Kemi Nelson is a finance executive in Dallas, TX, with an impressive 15-year career in corporate leadership. She loves investing in people and has driven growth at every company she's worked with.
The Role of Data Governance in Ensuring Data Quality Throughout the Life Cycle
Data governance (DG) is everything we do to ensure data is secure, private, accurate, available, and usable. It is the process that modern organizations – governments, companies, schools – use to manage the availability, usability, integrity, and security of their data and data enterprise systems. This is typically based on internal data standards and policies controlling data usage and external compliance mandates. Effective data governance must ensure data is consistent and correct. But more importantly, it is vital to ensure that data is available to use for business value without being misused.
Kemi Nelson Discusses the Potential of Synthetic Data in Data Science
Artificial Intelligence (AI) and Machine Learning (ML) models have become increasingly popular in both the business and private sectors. They allow individuals and companies to generate images, text, audio, and more for little to no cost and cut down on the number of labor hours required to complete crucial workplace tasks. They can also be valuable assistants for creative and analytical minds alike, providing faster ways to complete menial or repetitive tasks. However, before AI/ML models can be utilized in these capacities, they must first be trained. Synthetic data provides a possible solution to the vast amount of information and time that must be dedicated to creating a functional AI model.
Building a Successful Career in Data Analytics
Over the last couple of years, our world has become more and more data-driven, thanks to tech advancements and innovations. Because of this, the need for professionals who can work with data and turn it into actionable insights is also on the rise. Data and analytics constantly evolve and transform various industries, creating a wide range of career opportunities for professionals with the required skills and knowledge.
Why Data Science Education is Essential
In the modern world, data is everywhere. We generate data whenever we use a smartphone, make a purchase, or even browse the internet. As a result, data science has emerged as a critical area of study for anyone interested in understanding and working with this flood of information.
What Is Data Life Cycle Management, And Why Does It Matter?
Data life cycle management helps companies maximize value and minimize risk. A DLM program should target specific organizational needs and integrate with existing processes. Learn why data life cycle management is essential to ensure confidentiality, accuracy, and relevance.