Academic journal article Informatica Economica

Agile BI - the Future of BI

Academic journal article Informatica Economica

Agile BI - the Future of BI

Article excerpt

In a rapidly changing economy, Business Intelligence solutions have to become more agile. This paper attempts to discuss some questions which help in creating an agile BI solution such as: What is Agile? Why agile is so well suited for BI? Which are the key elements that promote an agile BI solution? Also, this paper briefly looks at technologies that can be used for enabling an agile BI solution.

Keywords: Agile Business Intelligence, Agile Business Analytics, Agile Development Methodologies, In-Memory Bi Approaches, Data Virtualization Server

1 Introduction

Business Intelligence (BI) was defined in different ways. The Data-Warehousing Institute has defined Business Intelligence as "the tools, technologies and processes required to turn data into information and information into knowledge and plans that optimize business actions" [6], Turban has defined BI as "a broad category of applications and techniques for gathering, storing, analyzing and providing access to data to help enterprise user make better business and strategic decisions." [23], The range of capabilities that can be defined as business intelligence is very broad. The spectrum of BI technologies is presented in [16].

Most enterprises have hundreds of internal and external data sources such as: databases, e-mail archives, file systems, spreadsheets, digital images, audio files and more. 80% of the organizational data are unstructured and semi-structured data.

Traditional Business Intelligence systems use a small fraction of all the data available. Also, traditional BI systems use only structured data. The core components of a traditional BI architecture are: ETL tools, an enterprise data warehouse with metadata repository and business analytics (Figure 1).

Traditional BI systems use ETL tools for extracting data from multiple sources and temporarily storing those datasets at a staging area. Organizations use data warehouses to aggregate cleaned and structured data. Business analytics/BI tools include enterprise reporting tools, ad hoc query tools, statistical analysis tools, OLAP tools, spatial-OLAP analysis tools, dashboards, scorecards and advanced analytics. Advanced analytics typically refer to: data mining tools, text mining tools, predictive analytics, artificial intelligence, and natural language processing. But this architecture is unable to get adapted to change. A study by Aberdeen Group [24] showed that "this style ofBI is predominantly controlled, driven and delivered by corporate IT. Often, only static views of data are available and any changes or enhancements must be made by the IT organization". These characteristics are in contradiction with frequently changing business requirements and "big data". Big data typically refers to the following types of data: semi-structured data (XML and similar standards), unstructured data, Web data (social data, Web logs) and real-time data (event data, spatial data, machine-generated data).

Table 1 briefly summarizes the main disadvantages of traditional BI systems.

How to eliminate these problems? By building an agile BI solution. A study by TDWI Research [22] showed that many traditional business intelligence systems are not agile:

* "33% of the organizations needed more than three months to add a new data source to an existing business intelligence system"

* "developing a complex report or dashboard with about 20 dimensions, 12 measures and 6 user access rides took on average 7 weeks in 2011"

The next section presents briefly the concept of agile BI and the key elements that together promote an agile BI solution.

2 Agile BI

Agile means the ability to be adaptable. Agile BI was defined in different ways. The Forrester Research defines agile BI as "an approach that combines processes, methodologies, organizational structure, tools and technologies that enable strategic, tactical and operational decision -makers to be more flexible and more responsive to the fast pace of changes to business and regulatory requirements" [9], According to Data Warehousing Institute agile BI "addresses a broad need to enable flexibility by accelerating the time it takes to deliver value with BI projects. …

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