic indexing in master data management systems, and which queries each approach can support.Continue Reading

• How deterministic and probabilistic matching work

  Expert David Loshin explores the benefits and challenges of the two classes of record matching in master data management systems: deterministic matching vs. probabilistic matching.Continue Reading

• 11 features to look for in data quality management tools

  As the need for quality data has increased, so have the capabilities of data quality tools. Learn how collaboration, data lineage and other features enable data quality.Continue Reading

• Big data platform broadens place in analytics architecture

  Big data platforms stumbled a bit getting out of the prototyping stage. But a view from the Strata Data Conference in New York sees broader use in the offing.Continue Reading

• The gradual evolution of master data management software

  Master data management began with a bang, then hit roadblocks due to complexity. Now, MDM is shifting toward more pragmatic projects tied to data governance.Continue Reading

• Mining equipment maker uses BI on Hadoop to dig for data

  BI on Hadoop is still new, but moving BI to data is trending. A data scientist working with IoT data at Komatsu sees the importance of getting big data to the right people.Continue Reading

• 4 strategies to beat the SQL Server 2008 support cutoff

  The looming end of SQL Server 2008 extended support should spur database teams into action. Consider these four options to extend security updates or migrate your aging SQL Server systems.Continue Reading

• What is the best structure for data governance programs?

  The optimal approach to a data governance framework includes a program team, a data governance council and stewards. Expert Anne Marie Smith explains what role each group plays.Continue Reading

• SQL Server high availability best practices in the cloud

  The cloud isn't immune to system failures. You can increase database uptime and prevent data losses with these high availability best practices for SQL Server in the cloud.Continue Reading

• Why data quality tools matter in today's organizations

  Data is everywhere -- but is it good? Data quality tools could answer that question and help save time and money. So why don't more organizations use the technology?Continue Reading

• GDPR checklist items data managers might have overlooked

  Now that the General Data Protection Regulation has been implemented, it's a good time for organizations to make sure they haven't missed any GDPR best practices.Continue Reading

• How to manage data and the GDPR right to be forgotten

  The General Data Protection Regulation requires organizations to delete personally identifiable information if customers ask -- which can be a challenge. Experts offer four tips.Continue Reading

• How graph data modeling can help evaluate database tools

  Mapping data to a graph model can be challenging, but these steps can help you create prototype applications -- which then can aid in evaluating graph databases.Continue Reading

• When to choose an S3 big data environment over HDFS storage

  Selecting a storage service for big data in the cloud can be challenging. Expert David Loshin explains usage patterns that could lead organizations to Amazon Simple Storage Service.Continue Reading

• Four first steps for customer data management

  Forrester's Mike Gualtieri details how to develop a unified plan to manage customer data that gives business users what they need to manage CRM programs.Continue Reading

• Evolving data integration strategies target new analytics needs

  Most companies don't have a shortage of data, but it's often stored in siloed systems or inconsistent formats -- problems that data integration programs need to address.Continue Reading

• What goes into a customer analytics data integration framework

  Customer data integration is a minefield for IT teams to navigate. But incorporating a set of core technical functions into an integration architecture can ease the process.Continue Reading

• Six data risk management steps for GDPR compliance

  By layering data risk management processes into your data governance framework, you can ensure the personally identifiable information your company stores meets GDPR compliance rules.Continue Reading

• CockroachDB database wagered on for scalability boost, GDPR

  CockroachDB is an open source distributed database designed for processing on a global scale, a need that online gambling company Kindred Group hopes it can meet.Continue Reading

• What the Microsoft GDPR compliance toolkit offers for SQL Server

  The set of GDPR compliance tools that Microsoft offers for SQL Server is designed to make it easier for users of the database software to adhere to the EU's new data rules.Continue Reading

• GDPR data protection edicts make good data governance a must

  The European Union's new GDPR law puts the onus on companies to ensure that their data governance and management practices enable them to comply with its requirements.Continue Reading

• GDPR rules can spur broader steps to protect sensitive data

  Companies need to make compliance with GDPR's requirements on managing personal data a priority, but they should also work to implement wider data protection efforts in the future.Continue Reading

• Security of big data fashions a whole new look with GDPR

  As data managers scramble to protect their precious lakes of washed and unwashed data from the evils of hacking, malware, ransomware and botnets, there comes a privacy regulation of European Union origin that could change the way many U.S. companies...Continue Reading

• IoT, edge computing spawn new security issues

  As real-time big data increasingly hitches up to internet of things, edge computing power and fog nodes, a whole new layer of security threats emerges.Continue Reading

• 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

• Information architecture applied to big data streaming, AI

  New technologies challenge data professionals, but taking a step back helps with hurdles. In this interview, consultant William McKnight takes a measured look at data streaming, GDPR and AI.Continue Reading

• Cloud workloads, data lakes challenge information architecture

  Data management options are expanding; cloud workloads are an example. That means changing your approach to information architecture, says data management expert William McKnight.Continue Reading

• GDPR mandates push data quality improvement into IT spotlight

  Data quality issues cost companies significant amounts of money in lost revenue and added expenses, and their impact will only get bigger when the EU starts enforcing its GDPR law.Continue Reading

• IT, others focus efforts as GDPR implementation date looms

  The EU's General Data Protection Regulation is meant to bring better data privacy to bear in the age of big data. How GDPR implementation will proceed remains to be seen.Continue Reading

