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Data quality techniques and best practices

• 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

• What steps are key to building a data catalog?

  An enterprise data catalog can help an organization effectively manage metadata and explore data sources. Expert Anne Marie Smith offers seven tips for creating a data catalog. 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

• How data lineage tools boost data governance policies

  Enterprises can bolster data governance efforts by tracking how and when changes are made to data. Expert David Loshin offers advice on what to look for with data lineage products. Continue Reading

• Definitions to Get Started

  • data quality
  • data governance (DG)
  • data
  • data scrubbing (data cleansing)

  • raw data (source data or atomic data)
  • synthetic backup
  • fixed data (permanent data, reference data, archival data, or fixed-content data)
  • dirty data

  View All Definitions

• 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

• 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

• 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

• data quality

  Data quality is a perception or an assessment of data's fitness to serve its purpose in a given context.Continue Reading

• Good data quality for analytics becomes an IT imperative

  High-quality data is a must for analytics applications. That's driving more demand for data quality tools, but quality initiatives are still maturing in many companies.Continue Reading

• data governance (DG)

  Data governance (DG) is the overall management of the availability, usability, integrity and security of data used in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures and a plan to ...Continue Reading

• data

  In computing, data is information that has been translated into a form that is efficient for movement or processing.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

• 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

• 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