Breaking Down Data Silos with Automated Integration
Automated integration takes much of the burden off of the technical staff by handling the numerous manual tasks required to make siloed data available to …
Topic: Data management
apply(conf) puts everything on the table to help data and ML teams succeed
Bringing ML models into production is hard. Fortunately, community initiatives such as apply(conf) are helping.
Learning to Trust in the Black Box with Observability
If your organization spends more time scratching its collective head about data quality or operational issues than it does asking unique and interesting …
Join the Open Banking and Open Finance Revolution
Open Banking is now expanding towards the broader revolution of Open Finance, which goes beyond any regulatory framework and is designed to share more precise …
The Role of Knowledge Graphs in Cloud Data Integration
Graph databases and knowledge graphs have a number of built-in advantages when it comes to overcoming the challenges of data
Time Consumed by Data Prep: Is This a Bad Thing?
Data professionals are spending too much time on data prep, but the quality assurance that provides ensures projects are working with clean data
Major Integration Challenges of Today and How to Overcome Them
We discuss integration challenges and how the use of AI, no code and low code techniques, and automation can help companies overcome
Overcome These Four Bad Data Quality Categories
It is essential that organizations assess the need for improved data quality and make the necessary changes to save not only their reputation but the bottom …
Change Data Capture and the Many Roles it Can Play
In modern microservices-driven architectures, CDC has gained new importance by providing a bridge to connect traditional databases with cloud-native, …
Avoiding the Skepticism-driven Culture of Data Downtime
Data downtime creates a downward spiral of company culture, stopping companies from achieving the degree of data-driven decision-making that they aspire