Data Cube Is Dead, Long Life To Data Cube In The Age Of Web Data

In a short time, the data warehouse (DW) technology took an important place in the academic and industrial landscapes. This place materialized in the large majority of engineering and management schools that adopted it in their curriculum and in the small, medium-size and large companies that enhanced their decision making capabilities thanks to it. The 1990s saw the advent of conferences such as DaWaK and DOLAP that carried the acronyms DW and OLAP in their titles. Then, all of a sudden, this technology has been upset by the arrival of Big Data. Consequently, those actors have replaced DW and OLAP by Big Data Analytics. We are well placed to assert that this brutal move may have a negative impact on schools, academia, and industry. This technology is not dead, today's context, with the connected world and Web of Data, is more favorable than when building DW merely stemmed from company internal sources. In this invited paper, we attempt to answer the following question: how does DW technology interact with Linked Open Data (LOD)? To answer the question, we provide a complete vision to augment the traditional DW with LOD, to capture and quantify the added value generated through this interaction. This vision covers the main steps of the DW life-cycle. This value is estimated through two different perspectives: (i) a source-oriented vision, by calculating the rate of the DW augmentation in terms of multidimensional concepts and instances, and (ii) a goal-oriented vision where the value is calculated according to the ability of the DW to estimate the performance levels of defined goals that reflect the strategy of a company, using the defined DW of the case study of a leading Algerian company.