Features

Features

Data quality techniques and best practices

• Alternative data in finance holds potentials and risks

  Alternative data sources, when verified as reliable and trustworthy, can be an essential tool for financial institutions when it comes to gathering information.  Continue Reading

• Data governance and COVID-19 data security challenges

  Maintaining data governance and data security best practices is essential now more than ever. But the increase in working from home can put a strain on those practices.  Continue Reading

• Common data lake challenges and how to overcome them

  Managing the data contained in your enterprise data lake presents many challenges. From the amount of data to data inconsistencies, here are some solutions to common issues.  Continue Reading

• How data governance and data management work together

  Data governance is an important part of data management. These recommendations will help build a strong complementary relationship between the two strategies.  Continue Reading

• How to build an effective streaming data architecture

  Data architecture can be tricky when it comes to real-time analytics. Clear objectives and scalability are important factors when determining the streaming data architecture you need.  Continue Reading

• Data governance metrics: Data quality, data literacy and more

  Statistics on data quality are the most common metrics used to track data governance programs, but other types of data-related measurements also can be applied.  Continue Reading

• Breaking down data silos with strong data governance

  Not having a single source of truth can be a huge issue for data professionals. But strong data governance policies can prevent data silos and lead to better-quality data.  Continue Reading

• Proactive practices for data quality improvement

  Instead of waiting for data quality to become an issue, consider a proactive approach. Here are ways to improve data quality in your organization before it's a problem.  Continue Reading

• Evaluate your data governance and privacy best practices

  GDPR and CCPA have put data governance in the news. With this increase in data legislation, now is a great time to review your company's data governance policies.  Continue Reading

• How to improve data governance for self-service analytics

  Citizen data scientists and self-service analytics are on the rise as the data scientist shortage continues. Here are some data management best practices to support them.  Continue Reading

• Data catalog management for analytics fraught with unique demands

  Data catalogs for analytics applications demand detailed assessment of user needs, cross-functional teams, ready access, continuous improvement and a self-sustaining system.  Continue Reading

• How to streamline feature engineering for machine learning

  Structured data is necessary in machine learning, but sifting through data is time consuming. Streamlining the feature engineering process can help data scientists be more productive.  Continue Reading

• How AI could save the enterprise data catalog

  Enterprise data catalogs record all the databases and files in a corporation, but sometimes it can become out of date. Advances in AI are helping minimize the problem.  Continue Reading

• DOD CDO shares 7 data management best practices

  The DOD's first chief data officer, Michael Conlin, shares tips on how organizations can modernize their data management practices with the objective of matching private enterprise.  Continue Reading

• Align business and IT drivers through data quality best practices

  Information management consultants talk about the importance of aligning business and IT drivers for a holistic architectural approach to ensuring strong data quality.  Continue Reading

• Information Builders exec talks data management ethics

  In this Q&A, James Cotton, director of the Data Management Centre of Excellence at Information Builders, offers advice on how organizations can carry out ethical data management.  Continue Reading

• Key components of an effective data virtualization architecture

  Experts break down which elements -- both technical and nontechnical -- are most crucial to successfully deploying and managing a data virtualization architecture.  Continue Reading

• Advice on enterprise data cleansing from an SAP VP

  SAP's Kristin McMahon details data cleansing best practices and explains why a good data cleanse needs continual communication, collaboration and oversight.  Continue Reading

• USAA adds data engineering skills to speed data science work

  When the United Services Automobile Association's data science team wasn't getting data in the right format, the team lead realized the USAA needed more data engineers.  Continue Reading

• How to navigate the challenges of the data modeling process

  Data modeling and curation can help businesses more efficiently use data they've collected. There are challenges, however -- beginning with ensuring data quality.  Continue Reading

• 8 tips to improve the data curation process

  A data curation and modeling strategy can ensure accuracy and enhance governance. Experts offer eight best practices for curating data. First, start at the source.  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

• Data integrity protection spurs greater security spending

  As hacking, ransomware and malware attacks mount, companies place big data protection and integrity among the primary reasons for increased spending on security software.  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

• DMBOK2 eyes evolving data management best practices, challenges

  In a Q&A, DAMA president Sue Geuens talks about the second edition of the group's DMBOK reference book and how data management trends and processes have changed since the first version.  Continue Reading

• Data monetization takes three routes to turn data into dollars

  Data monetization is not monolithic. Instead, it takes several forms, according to MIT researcher Barbara Wixom. Each approach has its own unique traits.  Continue Reading

• Data lake management, governance a hands-on job for big data teams

  Deploying big data systems is just the first step for IT and data management teams. The next big challenge is setting up systems and processes for governing data lakes.  Continue Reading

• Big data queries eyed to head off Hadoop performance problems

  Processing in big data systems can slow to a crawl if queries are not properly tuned or workloads not well balanced -- issues that call for careful monitoring of clusters.  Continue Reading

• Hadoop data governance takes hold in companies as data gets 'bigger'

  LinkedIn, Cleveland Clinic and fitness company Beachbody are examples of organizations that have increased their data governance efforts in connection with big data applications.  Continue Reading

• Q&A: Big data leads to bad insights without a data governance plan

  Big data holds the potential to provide invaluable insights for business growth, but only if data governance is part of the plan.  Continue Reading

• Inside the Informatica Master Data Management portfolio

  Informatica Master Data Management is aimed at helping sales, marketing and customer service teams ensure they're working from the most relevant and accurate data available.  Continue Reading

• Examining the top data governance tools on the market

  Expert John Ladley examines the leading data governance software products, comparing and contrasting their features to help you determine which tool will best meet your needs.  Continue Reading

• How to narrow down your choices for buying a data governance tool

  Evaluating and selecting a data governance tool depends on not only features and functionality, but also how you will use the tool to add value to your organization.  Continue Reading

• How to know if your company is ready for data governance tools

  Even if you can identify with the use cases presented here, it's important your organization is well-prepared to deploy the software it buys.  Continue Reading

• How data governance software helps ensure the integrity of your data

  While a data governance initiative comprises people, processes and technology, data governance software supplements and automates the processes the organization implements.  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

• CDO jobs on the rise to help wring more business value out of data

  Chief data officers are becoming more prevalent in companies, and more necessary, consultant John Ladley said in a webinar -- so much so that he thinks 2015 could be 'the year of the CDO.'  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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• Data quality issues management

  Identifying data quality issues is only the first step in solving them. In this chapter, Jack Olson explains the need for a data quality assurance management system -- one that asesses the impact and causes of poor data quality.  Continue Reading

• Data quality assurance

  This chapter outlines the basic elements of a data quality assurance program. It focuses on data accuracy, a single dimension of data and information quality.  Continue Reading