Case Study

Case Study describes the course of a specific service from the point of view of a key problem in the performance. It explains processes that are not visible to the naked eye during service provision and describes only completed and completed cases.

Below, we would like to provide you with the most important of the examples, which will show the range of experience we have as a group that sets us apart from other companies, and hints at what guides our decisions and the effect they have.

Glossary of key terms

Below are the most important terms we use in the descriptions, this is not a complete list, but it will give you a better understanding of the general issues explained, for all cases:

  • Data - processed information given priority, weight, and a component or whole that proves the correctness of the conclusion made. We consider data to be the results of analyses, including predictions.
  • Data mining - digging into data, a standard term familiar to big data analysts. Data mining is used to find patterns and relationships in structured data - e.g. from ERP systems, CRM, accounting applications, spreadsheets.
  • Digitization - the meaning of this word will always refer to the transfer of physical (paper) documents into a digital form (e.g. a scan).
  • Information - An unspecified and uncharacterized value that has not been processed (raw). Information is used to perform analyses, and all available information creates Population.
  • Knime - is the name of a free solution for advanced operations and analysis of large collections of information. It is an advanced environment that provides the full range of tools used in BI.
  • NLP (Natural Language Processing) - a collection of technologies used to analyze text according to a general or predefined dictionary (e.g., SJP,
  • OCR (Optical Character Recognition) - the basic technology used to convert a scan as an image into text.
  • Population - is a term for the total unspecified information that we may obtain from a customer. The population can consist of contracts, reports, invoices, emails, photos, headlines, and any other information in the form of text, graphics, or audio.
  • Sample/group - in the cases described, we will call a group or sample a specific set of information that has been selected from the population and will be further analyzed.
  • Text mining - a term describing digging into unstructured data and transforming them into structured data suitable for analysis - such as text data from emails, documents, social media presentations, or websites.

Below is a list that includes the case studies described so far, focusing on the main problem and how to solve it: