Once And For All, We Answer The Question Of Why Master Data Management Is Important For Companies — Here Are 7 Essential Reasons!
Data sharing has become more and more popular, even in small and big organisation. A good master data management strategy allows you to share data among different departments and staff, facilitating communication within your company. A fundamental thing for sharing...
Data Governance is a term that picked up its importance in recent years when enterprises started realizing the importance and impact of Master Data, Data is all around us and it is not an exaggeration to tell that Data governance is part of the environment. I was exploring the standard framework for data governance over […]
List of 20 data management best practices, strategies, and guidelines that guarantee improved business decision-making. What is data management? Best practices for data governance, data stewardship, data integration, data quality, and enterprise master data management strategies.
Many life sciences companies find themselves in an unfortunate situation when it comes to their systems for managing their universal data, which is the information about customers and products that’s used by multiple functions in the organization. Given the cost and complexity of developing an enterprise-wide solution, they’ve allowed spot…
Setting up data quality management seems to be a blurry task? We show what a well-organized process looks like and enumerate the required tools. These best practices will help you improve the quality of your data and, ultimately, your decisions.
G3sm data governance methodology supports organizations in planning and implementation for successful data governance and data stewardship programs.
Master Data Management (MDM) is the technology, tools and processes that coordinate your master data across the enterprise.
Fresh Gravity helps organizations solve their toughest enterprise data management and data governance challenges
Data is not given prominence in system design, architecture… The proof of this is demonstrated by the problems in your legacy systems #datamanagement #BI #dataquality #analytics #datagovernan…
Setting up data quality management seems to be a blurry task? We show what a well-organized process looks like and enumerate the required tools. These best practices will help you improve the quality of your data and, ultimately, your decisions.
Dave Wells, senior analyst at Eckerson Group, details the role of the data catalog in modern data architecture.
Different types of DBMS include relational, object-oriented, hierarchical, network, NoSQL, column-family, document-oriented, graph, time-series and in-memory.
What is a data lake, what are the benefits of data lakes, how do they help in big data analytics and how are they evolving.
The Stanford maturity model considers six components subidivded by three dimensions, all across 5 maturity levels. Here's how you can use it.
Build a solid data governance strategy in your company by implementing a successful data governance framework.
The 6 types of impact data you need to provide evidence for funders and internal stakeholders.
Data Governance Framework Each vendor has their own opinion about the best framework for Data Governance, here I try to explain in qui...
Proper data classification is necessary to select correct statistical tools
Directors and managers in the non-profit and for-purpose sectors generally like to think of themselves as rational (evidence-based) decision-makers. As in most fields however, decision quality is o…
