Ask the Experts

Ask the Experts

• DBMS keys: Primary, super, foreign and candidate keys with examples

  Here's a guide to primary, super, foreign and candidate keys, what they're used for in relational database management systems and the differences among them.  Continue Reading

• What data lake governance challenges do organizations face?

  Consultant Anne Marie Smith details five challenges that an organization may face in applying data governance policies to data lakes and offers advice on how to overcome them.  Continue Reading

• What steps are key to building a data catalog?

  An enterprise data catalog can help data stewards and other users in an organization manage metadata and explore data assets. Here are 10 key steps for creating a data catalog.  Continue Reading

• What are the main features of data catalog software?

  Data catalogs are curated data portals for self-service analytics users. Learn about the capabilities of data catalog tools, vendors that sell them and how catalogs work.  Continue Reading

• What is the difference between DBMS and RDBMS?

  A relational database management system is the most popular type of database management system for business uses. Find out how RDBMS software differs from DBMS technology in general.  Continue Reading

• What is an enterprise data strategy?

  Defining a data strategy can help focus an organization's data management initiatives -- but it isn't the same as data governance. Expert Anne Marie Smith explains why.  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

• 5 to-dos for your GDPR compliance checklist

  It's never too late to fine-tune your GDPR strategy. Expert Anne Marie Smith suggests a current state analysis of your PII protections, drafting a data privacy policy and more.  Continue Reading

• What's the difference between DDL and DML?

  What's the difference between DDL and DML? Get the answer and see examples of data manipulation language and data definition language commands for SQL databases.  Continue Reading

• What does the GDPR definition of personal data include?

  The definition of personal data in the EU's GDPR data protection rules is broad enough to include any type of data that can be used to directly or indirectly identify a person.  Continue Reading

• Dimension tables vs. fact tables: What's the difference?

  Fact tables and dimension tables are used together in star schemas to support data analytics applications. But they play different roles and hold different types of data.  Continue Reading

• Operational data store vs. data warehouse: How do they differ?

  Operational data stores and data warehouses both store operational data, but the similarities between them end there -- and they both have a role to play in analytics architectures.  Continue Reading

• What are key features for choosing the best ETL tools for your needs?

  Choosing the right ETL tool for your data integration requirements can be a challenge. Here's a rundown on what to look for in ETL software and potential vendors to consider.  Continue Reading

• What do we need to optimize our MDM strategy?

  Companies in all industries can benefit from a master data management program, advises MDM expert Anne Marie Smith. Learn how to enhance yours.  Continue Reading

• How a data steward can enable data governance, without 'police' tag

  A data governance program doesn't have to be a police action. Instead, advises expert Anne Marie Smith, data stewards should help bring about cultural change in a collaborative way.  Continue Reading

• Hadoop, big data haven't eclipsed data warehousing jobs -- yet

  Hadoop and big data technologies may grab headlines, but there's still a place for traditional data warehousing skills, according to careers expert Matt Mueller.  Continue Reading

• How metadata management relates to data governance and MDM

  Why is metadata management important? Because without it, you couldn't have a successful data governance or master data management program, explains governance expert Anne Marie Smith.  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

• How to combine MDM projects and BI programs -- and boost their ROI

  Combining master data management projects and business intelligence programs can provide business value -- if the architecture is there to support it, says expert Anne Marie Smith.  Continue Reading

• Integrate data quality into your master data management strategy

  When implementing an MDM initiative, businesses should take steps to incorporate effective data quality management practices from the outset.  Continue Reading

• When does a NoSQL DB trump a traditional database?

  The unstructured data types common in big data systems are often better managed by a NoSQL database than relational software, Mark Whitehorn says.  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

• In-memory databases best suited for 'relatively small' data sets

  How does data set size determine whether an in-memory database is a good fit for applications, especially analytics uses? Mark Whitehorn explains.  Continue Reading

• Big data careers: Taking the initiative to improve your skill set

  Expert Matt Mueller offers advice to data management pros who are interested in developing their big data skill set.  Continue Reading

• Creating a data governance council: Enlist champions to lead

  Enlist senior-level champions from both business and IT to guide a data governance program and achieve harmony between the two sides.  Continue Reading

• Priming a master data management strategy for success

  Organizations should meet a few key program development goals prior to implementing an MDM initiative, according to MDM expert Anne Marie Smith.  Continue Reading

• Key issues to consider when building a data warehouse

  There are numerous issues, both technical and cultural, that organizations need to consider before building a data warehouse. Learn what they are from our data warehousing expert.  Continue Reading

• Role of a data architect in making data management project decisions

  Learn about the roles of data architects when it comes to making data management project decisions.  Continue Reading

• 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.  Continue Reading

• Six tips for improving data warehouse performance

  Get six expert tips for improving data warehouse performance. Learn how database engines, SSDs and MOLAP cubes can affect your data warehouse performance.  Continue Reading

• Emerging database technologies: How Hadoop and MapReduce compare

  Hadoop and MapReduce are two emerging database technologies. Find out how Hadoop and MapReduce compare and relate to each other.  Continue Reading

• How to get senior execs to buy into a data governance plan

  Learn how to get senior management to buy into data governance. Get tips on selling data governance policies and processes to executives who can approve data governance programs.  Continue Reading

• Do you need to gather business requirements for MDM projects?

  Do you need to gather business requirements for an MDM project? Find out and learn how functional requirements are the key difference between the MDM and BI development processes.  Continue Reading

• What are the most common MDM project pitfalls to avoid?

  Learn about the most common master data management (MDM) project pitfalls that companies run into. Get a list of the major problems that can hold back an MDM program.  Continue Reading

• What’s the best way to conduct an MDM implementation?

  Is it better for companies to go with an enterprise-wide master data management (MDM) implementation or deploy MDM departmentally? Find out which approach our MDM expert prefers.  Continue Reading

• How change data capture (CDC) and data federation differ

  Learn the difference between change data capture (CDC) and data federation. Find out how companies can use both data integration technologies to improve data warehouse systems.  Continue Reading

• 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.  Continue Reading

• 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.  Continue Reading

• Key components of enterprise information management programs

  Learn which three components of enterprise information management programs are most important for a successful EIM strategy.  Continue Reading

• What is the difference between data definition language (DDL) and SQL?

  Learn the difference between a data definition language (DDL), also known as data descriptive language, and the Structured Query Language (SQL). Find examples of both DDL and SQL.  Continue Reading

• How database performance tuning and data migration affect databases

  Find out how database performance tuning and data migration to a new database engine affect database performance. Learn about indexing columns and partitioning tables.  Continue Reading

• How to organize an enterprise conceptual data model development effort

  Find out why it’s important and how to organize an enterprise conceptual data model development. Learn how a data governance organization can help your ECDM effort.  Continue Reading

• Steps for converting a logical data model into a physical data model

  Learn how to convert a logical data model into a physical data model via data modeling best practices. Find out how DDL and your data modeling practices play a role in conversions.  Continue Reading

• Data modeling tools: Best practices for selection and evaluation

  Get best-practices advice and tips for choosing and evaluating data modeling tools. Also, learn how to define data modeling requirements and use your data governance council.  Continue Reading

• Can we enforce data integrity in a company to ensure accurate data?

  Find out if companies can enforce data integrity to ensure data accuracy in internal reports and systems. Plus, learn how data interpretation can affect the use of accurate data.  Continue Reading

• Data warehouse concepts: Data flow and sending data to source systems

  Learn about a data warehouse concept: data flow. And find out if it's a good idea to flow data from your data warehouse or data marts back to source systems.  Continue Reading

• What are aggregate tables and aggregate fact tables?

  Here you'll see examples and read definitions of aggregate tables and aggregate fact tables. You'll also learn how to use aggregate tables in data warehouses and databases.  Continue Reading

• Four common data integration issues and challenges

  Embarking on a data integration project? Make sure you know common data integration issues and challenges before beginning your next integration implementation.  Continue Reading

• Understanding five major enterprise information management benefits

  Learn about the primary enterprise information management (EIM) benefits and five major problems EIM can help solve, including data quality, information management, process efficiency, security and organizational agility.  Continue Reading

• What is the difference between a logical and physical warehouse design?

