Executive Summary :

The client has long been a classic American icon, its distinguished reputation embodied in its renowned moniker and roaring lion trademark. Since its founding in 1924, the Company has prided itself on creating and shaping cinematic history, delighted audiences worldwide with entertainment of unparalleled distinction. Throughout its existence, they enjoyed memorable successes and overcome difficult obstacles, forging ahead with renewed vigor. Along the way, the Company has evolved and changed to meet the specific demands of modern audiences and maintained its foothold in rapidly emerging technologies, setting the stage for success in a new century of entertainment. Now, 80 years after its birth, it remains a major force in the entertainment industry, with a proud heritage, an enduring legacy, and a promising future.

The reports that had to be developed were complex reports. They recently migrated to Teradata from SAP BW and they have a highly normalized database. They wanted a very fast response time for their reports and this becomes a problem because of the way their database is structured.

The client needed someone with extensive experience and expertise in ReportNet. Nrit has a number of world-class consultants who specialize in this particular area and so when Nrit was asked to do this job, there were no surprises.

We needed to count the number of stores with POS. This presented a problem because we needed to get only the distinct stores. For achieving this, we resorted to Tabular SQL because you cannot have the distinct clause in a calculation in a report. We were making a report that was essentially a combination of three different reports. So we created a Tabular SQL and a Tabular model and did a union of the Tabular Set and the Tabular Model. We had another Tabular SQL at the top level and we did a union of the Tabular SQL with the result of the above union to achieve the desired results. Now the requirement for doing a union is that the
number of columns must be the same and the columns must be of the same data type. We achieved this by putting dummy columns and putting their value to 0 and rolling up the values.