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Designing BI Solutions in the Era of Big Data

1. Introduction

Companies are following different strategies in order to be competitive against others. According to Competitive advantage: Creating and sustaining superior performance, the advantages can be derived from following two aspects: (1) operational efficiency and (2) unique value creation for customers. Both aspects involve building an enterprise structure and designing a business process in a systemic and unique way.

For these reasons discovering new business value adding process based on business historical behavior (extracted from data) to overcome their competitors is emerging. Such can be achieved with support of business intelligence (BI). According to An architecture for ad-hoc and collaborative business intelligence, current BI implementations suffer from several shortcomings:

  • Missing focus on the individual needs of particular analysts or decision makers. These users are forced to rely on standard reporting and predefined analytical methods that often do not answer to all needs of the individual. They strongly depend on either IT administration or enhanced technical skills.
  • The lack of business context information, such as definitions, business goals, and strategies as well as business rules or best practices for the provided analytical data. Hence, business users have to understand the semantics of data by themselves and they have to take decisions and derive strategies using additional information sources, which often leads to an escalation of efforts and costs.
  • Poor alignment between Business and IT department. The setup and configuration of current BI systems requires deep insight in both the data to be analysed and the intended analytical tasks. Content and data models have to be provided in advance by the IT department and it must support the whole information in the decision making process.
  • The modal time for new BI implementations is between 3 and 6 months causing implementation and support costs that often deter companies of a wider BI deployment.
  • BI solutions have a strong focus on structured, enterprise-internal data but lack the capability of integrating external and/or unstructured information in an easy, (near) real-time, and effective way. As a consequence, a lot of useful information is never included in the analysis. Not considering this information could provide a distorted or incomplete view of the actual world and consequently, it could lead to wrong business decisions.

Current work focuses on a presenting new approach for designing BI solutions. Presented approach is addressing following goals: (a) time reduction that is spend on BI solution designing phase; (b) flexibility achievement in BI solution by removing "data agnosticism"; (c) preparedness of BI solution to be used with big data. The research is extending existing concept ELT (Extract, Load and Transform) to an ELTA (Extract, Load, Transform and Analyse).