Logi DataHub v2.2 Overview
DataHub is a web-based application that retrieves and caches data destined for analysis, using a high-performance, self-tuning data repository. It off-loads data from transactional systems, which are not optimized for analysis, and provides access to data sources not generally available in Logi Info.
The Logi DataHub v2.2 Help System provides you with everything you need to know to fully utilize all of the features of DataHub v2.2. This topic provides a brief explanation of DataHub v2.2, and you can access other relevant information using the links we have listed in this topic, or by looking at the Table of Contents, or by using Search.
For information about hardware and software requirements for DataHub v2.2, see: System Requirements.
Logi DataHub is a data retrieval and preparation tool for use with analytic applications that solves many of these problems. It connects to multiple data sources, retrieves and caches data for improved performance, and prepares data with smart profiling, joins, and data enrichment, so you can deliver efficient reporting and analysis without impacting your transactional systems and application data sources.
DataHub can access data sources not supported within Logi Info, and can access data located in multiple locations. It can blend data from the cloud, databases, applications, and files and supports large datasets (250M+ rows).
Large dataset performance is accelerated with a self-tuning, easy-to-maintain columnar data store.
DataHub allows you to create and manage "dataviews", which are made available to Logi applications, including our self-service analytics offerings.
Here's a quick overview of the typical steps, left-to-right, involved in using Logi DataHub:
DataHub's easy-to-use interface and intuitive operations do not require a DBA or data scientist in order to create meaningful results. Once created, dataviews are then available to a wider audience of Logi application users, who benefit immediately without having to know the data in depth.
DataHub can connect to and retrieve data from a variety of data sources, some of which are illustrated below:
Data can be blended together to produce unique relationships and enriched through Smart Profiling to make working with it easier.
Data retrieval can be scheduled, allowing you to refresh cached data as necessary, without impacting data sources during peak usage periods.