Top Challenges of Using Real-Time Data
Given the unique challenges of working with real-time data, organizations need to consider which tools will help them deploy and manage AI and ML models in the …
Topic: Big Data
Big Data technologies and use cases for real-time analytics. Big Data technologies, market insights, and use cases for real-time analytics.
Are Data Lakehouses the Panacea We’ve Been Waiting For, Or Is There Something Better?
While data lakehouses solve some issues, they are not a universal remedy. They really are the next generation of data lakes, incorporating some features and …
Using DataOps For Hybrid, Real-Time Data Management
DataOps can help reduce time spent on busy work, allowing everyone from business leadership to entry-level data analysts to become more organized and …
To Batch or To Stream–That Is the Question of the Day
Claypot AI founder, Chip Huyen, designs machine-learning systems that combine streaming data and batch processing to accommodate multiple data
Why Error Handling Needs to Be Part of Data Integration
Error handling is crucial for successful data integration, but error handling isn’t easy, which is why it is often overlooked.
Maximizing the Value of Your Data Lake
Organizations are adopting modern data management approaches, such as semantic-based knowledge graphs, to connect data across the enterprise and accelerate the …
Data Engineers Spend Two Days Per Week Fixing Bad Data
Data engineers spend 40% of their workweek dealing with incidents relating to poor data quality, which may cost an organization 20% of its
The 4th Shift in the Evolution of Finding Insights from Data
Real-time analytic databases that combine CRUD with streams for high concurrency and sub-second response times across billions of data points are needed for …
Why SQL Will Remain the Data Scientist’s Best Friend
A dizzying range of tools and services has grown out of the need to speed up and scale data analytics. However, one skill that has often been overlooked is …
Data Management in the Era of Data Intensity
To succeed in the digital services economy – and the era of data-intensive applications – you need to leverage fresh data to deliver engaging real-time …