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Data quality techniques and best practices
What is data governance and why does it matter?
Data governance (DG) is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage. 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
data stewardship
Data stewardship is the management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner. Continue Reading
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How data lineage tools boost data governance policies
Organizations can bolster data governance efforts by tracking the lineage of data in their systems. Get advice on how to do so and key features in data lineage tools. Continue Reading
master data management (MDM)
Master data management (MDM) is a process that creates a uniform set of data on customers, products, suppliers and other business entities from different IT systems. Continue Reading
data quality
Data quality is a measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and whether it's up to date.Continue Reading
What is data management and why is it important?
Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization, as explained in this in-depth look at the process.Continue Reading
data
In computing, data is information that has been translated into a form that is efficient for movement or processing.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
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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
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
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
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
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
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
data scrubbing (data cleansing)
Data scrubbing, also called data cleansing, is the process of cleaning up data in a database that is incorrect, incomplete, or duplicated.Continue Reading
raw data (source data or atomic data)
Raw data (sometimes called source data or atomic data) is data that has not been processed for meaningful use.Continue Reading
Data quality and governance management quiz
Test your knowledge of data quality and data governance management concepts, trends and vendor news in this short quiz. When you are done, check your answers and read detailed explanations for each response.Continue Reading
synthetic backup
Synthetic backup is the process of generating a file from a complete copy of a file created at some past time and one or more incremental copies created at later times... (Continued)Continue Reading
Data quality guide
Here you'll find articles, white papers, advice and resources to help you better manage and leverage your company's data. From an introduction to data quality-related terms to understanding the innovations in tools and technology, this is your best ...Continue Reading
dirty data
In a data warehouse, dirty data is a database record that contains errors.Continue Reading
fixed data (permanent data, reference data, archival data, or fixed-content data)
Fixed data (sometimes referred to as permanent data) is data that is not, under normal circumstances, subject to change. Any type of historical record is fixed data. For example, meteorological details for a given location on a specific day in the ...Continue Reading
cooked data
Cooked data is raw data after it has been processed - that is, extracted, organized, and perhaps analyzed and presented - for further use.Continue Reading