  What's the difference between logical design and physical design? Get an expert's take, plus learn about three data warehouse models -- the user model, physical model and logical model -- and how they differ.  Continue Reading

• 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

• 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

• Are there data governance plans, templates or standard procedures?

  In this Q/A, learn what resources to use to find standard operating procedures templates for your data governance program.  Continue Reading

• Defining enterprise information management (EIM) vs. other data management initiatives

  Find out about enterprise information management (EIM) vs. other data management applications and programs and learn how to maximize the benefits of an EIM initiative.  Continue Reading

• How to select an MPP database: DB2 vs. Teradata

  Should you run a massively parallel processing (MPP) database with DB2 or Teradata? Find out how to compare DB2 vs. Teradata and how to choose a database system and with advice from a data warehouse expert.  Continue Reading

• What comes first -- the data mart or the data warehouse?

  Data mart or data warehouse -- which does your company need? Learn the difference between a data warehouse and a data mart and find out what problems data marts and warehouses address in this tip.  Continue Reading

• How to get data/database independence with a three-tier architecture

  Discover how to attain database and data independence in this tip. Find out what database independence is and learn the benefits of a three-tier data warehouse vs. a two-tier data warehouse.  Continue Reading

• Tips for planning a data governance strategy and MDM strategy

  Read a data governance definition, learn about data governance and MDM and how data governance strategy plays an important role in master data management (MDM) strategy.  Continue Reading

• How important are the different styles of MDM architecture?

  Learn how to compare different MDM architecture and learn about strengths and weaknesses of different styles such as persistent MDM hubs. Also discover how to communicate the value of MDM architecture to business users.  Continue Reading

• 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

• Is an Inmon-modeled BI system, like Madison, the future of data warehousing?

  Learn the future of data warehousing, read an expert's take on Microsoft Madison, read about data warehousing concepts and methodologies and find a comparison of the core relational and dimensional data warehouse.  Continue Reading

• What are the benefits and disadvantages of a RDBMS?

  Find out about the benefits and disadvantages of RDBMS are and get examples of when relational database management systems are the best database system tools to use in this tip.  Continue Reading

• What are some SOA risks and challenges and how can we mitigate risks?

  Learn about SOA risks and challenges common when transitioning to a service-oriented architecture (SOA). Take steps to reduce risks with these SOA initiative best practices.  Continue Reading

• What is the main use of a DBMS and what is the main use of a data warehouse?

  There are distinct functions for a database management system (DBMS) and a data warehouse. Learn how to use a DMBS and how to use a data warehouse to manage data in your organization.  Continue Reading

• Defining dimensional vs. normalized database design, dimension vs. fact tables

  Find out if your existing database is in dimensional style or normalized database design style, learn the benefits and drawbacks of fact-dimension and normalized database schemas and read a comparison of dimension tables vs. fact tables.  Continue Reading

• What are the most common system implementation mistakes?

  Learn about some of the biggest mistakes in system implementation and why successful implementations are few and far between. Find out how to avoid these pitfalls with careful planning and more tips from our project management expert.  Continue Reading

• 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

• Designing the MDM team for an SAP MDM implementation project

  Get tips for creating an MDM team for an SAP MDM implementation project, including how to staff positions like MDM project managers, MDM administrators and developers, in this Q/A.  Continue Reading

• How to complete the MDM requirements-gathering analysis process

  Learn why it is important to complete the MDM requirements-gathering analysis process before evaluating MDM vendors -- and how to involve end users in the discussion.  Continue Reading

• How to estimate customer data cleansing costs

  How much on average does it cost to clean one customer record? Do you know if there been any specific reporting or analysis done on this area of customer data quality?  Continue Reading

• Definition of operational data store vs. persistent staging area

  Discover the definition of operational data store vs. persistent staging area, including how to use the operational data store and the persistent staging area effectively.  Continue Reading

• How to choose between the Inmon vs. Kimball approach for data warehouse design

  Get an overview of Inmon v. Kimball approaches to data warehouse design and business intelligence and find a checklist to help you decide on an architecture approach.  Continue Reading

• Tips for choosing a DBMS to meet your company's needs

  Learn tips for choosing a DBMS to meet your company's needs and how to evaluate database management system (DBMS) software based on cost and investment.  Continue Reading

• 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

• What are the components of service-oriented architecture (SOA)?

