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Monday 16 December 2019
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Tech Terms You Should Know!

Tech Terms You Should Know!

Technology Terms You Should Know! Tech Target seems surprise even us.. sometimes!

Some of these are probably terms you have used. But, as Technology evolves so do the terms that are needed to describe them and share them with the world.

spreadmart

A spreadmart (spreadsheet data mart) is a situation in which a company’s employees has inconsistent views of corporate data because each department relies on the data from their own spreadsheets.

Because spreadsheets are easy to work with, many businesses rely on them to take the place of a data mart or data warehouse. Instead of providing a consistent view of the entire company’s data, however, spreadsheets have unique views of limited amounts of data.

It is up to the spreadsheet creator to decide what metrics are important, what data needs to be collected, how the data is formatted and what level of granularity is required. In such a scenario, the spreadsheets become isolated data silos.

cloud orchestrator

A cloud orchestrator is programming that manages the interconnections and interactions among cloud-based and on-premises business units.

To orchestrate something is to arrange various components so they achieve a desired result. In an IT context, this involves combining tasks into workflows so the provisioning and management of various IT components and their associated resources can be automated. This endeavor is more complex in a cloud environment because it involves interconnecting processes running across heterogeneous systems in multiple locations.

Cloud orchestration products can simplify the intercomponent communication and connections to users and other apps and ensure that links are correctly configured and maintained. Such products usually include a Web-based portal so that orchestration can be managed through a single pane of glass.

When evaluating cloud orchestration products, it is recommended that administrators first map the workflows of the applications involved. This step will help the administrator visualize how complicated the internal workflow for the application is and how often information flows outside the set of app components. This, in turn, can help the administrator decide which type of orchestration product will help automate workflow best and meet business requirements in the most cost-effective manner.

 process intelligence

Process intelligence is data that has been systematically collected to analyze the individual steps within a business process or operational workflow.

Process intelligence provides an organization with accurate information about what work items exist, who does the work, how long it takes work to be completed, what the average wait time is and which steps are inefficient. The goal of process intelligence is to help an organization identify bottlenecks and improve operational efficiency.

Software can help an organization improve process management by integrating data from disparate sources and analyzing processes on a historic or real-time basis. Process intelligence software is especially useful for improving nonlinear processes that have a lot of dependencies.

microservices

Microservices is an approach to application development in which a large application is built as a suite of modular services. Each module supports a specific business goal and uses a simple, well-defined interface to communicate with other modules.

Microservices came about to help solve the frustrations developers were having with large applications that require change cycles to be tied together. In a monolithic service-oriented architecture (SOA) deployment, for example, each small change meant that the entire monolith needed to be rebuilt and this, in turn, meant that re-builds weren’t happening as rapidly as they should have. A more granular approach to defining modules allows changes to be made independently so rebuilt modules can be deployed without impacting other parts of the application.

In a microservices architecture, each microservice runs a unique process and usually manages its own database. This not only provides development teams with a more decentralized approach to building software, it also allows each service to be deployed and managed independently. Software developer and author Martin Fowler is credited with promoting the idea of breaking down services in a service-oriented architecture into microservices. Some developers maintain that microservices is simply a more granular approach to service-oriented architecture. Others believe that microservices is a more platform-agnostic approach to application development and therefore, should have a unique name.

advanced analytics

Advanced analytics is a broad category of inquiry that is used to predict future outcomes and help drive changes and improvements in business practices.

While the traditional analytical tools that comprise basic business intelligence (BI) examine historical data, tools for advanced analytics focus on forecasting future events and behaviors. In customer relationship management, for example, advanced analytics software can be used to predict which shoppers are most likely to be repeat customers so sales can identify cross-sell and up-sell opportunities.

Advanced analytic software can also allow businesses to conduct what-if analyses and predict the effects of potential changes in marketing campaigns, inventory management or other business concerns. To help an analytics initiative succeed, senior executives need to drive an internal emphasis on optimizing business performance through quantitative measurements and be prepared to fund such initiatives.

Although complex analyses usually required teams of experienced statisticians, new software tools and data visualization technologies have made predictive modeling more accessible to the average information technology (IT) department and the business users it supports. Some vendors now support the use of the R programming language in their software or offer completely R-based packages. This means that instead of having to hire staff to write complex R code, users can create sophisticated data models by using a front-end graphical user interface (GUI) and pointing and clicking.




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