Analytics Architecture

Analytics architecture refers to the systems, protocols, and technology used to collect, store, and analyze data. The concept is an umbrella term for a variety of technical layers that allow organizations to more effectively collect, organize, and parse the multiple data streams they utilize. When building analytics architecture, organizations need to consider both the hardware – how data will be physically stored—as well as the software that will be used to manage and process it.

How can I use Analytics Architecture?

No matter what kind of organization you have, data analytics is becoming a central part of business operations. The fast-rising amount of data your multiple touch points collect means that using a simple spreadsheet is quickly becoming unfeasible. Analytics architecture helps you not just store your data but plan the optimal flow for data from capture to analysis. Understanding these steps can give you a better idea of your hardware and logistics needs and clue you in on the best tools to use.

What is big data architecture?

A big data architecture is designed to handle the ingestion, processing, and analysis of data that is too large or complex for traditional database systems. Big data solutions typically involve one or more of the following types of workload: Batch processing of big data sources at rest.

What is Enterprise Analytics platform?

Enterprise Analytics Platform is a platform on which companies do their analytical research and comprise the data. Knowledge Available to all Employees – The convenience of data is not only available to analysts, instead employees of the whole organization can use the data for the welfare of the firm.

Why does software architecture matter?

The main function of traditional architecture is not to make pretty or unique buildings but buildings that function well in their intended role. See the full article for more details.