**3. The architecture of the BDI ecosystem**

*Data Integrity and Quality*

**62**

**Authors** Saggi et al

Kim et al

**Table 12.**

*Comparative Analysis of curated survey papers with specific parameters.*

2020

Survey sample data approach to handle big

Recognition of overlapping units and

correction of misclassification errors

data integration

2018

**Year**

**Study Objectives**

To bridge the gap by big data processing

and analytics

**Advantages** A comprehensive review of big

data projects in terms of analytics,

management, and machine learning

**Disadvantages**

It is required to carry

Y

Y

N

Y

N

Y

out empirical research

based on qualitative

and quantitative

methods

Statistical inference

Y

Y

N

Y

N

Y

variance estimation

with non-parametric

propensity score

tuning is not covered

**1**

**2**

**3**

**4**

**5**

**6**

The outline architecture of the BDI ecosystem is shown in **Figure 5**. This architecture has four major components. These components are Data Sources, Data Operations, Virtual Databases and Business Intelligence. This architecture also shows the operations performed by each of these components. The business Big data would be collected from various distributed sources in different formats and sizes in Data Sources component. The Data Operations component shows the different operations which are performed on this heterogeneous Big data.

The Big data gathered from various types of physically distributed databases are integrated to form a unified logical virtual database. Business intelligence information is extracted from this virtual data source by performing the operations stated in Business Intelligence Component. This intelligent information would be used for real-time intelligent business decision-making process across the organization.

**Figure 5.** *The architecture of the BDI ecosystem.*
