Tips

Tips

• Data virtualization benefits seen in unified views, IT agility

  Through in-place integration, data virtualization platforms can provide wider access to data and simplify security and governance. But they come with some limitations.  Continue Reading

• Key features to create a SQL Server audit trail in databases

  SQL Server offers a set of built-in auditing tools that can help make the process of tracking logins and other database activities easier for database administrators.  Continue Reading

• The evolution of the data preparation process and market

  Organizations have long struggled with inconsistent data and other issues. Expert Andy Hayler explores how that has led to the rise of the data preparation tools market.  Continue Reading

• Check SQL Server Query Store performance impact before using

  Many IT teams hesitate to use SQL Server Query Store due to performance concerns. Consultant Andy Warren offers tips on how to test and get started with Query Store.  Continue Reading

• SQL Server performance tuning best practices for DBAs

  Tuning database performance is a complex process, but consultant Joey D'Antoni details a list of SQL Server performance tuning best practices that can make it easier.  Continue Reading

• Pros and cons of using SQL Server audit triggers for DBAs

  Using triggers to capture audit information in SQL Server can be instrumental in keeping track of database use and changes. But they aren't a perfect fit for all cases.  Continue Reading

• 5 things to know about deploying big data systems in data containers

  Planning for security and container APIs, and watching out for infrastructure sprawls are some issues to be aware of before deploying big data in containers.  Continue Reading

• Google Cloud Spanner overview: 4 features to consider

  Cloud Spanner's ability to offer data consistency and horizontal scalability has helped the relational database service gain traction. Learn more about its architecture.  Continue Reading

• How to resolve and avoid deadlocks in SQL Server databases

  Deadlocks are a real hindrance to SQL Server users, but database administrators can avoid them by taking steps to limit them and stop them from recurring.  Continue Reading

• Why data silos matter: Settling ownership of data issues

  Data management is often still seen as an IT task, but that can lead to data silos. Find out why the business should be in charge of its data as part of a governance process.  Continue Reading

• 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

• 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

• SQL Server 2019 improves Linux, container support

  The SQL Server 2019 release includes new big data integration features, a collection of database engine enhancements and improved Linux and container support.  Continue Reading

• Trifacta data prep tool helps blend disparate data sources

  Handling diverse data sources usually consumes precious developer time. That led healthcare CRM company SymphonyRM to hand the data prep task to business analysts.  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 Power BI-PowerShell cmdlet cheat sheet

  DBAs can manage Power BI data sets, workspaces and reports with PowerShell. Using the two tools together makes for a more efficient and effective workflow.  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

• 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

• 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

• 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

• 2 ways to attach SQL Server database files to Linux containers

  SQL Server files can be stored outside of Docker containers in host directories or volumes. Here's how to set up SQL Server on Linux databases and attach them to containers.  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 attach databases to custom SQL Server containers

  Deploying SQL Server in Docker containers for production applications typically requires custom containers. Here are guidelines on how to attach databases to them.  Continue Reading

• Good data quality for machine learning is an analytics must

  As companies add machine learning applications, they need to really understand -- and be able to improve -- their data. That's where data quality initiatives come in.  Continue Reading

• Six sample databases for SQL Server and how to find them

  SQL Server sample databases are useful for test and dev, but they can be difficult to parse. Use this SQL database sample overview to decide which to use and how to access them.  Continue Reading

• A quick tutorial on SQL Server maintenance plans

  SQL Server maintenance plans get a bad rap, but for DBAs who need a simple way to maintain databases, Microsoft's built-in tools are a good place to start.  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

• The benefits of columnar storage and the Parquet file format

  What's behind Apache Parquet's growing popularity? It may be the file format's columnar storage orientation, which leads to benefits including improved query performance.  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

• Three factors for protecting sensitive data in the GDPR era

  Data privacy is a hot topic nowadays thanks to GDPR and the Facebook data scandal. But how do data security, access control and data protection differ?  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

• Data integration techniques to help keep BI data consistent

  Data integration processes that aren't managed properly can create inconsistent data in BI and analytics applications. Here are some steps to avoid that problem.  Continue Reading

• Why Spark DataFrame, lazy evaluation models outpace MapReduce

  Learn how the Spark DataFrame execution plan works and why its lazy evaluation model helps the processing engine to avoid the performance issues inherent in Hadoop MapReduce.  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

• Why running SQL Server on Docker is no longer frowned upon

  Microsoft now lets SQL Server databases run in Docker containers, a capability that depends on using volumes to store data in a persistent way outside the containers.  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

• 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

• 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

• 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

• 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

• Relational database design tips to boost performance

  As relational database management systems handle more and more data, a strategic approach to data modeling has become vital.  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

• 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

• 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

• 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