Data Science and Knowledge Management Assignment: Analysis and Tools

This assignment solution addresses key concepts in knowledge management and data analysis. It begins by discussing the importance of knowledge management within organizations and explores various supporting technologies such as Decision Support Systems (DSS) and Document Management Systems. The solution then differentiates between databases and data warehouses, highlighting their respective roles and benefits, particularly in the context of Business Intelligence (BI). Furthermore, the assignment delves into the WEKA tool, a comprehensive machine learning platform, and demonstrates its application by classifying data from a vote.arrf file using the J48 classifier. The solution also covers the use of Tableau for data visualization and creating interactive dashboards. The document provides a detailed analysis of the assignment questions, including the importance of knowledge management, the differences between databases and data warehouses, and the practical application of data analysis tools.

Knowledge management
 Knowledge Management is the deliberate management of knowledge
in an organizations resources to meeting tactical and strategical
prerequisites and create value; it comprises of the procedures,
activities, techniques, and frameworks that improve assessment,
storage, refinement, creation and sharing of knowledge.
 Knowledge Managment should hence provide/create the right
peoples, tools, structures (groups), knowledge, culture, and so forth
in order to improve learning; it must comprehend the application and
value of the new knowledge create

KM Tools : Decision Support Systems
 DSS is an electronic system of data that is used for supporting
decision creation in a business or organization.
 The major benefit of DSS is it can aid in better decision making,
enhanced productivity and convenient critical thinking to manage
issues with fast emerging factors.
 With the use of DSS the data can be presented to the users in a
straightforward way and as per client's specifications it can create
various reports to analyze the data.
 Limitation of this tool is that it is user driven.

KM tools : Document Management Systems
 Document management system, as the name infers, are frameworks
that guide in the storage, publishing, retrieval and indexing of
documents.
 Such frameworks although relies solely on explicit knowledge, the
sheer volume of documents that are required by the organization to
manage makes them helpful.
 Advantage is that it requires less cost and easy to managed as
compared to non-electronic system.

Database and Data warehouse
 Databases and data warehouses both of them are relational data systems
 A data warehouse system pulls data together from a wide range of
sources inside an organization for the purpose of report and analysis.
 Databases enables storage of current transactions and empower quick
access to explicit transactions for continuous business processes, which is
called Online Transaction Processing (OLTP).
 A database is streamlined to amplify the efficiency and speed with which
data gets updated (modified, add or delete) and empower quicker analysis
and access to data.
 A store huge amounts of historical data is stored in the warehouses to
empower quick, complex queries over every one of the data, regularly
utilizing “Online Analytical Processing (OLAP)”.

Benefits of data warehouse
 Data from various sources are acquired and transformed into a given
format by the data warehouse which ensures the consistency and
synchronization of data among different departments in an
organization.
 Additionally consistent and accurate data makes great basis of
improved and accurate decision making.
 A number of recorded or historic data is stored in the data warehouse
to allow analysis of various timespans and patterns for making future
predictions

WEKA tool
 The WEKA is considered as complete package for machine learning. It
has all important features which are required for machine learning,
the features are data pre-processing, classification, regression,
clustering, association rules, and visualization.
 Weka comes under GNU (General public license) and it is free source
and it does not require any purchasing of license.
 In this assignment vote.arrf file is analyzed with the help of weka and
classification of the data present in the dataset is done by using J48
classification algorithm. J48 algorithm creates a decision tree and
classify the data.

Weka tool : Classification J48 run on
Vote.arrf file

Weka Tool : Tree created

Online business dashboard: Tableau
 Tableau is one of the BI tool which is used for analyzing the data and
with the help of this tool, user can create dashboard which are easy
to share and are interactive as well.
 By using tableau different type of sources can be connected such as
file, databases and big data and by using these sources various trend
and variation can be used to generate charts and graphs.
 This is widely used tool which finds its application in the field of
businesses, academic researchers, and many government
organizations for visualize the data.
 The popularity of this tool is due to its real time collaboration and
data blending and this is the unique feature of this tool.

Visualization for Business: Total
sales

Visualization: Region Wise sales