  What are the components that make up service-oriented SOA? Find out in this expert response.  Continue Reading

• Definition of data abstraction and data abstraction layers

  Data abstraction simplifies database design. Learn the definition of data abstraction and find out the three formal kinds of abstraction layers, from a database expert.  Continue Reading

• What business intelligence (BI) skills are required for a successful career?

  A successful business intelligence (BI) career entails developing both business and technical skills. Find out which BI skills are worth expanding.  Continue Reading

• Three data warehouse project management metrics

  Data warehouse project management requires careful planning. So learn three data warehouse project management metrics that just might make things run smoother.  Continue Reading

• Data architect vs. application architect: Segregate the duties

  Find out the duties of data architects and application architects -- and why they should not overlap, according to a data modeling expert.  Continue Reading

• How to evaluate data warehouse software in five steps

  Get five steps to evaluating data warehouse software from a data warehouse expert.  Continue Reading

• Data quality management for data warehouses

  Learn how to evaluate the risks of poor data quality in data warehouses -- and how good data quality management practices help mitigate risks.  Continue Reading

• Enterprise versus project level conceptual data modeling

  Learn the differences between enterprise level and project level conceptual data modeling, and find out how both approaches are compatible.  Continue Reading

• XML schema definition versus conceptual data model

  Learn the differences between XML schema definition (XSD) and a conceptual data model (CDM) -- and the basic functions of each.  Continue Reading

• Data model conversion: Conceptual design to logical design using an ER model

  Learn two common approaches to converting a data model from a conceptual design to a logical design.  Continue Reading

• Top three database management system (DBMS) trends

  Let three database management system (DBMS) trends that may surprise you.  Continue Reading

• Can a dimension table be a fact table for another data mart?

  Find out if a dimension table can be a fact table for another data mart -- and get an explanation of the answer.  Continue Reading

• Four guidelines for enterprise conceptual data model (ECDM) entity selection

  Get four guidelines for deciding what entities to include in an enterprise conceptual data model (ECDM).  Continue Reading

• Chief Compliance Officer: Top three responsibilities of a CCO

  Learn the top roles and responsibilities of a Chief Compliance Officer (CCO).  Continue Reading

• Sarbanes-Oxley compliance: GRC technology vs. spreadsheets

  Learn why Sarbanes-Oxley (SOX) compliance technology, such as GRC management platforms, is better than spreadsheets for meeting Sarbanes-Oxley requirements.  Continue Reading

• Database administrator job roles: Organizing the DBAs

  Learn how to organize database administrators (DBAs) and determine roles when there are multiple DBAs.  Continue Reading

• Data modeling for data warehouse projects

  Learn how to begin a data warehouse project and why creating a data model is an important step.  Continue Reading

• What is high quality information?

  Learn a definition of high quality information, and find out what it means for overall data quality.  Continue Reading

• Data warehouse development: Four strategic steps

  Learn the basics of data warehouse development in four strategic steps, from expert William McKnight.  Continue Reading

• Logical database design

  Logical database design involves two distinct processes, according to DBMS expert Mark Whitehorn.  Continue Reading

• The ETL process and MySQL

  Get advice on the ETL process and ETL tools for transforming raw data in MySQL.  Continue Reading

• Centralized database systems vs. data silos for master data storage

  Learn when it may be best to have master data in a centralized database system vs. stored in data silos, according to DBMS expert, Mark Whitehorn.  Continue Reading

• The latest database management system (DBMS) trends

  Learn what several of the latest database management system trends are, as suggested by our DBMS expert Mark Whitehorn.  Continue Reading

• Data architecture vs. information architecture

  Learn about the differences between data architecture and information architecture, as well as the relationship between the two.  Continue Reading

• What are the benefits of a conceptual data model?

  Learn the functions and potential benefits of a conceptual data model, from data modeling expert Pete Stiglich.  Continue Reading

• ERP reporting tools' advantages and disadvantages

  Learn about the benefits and drawbacks of enterprise resource planning (ERP) reporting tools.  Continue Reading