Forwarded from Hadi
Word of the day....
Agile business intelligence (BI)
Agile BI is an approach to business intelligence (BI) that incorporates Agile software development methodologies to accelerate and improve the outcomes of BI initiatives.
When an organization embraces Agile BI, it generally embeds Agile software developers in the organization's business intelligence team. As with all Agile initiatives, BI projects are broken down into a series of smaller projects that are planned for, developed, tested and rolled out on a continuous basis. This iterative development approach facilitates continuous improvement and helps an organization adapt more quickly to changing market conditions and organizational goals. Each iteration of an Agile BI project is planned and reviewed by both the software development team and the business owners who have requested work. This close collaboration between business and IT results in better communication, clearly-defined goals and end results that more accurately meet expectations.
Agile business intelligence (BI)
Agile BI is an approach to business intelligence (BI) that incorporates Agile software development methodologies to accelerate and improve the outcomes of BI initiatives.
When an organization embraces Agile BI, it generally embeds Agile software developers in the organization's business intelligence team. As with all Agile initiatives, BI projects are broken down into a series of smaller projects that are planned for, developed, tested and rolled out on a continuous basis. This iterative development approach facilitates continuous improvement and helps an organization adapt more quickly to changing market conditions and organizational goals. Each iteration of an Agile BI project is planned and reviewed by both the software development team and the business owners who have requested work. This close collaboration between business and IT results in better communication, clearly-defined goals and end results that more accurately meet expectations.
Forwarded from Hadi
although Vagrant and Docker appear to be competitors, some enterprising admins have found a way to use them to actually complement each other. In such a scenario, Vagrant is used to create a base VM, then when you need to create different configs that all utilize this base VM, use Docker to provision and create different lightweight versions.
Forwarded from Hadi
Word of the day....
machine-generated data
Machine-generated data (MGD) is information that is produced by mechanical or digital devices. The term is often used to describe the data that is generated by an organization's industrial control systems as well as mechanical devices that are designed to carry out a single function.
In the past, operational technology (OT) systems and single-purpose machines typically ran in isolated environments. The software that supported them was usually proprietary and data was stored in log files. It was difficult to normalize the data that was produced and integrate it with the organization's information technology (IT) systems. An additional problem was that most information technology systems were not designed to handle the sheer volume of data that operational technology produces.
As the Internet of Things (IoT) has continued to evolve, however, access to machine-generated data and integration between OT and IT have become more important. In response, vendors have begun to insert IT capabilities into operational technology, allowing devices that generate machine data to talk with each other and connect with the IT infrastructure that captures, transfers, stores and analyzes the rest of the organization's data.
machine-generated data
Machine-generated data (MGD) is information that is produced by mechanical or digital devices. The term is often used to describe the data that is generated by an organization's industrial control systems as well as mechanical devices that are designed to carry out a single function.
In the past, operational technology (OT) systems and single-purpose machines typically ran in isolated environments. The software that supported them was usually proprietary and data was stored in log files. It was difficult to normalize the data that was produced and integrate it with the organization's information technology (IT) systems. An additional problem was that most information technology systems were not designed to handle the sheer volume of data that operational technology produces.
As the Internet of Things (IoT) has continued to evolve, however, access to machine-generated data and integration between OT and IT have become more important. In response, vendors have begun to insert IT capabilities into operational technology, allowing devices that generate machine data to talk with each other and connect with the IT infrastructure that captures, transfers, stores and analyzes the rest of the organization's data.