Classmate 1: Organizations are widely associated with the use and application of data and information in which data management has become the main concern (Tuchkova & Kondrasheva, 2019). Poor data quality and management will create barriers for the development of organizations due to which they may not be able to maintain proper records, make precise decisions, enforce the strategic processing techniques, and enhance the improvement of business standards. All these will show impacts on the efficiency of organizations very badly (Neha K, 2012). Moreover, it was estimated that companies face a loss of 9.7 million dollars of capital per year. Therefore, poor quality management of data will shred down the business of organizations (Aberer, 2011). Data mining is the process of unveiling the data patterns from a big and voluminous set of data and detecting anomalies to prevent them from corrupting useful information. Data mining is an analytical tool that has been used to prevail in the business era, and it helps organizations to expand the ambit of achieving success with the support of precise decision-making (Aberer, 2011). It can be logically related that the ability of decision-making will be enhanced with the critical analytics of data with an increased set of predictions that probably help make effective changes in organizations (Neha K, 2012). Hence data mining is also defined as the process of knowledge discovery in databases (Tuchkova & Kondrasheva, 2019) Text mining is a part of data mining, which can also be called as text data mining. Similar to data mining, text mining involves the process of confidential and quality information from the textual context of data (Aberer, 2011). It is a procedure that involves statistical analytics that unveils the patterns of data (Tuchkova & Kondrasheva, 2019). Text mining is being used in various fields like call centers for transcribing, customer surveys, and online reviews. The main motive of text mining is to transform the textual content into actions (Neha K, 2012). Classmate 2: Business costs: Business costs are identified as one of the priority areas for SMEs. The purpose of this study is to simplify the management cost of SMEs and effectively address the issue of the Evaluation Index system. (Guo Yan, 2015) The continuous change is characteristic of not only social space but also economic structure and business. (Ponisciakova, 2015) For the reasons and reasons for these changes in our agents, our financial circumstances are changing, but the process has been operating for many years, and the market policy has become real, but the importance and impact of the new phenomenon are growing. The advantages of the factor-entropy method are shown in the evaluation index system. However, the emergence of global trends and transitions depends on the private sector and its impact on development. (Daniel M. Franks et al., 2014) It identifies environmental and Business costs as an additional means of trans.

1. Classmate 1:
Organizations are widely associated with the use and
application of data and information in which data management
has become the main concern (Tuchkova & Kondrasheva, 2019).
Poor data quality and management will create barriers for the
development of organizations due to which they may not be able
to maintain proper records, make precise decisions, enforce the
strategic processing techniques, and enhance the improvement
of business standards. All these will show impacts on the
efficiency of organizations very badly (Neha K, 2012).
Moreover, it was estimated that companies face a loss of 9.7
million dollars of capital per year. Therefore, poor quality
management of data will shred down the business of
organizations (Aberer, 2011).
Data mining is the process of unveiling the data patterns from a
big and voluminous set of data and detecting anomalies to
prevent them from corrupting useful information. Data mining
is an analytical tool that has been used to prevail in the business
era, and it helps organizations to expand the ambit of achieving
success with the support of precise decision-making (Aberer,
2011). It can be logically related that the ability of decision-
making will be enhanced with the critical analytics of data with
an increased set of predictions that probably help make
effective changes in organizations (Neha K, 2012). Hence data
mining is also defined as the process of knowledge discovery in
databases (Tuchkova & Kondrasheva, 2019)
Text mining is a part of data mining, which can also be called
as text data mining. Similar to data mining, text mining
involves the process of confidential and quality information
from the textual context of data (Aberer, 2011). It is a
procedure that involves statistical analytics that unveils the
patterns of data (Tuchkova & Kondrasheva, 2019). Text mining
is being used in various fields like call centers for transcribing,
customer surveys, and online reviews. The main motive of text

2. mining is to transform the textual content into actions (Neha K,
2012).
Classmate 2:
Business costs:
Business costs are identified as one of the priority areas for
SMEs. The purpose of this study is to simplify the management
cost of SMEs and effectively address the issue of the Evaluation
Index system. (Guo Yan, 2015) The continuous change is
characteristic of not only social space but also economic
structure and business. (Ponisciakova, 2015) For the reasons
and reasons for these changes in our agents, our financial
circumstances are changing, but the process has been operating
for many years, and the market policy has become real, but the
importance and impact of the new phenomenon are growing.
The advantages of the factor-entropy method are shown in the
evaluation index system. However, the emergence of global
trends and transitions depends on the private sector and its
impact on development. (Daniel M. Franks et al., 2014) It
identifies environmental and Business costs as an additional
means of translating business costs and decision-making.
Data mining
Data mining is a field of research with experience in relevant
methodological research and technical resources to generate
useful knowledge from a variety of data. (Ma, X., 2014).
Specifically, the tools used to extract data and gain knowledge
from the information gathered are described. It focuses on the
performance, use, impact, and volatility of a large data set
technique. (Han, J., 2011). The information gathered from these
repositories can help project managers, developers, and
businesses gain interesting insights. (Gupta, S., 2019).
Text Mining
The current research focuses primarily on the efforts of the
organization to facilitate user engagement rather than voluntary
consumer discussions between communities. (Kim, 2019) In
fact, due to the proliferation of online resources such as blogs,

3. e-mail, and social media, big data is highly text-based.
However, if you can't use it with analytics, it's much less likely
to have big data.(Chakraborty, 2013) Previous works have
shown that human explanatory works play an important role,
especially in stages (a) and (d). In addition, the proposed
methodology includes blogs, social networks, forums, and more.
(Buenano-Fernandez,2020)