• Data expert: GDPR deadline is an opportunity, not a burden

  There is stress as the EU's General Data Protection Regulation compliance deadline nears, but the GDPR privacy movement is a good thing for data policies, advises consultant Daragh O Brien.Continue Reading

• Data lake concept needs firm hand to pay big data dividends

  Data lakes pose technology deployment and data management challenges that can leave analytics users high and dry if the implementation process isn't handled properly.Continue Reading

• Data analytics architecture must break down higher ed silos

  Siloed data isn't only a problem for businesses. It's also a big issue for many large universities -- one that their data infrastructures need to resolve for effective analytics.Continue Reading

• Data catalog software takes open data initiative to the streets

  Data catalog software from Alation helped San Diego's chief data officer open up the city's data to residents, as well as city planners and other government workers.Continue Reading

• 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

• How SQL Server containers in Docker can ease database deployment

  Docker containers can make the SQL Server deployment process more efficient and flexible. Here's what they are and how to get started on creating containers for SQL Server databases.Continue Reading

• 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

• Many say yes to NoSQL software for easing big data management woes

  NoSQL software is seen answering the need for a more flexible database framework to capture, manipulate and analyze massive amounts of unstructured data.Continue Reading

• Options for scaling out SQL Server applications to boost workloads

  Scaling out a database to meet the needs of a heavy processing workload can be a challenge. Here are details on the SQL Server scalability methods available to ease the process.Continue Reading

• 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

• 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

• Sort through types of database management systems before you buy

  The database management system lies at the center of any organization's business activities. It houses the data that pumps life into operations and analytics applications and ensures that it's managed and manipulated securely. But the types of ...Continue Reading

• How to determine if an in-memory DBMS is right for your company

  Database expert Craig S. Mullins examines the pros and cons of the in-memory database management system, and the criteria you should consider during the request-for-proposal and evaluation period.Continue Reading

• 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

• Quiz: How do relational databases and NoSQL technologies compare?

  Take this quiz to see what you know about the recent developments in the world of RDBMS and NoSQL databases technologies.Continue Reading

• Seven best practices to boost big data governance efforts

  Governing big data is much like governing other data, though businesses must adjust governance processes to accommodate larger, more varied data sets.Continue Reading

• Former shadow IT worker helps bring analytics data into the light

  Ryan Fenner worked in a shadow IT unit at Union Bank for years. Now he's helping lead an IT effort to better manage BI data created in those shadows.Continue Reading

• Big data cloud is changing familiar database tech tune

  New cloud database applications that increasingly fall into the "big-data-intensive" category are shaking up the usual build-or-buy soliloquy.Continue Reading

• Supermarket co-op stocks up on big data platform to help spur sales

  Co-operative Allegiance Retail Services is deploying a cloud-based big data stack to replace a homegrown system that fell short on analytics power.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

• Using data profiling techniques -- and estimating the effort required

  Data profiling is a key part of data quality efforts. Here's a simple formula for calculating the amount of time needed to profile a data set.Continue Reading

• Building an effective data governance framework

  This essential guide examines data governance and data stewardship from various angles, outlining best practices and answers to common challenges.Continue Reading

• Quiz: Improving your data governance and data stewardship program

  Do you know what it takes for an effective data governance structure to take root in an organization? Take this quiz and find out.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

• Data steward role needs some shepherding itself

  Consultant David Loshin gives suggestions for building and managing a data stewardship program that can effectively support data governance.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

• Data governance tools: Part, but not all, of the governance puzzle

  While tools designed for data governance are helpful, organizations must also implement best practices and standard processes to be effective.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

• 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

• 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

• 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

• Categorizing 'big data' processing systems

  In the past, analytics applications typically were powered by relational databases. Now the options are more varied and less straightforward, says TechTarget's Wayne Eckerson.Continue Reading

• From the Editors: Database consolidation and standardization 101

  If you’re thinking about embarking on a database consolidation or standardization project, make sure you know the technical, cultural and skill-set issues that can arise.Continue Reading

• Structuring data integration models and data integration architecture

  Get tips on structuring data integration models and data integration architecture. Learn how to build a business case for data integration modeling and leverage process modeling.Continue Reading

• Using logical data models for data integration modeling

  Learn about using logical data models for data integration modeling. Get an overview of using a target-based data integration design technique.Continue Reading

• From the Editors: Analytical MDM sets up enterprise MDM, but plan well

  An analytical master data management project can be a great way to start an enterprise MDM program, but with certain conditions. Get tips for starting an analytical MDM project at your company.Continue Reading

• The evolution of MDM architecture

  Find out how MDM architecture has changed over the years and gain insight on architectural considerations to take into account when planning an MDM program and system.Continue Reading

• 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

• 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

• Data governance roles and responsibilities call for diverse skill sets

  Learn about data governance roles and responsibilities, and get advice on the management and technical skills that a successful data governance strategy and program requires.Continue Reading

• Data integration maturity levels and the future of data integration

  Read about current data integration maturity levels, data integration trends, how data integration technologies have evolved and the future of the data integration market.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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• Types of DBAs

  DBAs can take on many different roles. This excerpt from the "Database administration: The complete guide to practices and procedures" takes a closer look at different types of DBAs.Continue Reading

• What is the difference between DB2 UDB and DB2 OS/390?

  Database expert Craig Mullins explains the differences between DB2 UDB and DB2 OS/390. He begins by clarifying that the two are comprised of completely different code bases.Continue Reading