I recently described the use cases driving interest in hybrid data processing capabilities that enable analysis of data in an operational data platform without impacting operational application performance or requiring data to be extracted to an external analytic data platform. Hybrid data processing functionality is becoming increasingly attractive to aid the development of intelligent applications infused with personalization and artificial intelligence-driven recommendations. These...
Read More
Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data,
Digital Technology,
AI & Machine Learning,
data platforms,
Analytics & Data
Over a decade ago, I coined the term NewSQL to describe the new breed of horizontally scalable, relational database products. The term was adopted by a variety of vendors that sought to combine the transactional consistency of the relational database model with elastic, cloud-native scalability. Many of the early NewSQL vendors struggled to gain traction, however, and were either acquired or ceased operations before they could make an impact in the crowded operational data platforms market....
Read More
Topics:
Business Continuity,
Cloud Computing,
Data,
Digital Technology,
digital business,
data platforms,
Analytics & Data
The need for data-driven decision-making requires organizations to transform not only the approach to business intelligence and data science but also accelerate the development of new operational applications that support greater business agility, enable cloud- and mobile-based consumption, and deliver more interactive and personalized experiences. To stay competitive, organizations need to prioritize the development of new, data-driven applications. As a result, many have been encouraged to...
Read More
Topics:
Analytics,
Cloud Computing,
AI & Machine Learning,
Analytics & Data
Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness...
Read More
Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data Governance,
Data Integration,
Data,
Digital Technology,
data lakes,
data operations,
AI & Machine Learning,
data platforms
Breaking into the database market as a new vendor is easier said than done given the dominance of the sector by established database and data management giants, as well as the cloud computing providers. We recently described the emergence of a new breed of distributed SQL database providers with products designed to address hybrid and multi-cloud data processing. These databases are architecturally and functionally differentiated from both the traditional relational incumbents (in terms of...
Read More
Topics:
Cloud Computing,
Data,
Digital Technology,
Digital transformation,
digital business,
data platforms,
Analytics & Data
Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As...
Read More
Topics:
Analytics,
Cloud Computing,
Data Governance,
Data Integration,
Data,
Digital Technology,
data lakes,
data operations,
AI & Machine Learning,
data platforms