With the field of Data Management constantly evolving and becoming increasingly competitive, getting certified as a data professional helps you stand out from the crowd. The certification process requires applicants to demonstrate their knowledge and understanding of various areas of Data Management, such as database design, data modeling, data governance, programming, analytics, and data visualization. Many […]
Using Graph Technology in the Evolution of AI
Graph technology is being used to promote the evolution of artificial intelligence. Graph databases show how data is interlinked, expressing relationships within the data that cannot be communicated using a tabular SQL system. They work especially well when complex patterns must be identified quickly. Graphs are an excellent tool for inferring relationships and enhancing artificial […]
Data Governance 101
Data Governance (DG), a formalized practice that connects different components – such as roles, processes, communications, metrics, and tools – increases data’s value. By harmonizing these fundamental elements, governance ensures that the right data flows efficiently to the right resources at the right time. In this Data Governance 101 article, we will look at the definition […]
Getting Executive Buy-In for Data Analytics
In a world driven by data, business analytics and data analytics can work together to maximize efficiencies, uncover actionable insights, and help businesses drive value. Data analytics is an iterative study of data in an organization, focusing on applying statistical and other techniques to uncover insights that may help to promote innovation and the financial […]
Improving Data Quality: 9 Essential Steps
For the data-driven, high-volume businesses of today, improving Data Quality is essential to ensure trustworthy data and operational efficiency. But the process doesn’t have to be daunting, said Ryan Doupe, VP and chief data officer at American Fidelity Assurance. In a presentation at DATAVERSITY’s Enterprise Data Governance Online event, Doupe laid out a nine-step program for better […]
Database Management Trends in 2023
The recent trends in Database Management reflect how organizations are improving their storage and how they process data. Organizations can drive their business growth by improving their Database Management platform. Database Management typically involves the use of software to support automated data services. Database Management is not the same as Data Management, nor is it Data […]
What Makes a Great Data Scientist in 2023?
A great data scientist combines expert knowledge of various interrelated academic disciplines to help global enterprises make agile decisions for improved business performance. Data scientists use statistics, mathematics, data mining, and computer science to analyze data sets for observable trends and patterns. They are also experts in data collection and storage methods. The Bureau of Labor Statistics had predicted […]
The Importance of a Modern Data Architecture
The legacy architecture of some organizations’ data systems may need a serious upgrade to stay competitive. For example, the old architecture of a business may provide a clumsy fit when accessing cloud services and take longer to transfer data and perform tasks within the cloud. This results in higher cloud costs. Additionally, upgrading to a […]
Data Management Trends in 2023
In a world driven by data, companies that are successful at extracting actionable insights through Data Management will be able to innovate more quickly, develop better strategies, and govern change more efficiently. Data analytics, which has been completely overtaken by technologies like artificial intelligence (AI) and machine learning (ML), has emerged as a critical game […]
7 Top Data Quality Issues (and How to Fix Them)
Having Data Quality issues is a common – and costly – problem. According to Gartner, poor-quality data costs organizations an average of $12.9 million annually. Data Quality uses factors such as accuracy, consistency, and completeness in determining the value of the data. High-quality data can be trusted, while low-quality data is inaccurate, inconsistent, or incomplete. In […]