Importance of Planning, Communication and Analysis in Business Intelligence - Desklib

This article discusses the importance of planning, communication and analysis in business intelligence. It also covers the difference between traditional and contemporary business intelligence, collaborative filtering and content-based filtering, semantic analysis and visual analysis, replication and sharding, and ACID and CAP theorem. The strengths and weaknesses of Hadoop distributed processing and event stream processing are also discussed. Subject: Data Science, Course Code: NA, Course Name: NA, College/University: NA

Data Science project 2
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Contents
TASK 1............................................................................................................................................3
TASK 2............................................................................................................................................5
TASK 3............................................................................................................................................9
REFERENCES..............................................................................................................................11
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TASK 1
Planning, organization and teamwork
Wilmslow Astute is based on the data analytics firm located in greater Manchester.
Usually, this organization was established in 2016 by two friends, because they are very
passionate about the data science, business intelligence. Company will make an effective plan to
use data analytics technique service provided in different areas such as healthcare, automotive
and property business. In this way, it gained more opportunity to acquire datasets and then
perform operations in step by step manner.
On the basis of this organization, it should be developed a dynamic team which is mainly
influenced with data analytics technique so that they will create a plan to promote importance of
business intelligence in different sector or areas. But it is possible on the basis of planning which
may be inspired or motivated team member in organization. So as they can launch a business
intelligence tools. Nowadays, in market there are various tools already exists such as power BI,
tableau, Excel. These are attracting many business to organize the large amount of data or
information in proper manner (Wazurkar, Bhadoria and Bajpai, 2017). This is good thing that
team work will support planning of business intelligence. This is why because of major complex
situation identified in the business data management. That’s why, the significant role of
Wilmslow Astute as analytical firm to influences many people for achieving desirable goal or
objective.
Communication, negotiation and conflict resolution
Before launching any innovative idea in market, an effective communication plays
important role that help to share information from one person to another. In Wilmslow Astute, it
may arise conflict situation among team members because of disagreement on particular subject
or matters. Afterwards, it will be converting into complex situation and never handle
immediately (Ramakrishnan, Khuntia and Saldanha, 2018). At that time, an effective
communication will help for manager in organization to negotiate with team members in regards
of innovative analytical plan. It is very important aspect to resolve any kind of conflict through
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communication. It will try to give a preference of every team member at the time of discussion.
Therefore, every member can share their opinion and view point according to the experiences.
Due to high demand of new data scientists, company has contracted to team member where they
can complete their piece of work for them.
Fair division in labour based on individual group members
In the project of collecting large amount of dataset related vaccination. Therefore,
company will need to assign an equal tasks for their team members. A new data scientist plays an
important role to establish a strong connection with team members (Ramakrishnan, Khuntia and
Saldanha, 2018). Moreover, it behave as fair division in labour and provide preference where
they can share views on the management of large amount of data collection.
In specific project, the fair division in labour based on the individual group members
which means that represent an equal contribution of team member in the project. This can help to
influence staff member to improve their performance. For innovative project, it should require
some essential strategic plan to handle the complexity in project effectively and efficiently.
Contribution to the group
Here are different ways to contribute more effectively and make an innovative project
that will work on more successful. Regardless of particular tasks, it make better decision related
to the management of large data sets of vaccination at the time of covid-19. That’s why, analytics
approach will help to organize, manage and structured the data within single units. By using data
analytics, it is better way to make an important decision and also identify the overall populations,
who have already vaccinated. In context of health care, the contribution of Wilmslow Astute as
business intelligence firm to provide the best quality of analytical services.
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TASK 2
Difference between following concepts
Traditional Business Intelligence Contemporary Business Intelligence
Traditional BI is based on the old version
which is mainly support to implement data
through analytics tool or platform.
Contemporary BI is kind of advanced approach
for implementing data analytics but It enables
user to access, use data without statistical
analytical
Traditional business intelligence are
technically complex and required a proper
extensive IT staff member to maintain and
manage. BI to extract insight out of
information and create analytical reports for
separate manner.
This approach depends on BI tool that allow
users to filter, sort, visualise and analyse large
amount of data sets. It may support to easily
extract insight without dependence on
developer (Sun, Sun and Strang, 2018).
Traditional BI needs to be structured data
before it can be utilised
In Contemporary BI, it can be examined the
hardness of data in different formats from
multiple sources.
Focused on the answering the specific
questions about what happened in past. This
is limited capabilities of on-demand reporting.
