liteSpace: Analyze data without a Data Warehouse?

At Litebi, we have worked for a long time in the field of Business Intelligence. We have built many systems for many industries and in general, the central concept of the project was the Data Warehouse. The Data Warehouse is a central concept from which (together with the executive information systems and a few more acronyms) the whole concept of Business Intelligence evolved from more than a decade ago. The idea is essentially to construct a large "warehouse" that collects business information from heterogeneous data source, takes care of integrity, quality, and historic data, and makes it available for analysis. Here you have some further reading if you are interested. The great theorists of this (Ralph Kimball and Bill Inmon) threw books to each other heads thourgh the years with the different approaches to build the DW. But they always seemed to agree in something, the data warehouse is something big, costly, complex and certainly requires someone who has read the books they write (like the excellent The Data Warehouse Toolkit) or least attended one of his lectures. The result of this is that many people run away scared when they hear about a concept associated with long projects and big investments. And sometimes, that gigantic approach, it's the right thing to do. If you are a large corporation, i might make sense for you to address all analytical needs at once. However, at Litebi we think that in 99% of the scenarios this is simply not worth it. Rarely the analytical needs of a company (of any size) need the building of a complete Data Warehouse from the beginning. In many cases it is smarter to go step by step toward the construction of the analytical system. Or at least save the deployment of it (including the purchase of equipment, purchase a database, etc ...) through the SaaS model. That is our goal. At the core of Litebi lays liteSpace. We like to talk about it as an "analytic space" or a " Managed Data Warehouse". The idea is simple, being able to offer the advantages of a classic Data Warehouse (responding to the analytical needs of the customer, integrating information from all sources, cover the entire organization, etc ...) but without the complexity, risk and cost that such projects usually mean. Partly thanks to the SaaS model that eliminates the need to manage the Data Warehouse 'in-house' (and hardware, and deployment...), and partly because we have a technology capable of allowing anyone to define "what" want they want to analyze through web interfaces (dimensional models) and let Litebi do all the hard work between racks (model building, optimization of the same design, metadata, etc. ..). This allows our customers to have a powerful analytic system deployed in a few weeks and with minimal risk and investment concerns: All the benefits of Business Intelligence, plus all the benefits of the SaaS model. Needless to say that we are happy to perform demonstrations to anyone interested :) Greetings. Tweet