The Data is In: Data Science is Delivering
Nearly four in five (79%) managers agreed that data science, machine learning, and AI are critical to the overall future growth of their
Topic: Analytics
How real-time data is used in business analytics, including predictive, descriptive, and prescriptive uses. Edge analytics is also explored.
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 …
Real-time Analytics News for Week Ending September 17
In this week's real-time analytics news: A paper by Arm, Intel, and NVIDIA describes a specification to provide a common interchangeable format for both …
Transforming the Private Equity Value Landscape with AI and Cloud Technology
Private equity firms whose management teams focus on data and analytics – through building a data strategy, investing in cloud and analytics capabilities, …
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 …
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 …
Life Sciences Increases its Doses of the Metaverse
The constellation of metaverse technologies includes extended reality, blockchain, artificial intelligence, digital twins, non-fungible tokens, and smart …
Real-time Analytics News for Week Ending September 10
In this week's real-time analytics news: Canonical announced Charmed Kubeflow 1.6, an end-to-end MLOps platform with optimized complex model training …
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 …