Whois & Analysis for sevenbillion.co

Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information.

Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.

MLOps is the set of practices at the intersection of Machine Learning, DevOps and Data Engineering.

MLOps or ML Ops is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.

The word is a compound of "machine learning" and the continuous development practice of DevOps in the software field.

Machine learning models are tested and developed in isolated experimental systems.

When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm to production systems.

Similar to DevOps or DataOps approaches, MLOps seeks to increase automation and improve the quality of production models, while also focusing on business and regulatory requirements.

While MLOps started as a set of best practices, it is slowly evolving into an independent approach to ML lifecycle management.

MLOps applies to the entire lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics.

According to Gartner, MLOps is a subset of ModelOps.

MLOps is focused on the operationalization of ML models, while ModelOps covers the operationalization of all types of AI models.

Analytics is the systematic computational analysis of data or statistics.

It is used for the discovery, interpretation, and communication of meaningful patterns in data.

It also entails applying data patterns toward effective decision-making.

It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.

Thomas Edison with phonograph.

Edison was one of the most prolific inventors in history, holding 1,093 U.S. patents in his name.

In the field of management, strategic management involves the formulation and implementation of the major goals and initiatives taken by an organization's managers on behalf of stakeholders, based on consideration of resources and an assessment of the internal and external environments in which the organization operates.

Strategic management provides overall direction to an enterprise and involves specifying the organization's objectives, developing policies and plans to achieve those objectives, and then allocating resources to implement the plans.

Academics and practicing managers have developed numerous models and frameworks to assist in strategic decision-making in the context of complex environments and competitive dynamics.

Strategic management is not static in nature; the models can include a feedback loop to monitor execution and to inform the next round of planning.