Data definitions are about a business creating a common vocabulary in a common language. They’re about how the organization thinks about itself. Take product data: The business needs to know what products it sells, how they can be categorized, what needs to be understood about that, who has financial responsibility for them, and why it […]
Training Artificial Intelligence Systems
Computer vision systems are driving some incredible developments. Convolutional neural network (CNN) algorithms are most commonly applied to analyzing visual imagery. That involves the “classification, detection, [and] segmentation of entities in the 2D space and analyzing temporal information in the 3D space, such as Action/Video,” says PR Krishan, VP and Global Head, Enterprise Intelligence Automation, […]
Semantic Web and Semantic Technology Trends in 2020
One way or another, it’s all about graphs. And machine learning. And AI. And what their connections to each other are. Welcome to the world of semantic technology in 2020. The year ahead largely picks up the pace on what industry experts predicted would happen in 2019. Graph technologies have finally become mainstream, says Andreas […]
Deep Neural Networks, Big Data, AI, and the Road to Autonomous Systems
Autonomous driving – green light, red light, or yellow? Earlier this year Tesla CEO Elon Musk said the future is now. By the middle of 2020, he said at an event for investors, Tesla’s autonomous system will have improved to the point where drivers will not have to pay attention to the road. He revealed […]
Enterprise Architects are More Than Just Modelers
New opportunities are emerging for enterprise architects (EAs). EAs will work in conjunction with technology innovation leaders to help their organizations select, create, and implement the right business- and technology-based platforms to support their business ecosystems. “By 2021, 40 percent of organizations will use enterprise architecture to help ideate new business innovations made possible by […]
Smart AI Means Smart Data Prep
Every company wants to put artificial intelligence (AI) to work. Its potential seems limitless. Big business benefits at the snap of a finger. But then reality hits: the value that AI can deliver isn’t easy. Even IBM, a pioneer in the early age of AI (or AI’s rebirth if you want to trace it back […]
Data Orchestration Brings Your Data Closer and Makes Access Faster
Data orchestration means trying to bring order and speed to a complex Big Data ecosystem, a conglomeration of storage systems like Amazon S3, Apache HDFS, or OpenStack Swift and computation frameworks and applications such as Apache Spark and Hadoop MapReduce. The data stack is fragmented and performance-challenged by a proliferation of data silos. The technology […]
It’s Time to Productionize Data Science
To make Data Science part of business value creation, business users have to be part of the Data Science lifecycle. They need to be able to go back to Data Science teams and provide feedback so that the Data Science process reflects their requirements — and quickly. Models may need to be updated or functionalities […]
Modernize Data Practices with DataOps
Back in 2015, a new term was introduced to the market: DataOps. “DataOps,” wrote Andy Palmer: “Is a Data Management method that emphasizes communication, collaboration, integration, automation and measurement of cooperation between data engineers, data scientists and other data professionals.” The practice was born out of the democratization of analytics and the implementation of built-for-purpose […]
Data Virtualization for a Hybrid World
Many organizations see the hybrid cloud and multi-cloud models as critical to their present business requirements, and to their future ones too. Organizations are paying more attention to the use of containers to help with simple and automated portability and scaling that can play an important role in accelerating cloud projects and deliverables; to cloud […]