Market and customer analyses, simulations and forecasts based on reliable statistics, scenarios oriented to support the most important strategic decisions, data management and selection according to the business, filing and rapid analysis on a limitless amount of information, management of unstructured data and interrelation with structured data, security and rapidity of the systems: these are the resources necessary to be competitive.
Nowadays, possession of data is as important as the software. But data are also considered essential facilities, that is, resources to be shared while an advanced proprietary system is the key for the analysis of information and its use according to the business.
The real digital transformation is therefore not simply the application of technologies, however sophisticated, to the traditional business, but the creation of new business in accordance with the guidelines:
- get to know the customer and personalize the customer experience;
- design tools that transform data and statistics into business;
- create agile, flexible architectures and solutions;
- offer availability and security 24 hours a day, 7 days a week.
Exprivia offers all the very latest tools for supporting both the decision-making processes and the ordinary activities based on the possession of information. The Big Data & Analytics area of Exprivia is dedicated to developing projects, services and solutions, aimed at the strategic use of big data for increasing business. The assimilation and processing of unstructured data, which, once duly reorganized, become a precious source of information for creating new value for companies, play a particularly important role in the Big Data process.
The reference guidelines are:
- direct use of Open Source technologies (such as Hadoop) and derived products;
- selection of well-supported distribution systems (such as Cloudera or Hortonworks) or Hadoop based proprietary distribution systems (SAP HANA Vora, IBM BigInsight or Oracle Big Data Appliance);
- use of open, recognizable and sharable standards (JSON, AVRO);
- design of solutions that can be integrated in the existing structure (DWH) for a gradual move towards BIG DATA technologies, in a future interpreted as a gradual and easy extension and not as a traumatic substitution.
This philosophy has many advantages: the adoption of an architecture that makes the most of the investments already made, the enrichment of the information base with external data at split costs, the planning of progressive analytical tasks on increasing numbers, the creation of an initial data lake for analytical and marketing activities, and the rationalization of hardware resources, scalable according to actual needs.