I recently wrote about the importance of data pipelines and the role they play in transporting data between the stages of data processing and analytics. Healthy data pipelines are necessary to ensure data is integrated and processed in the sequence required to generate business intelligence. The concept of the data pipeline is nothing new of course, but it is becoming increasingly important as organizations adapt data management processes to be more data driven.
Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, Digital transformation, data lakes, AI and Machine Learning, data operations, Digital Business, data platforms, Analytics & Data, Streaming Data & Events
Data mesh is the latest trend to grip the data and analytics sector. The term has been rapidly adopted by numerous vendors — as well as a growing number of organizations —as a means of embracing distributed data processing. Understanding and adopting data mesh remains a challenge, however. Data mesh is not a product that can be acquired, or even a technical architecture that can be built. It is an organizational and cultural approach to data ownership, access and governance. Adopting data mesh requires cultural and organizational change. Data mesh promises multiple benefits to organizations that embrace this change, but doing so may be far from easy.
Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, Digital transformation, data lakes, data operations, Digital Business, data platforms, Analytics & Data, Streaming Data & Events
With the announcement of Ventana Research’s 2022 Market Agenda, our expertise in Digital Business continues to advance the market need for effective investments into technology, and I will outline here the key areas of focus to provide insights to organizations that can increase their organizational resilience and workforce readiness. We are proud to provide expertise on ensuring technological effectiveness through our market research and experience in providing guidance on trends and best practices.
Topics: Performance Management, Business Continuity, Governance, Risk & Compliance (GRC), Digital transformation, Digital Business, Digital Security, Digital Communications, Sustainability Management, Work Management, Experience Management
As with many IT innovations, augmented reality (AR), extended reality (XR) and the related topic of spatial computing had been discussed to death long before they became a practical reality. As a user interface, AR is already well understood in terms of its ability to open vast new vistas in entertainment as well as making physical tasks, such as machinery maintenance and warehouse pick-and-pack, far more efficient. In the case of spatial computing, by using glasses to superimpose workflow directions, instructional videos, messages and the like onto the three-dimensional world, individuals can complete tasks faster with little formal training and make fewer errors in the process. So, long before these AR devices, tools and their related UI techniques are adapted to create a new era of immersive business computing, here are some thoughts on this idea.
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 global scalability) and the NoSQL providers (in terms of the relational model and transactional consistency). Having differentiated functionality is the bare minimum a new database vendor needs to make itself known in a such a crowded market, however.