It provides predictive and prescriptive
reporting with focused on forward approach,
diverse on demand reporting capabilities.
Table-1
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Collaborative Filtering Content Based Filtering
Collaborative filtering is based on technique
or method used by recommender systems.
This process will help to make an automatic
predictions about interests of user by
gathering preferences from users (Sun, Sun
and Strang, 2018).
Content based filtering is kind of machine
learning that uses similarities in order to focus
on feature. Afterwards, it help to make an
important decision.
It does need a specific data or information
which may be recommended for particular
users.
It does not need a specific data or information
which may be recommended for specific users.
Collaborative filtering approach will combine
a large amount of data or information.
in content filtering, it will be separately divide
data or information according to the demand.
Table- 2
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Semantic Analysis Visual Analysis
It refers to the process of checking whether it
is generated parse tree or not. This is
completely based on the rules of
programming language (Mount and Zumel,
2019).
Visual analysis is based on the process of
analysing a string of symbol either in natural
language. It can be comprised the data in the
structured format.
For purpose of semantic analysis, it is used
the semantic analyser.
For purpose of visual analysis, it can be
performed the parse performs through syntax
analysis.
Semantic analysis will check tree according to
the rule of specific language.
In context of visual analysis, it takes some
token as input and generates a parse tree as
output.
Table-3
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Replication Sharding
Replication can exists primarily to offer a data
redundancy and maintain high availability.
Sharing is kind of method or technique for
distributing across multiple machine.
In this process, it keep maintain durability of
data or information by keeping multiple
copies or replica of data on physical manner.
Sharing uses to support as deployment with
large amount of data sets, in order to improve
the capacity of single server effectively.
Table-4
ACID CAP Theorem
ACID stands for atomicity, consistency,
isolation, durability. These are basically
reinforce rules about its fields and create
relationship between themselves (Sun, Sun
and Strang, 2018).
CAP refer as consistency, availability and
partition tolerance. These are important
elements which are combined together.
ACID is basically explained the set of
properties which is guarantee a database
transaction. It has become reliable
CAP theorem is that describe how law of
physics uses and distributed system to make as
trade off among various aspects.
Table-5
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TASK 3
Hadoop distributed processing
Strength
 Cost effective- It is one of the best approach in context of cost effective which means that
provide better solution for business exploding a large data sets. In an effort to reduce the
actual cost or price, different companies are using Hadoop distributed processing to
classify the data or information (Liang and Liu, 2018).
 Flexible- Hadoop distribution processing enables enterprise to access new information
from multiple sources. Afterwards, it will be generating a more value from data. Different
companies are used Hadoop to gain more valuable enterprise insights from large data
sources such as email conversation and social media.
Weakness
 Security Concern- it is just managing a complex application like Hadoop. It is
challenging aspect to maintain security aspect. A lack of knowledge will increase the risk
or problem.
 Potential stability issues- Like all kind of open software, Hadoop has its fair to share
problem of disability. But in certain point, it is difficult to handle or equipped an issues.
Event stream processing
Strength
 Many companies are used the event stream processing which enable analysis after an
event and already happened. This can help to resolve queries of data management and
easily analysing event before their data is stored or processed.
 Event stream processing is helping to capture real time value of data or information
before it is lost in same time intervals tag between analysis and action. In some situation,
it enables to continuously know what events are happened in streaming data or
information.
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Weakness
 A data loss can happen when some of client did not get huge data or information, what
they are expected. This is serious issue identified in event stream processing. It may
chance to data loss and was not resolve critical error easily.
 Under load in context of production, it missed UDP packets, and show a problem in term
of reliability intervals.
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REFERENCES
Book and Journals
Liang, T.P. and Liu, Y.H., 2018. Research landscape of business intelligence and big data
analytics: A bibliometrics study. Expert Systems with Applications. 111. pp.2-10.
Mount, J. and Zumel, N., 2019. Practical data science with R. Simon and Schuster.
Ramakrishnan, T., Khuntia, J. and Saldanha, T.J., 2018. Business intelligence capabilities.
In Analytics and Data Science (pp. 15-27). Springer, Cham.
Sun, Z., Sun, L. and Strang, K., 2018. Big data analytics services for enhancing business
intelligence. Journal of Computer Information Systems. 58(2). pp.162-169.
Wazurkar, P., Bhadoria, R.S. and Bajpai, D., 2017, November. Predictive analytics in data
science for business intelligence solutions. In 2017 7th International Conference on
Communication Systems and Network Technologies (CSNT) (pp. 367-370). IEEE.
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