Data Handling and Business Intelligence

This document provides an overview of data handling and business intelligence. It covers research literature, knowledge and understanding, analysis, practical application, and skills for professional practices. The document explores different techniques and tools used in business intelligence and discusses the benefits and trends in the field. It also highlights the importance of data analysis and problem-solving skills in business intelligence.

Data Handling and
Business Intelligence

Table of Contents
Research informed literature..................................................................................................1
Knowledge and understanding business intelligence.............................................................1
Analysis..................................................................................................................................2
Practical application along with deployment.........................................................................3
Skills to professional practices...............................................................................................4
References........................................................................................................................................5

Research informed literature
Business intelligence is defined as application, practices and technologies for collecting,
integrating, analysis as well as presenting information possessed via business. The rationale of
business intelligence is to render support through which firms can formulate effective decisions.
It is accountable for aggregating data mining, business analytics, data visualisation,
infrastructure, tools and making best practices through which data driven decisions can be
developed (Jain, Tripathi and Shree, 2020). This will lead firm to drive in alterations, eradication
of inefficiencies as well as quick adaptation of supply changes or market. There are different
business analytic techniques they are:
Data mining: To sort larger datasets through the usage of statistics, database along with
machine learning for identification of trends and establishment of relationships.
Querying: This involves peculiar data from database.
Data preparation: It involves process to combine as well as structure data for preparing
analysis.
Reporting: This comprises of sharing operating along with financial information analysis
through which decision makers can derive into certain conclusion.
Benchmarking: Here, comparison is made in between business processes as well as
performance metrics for tracking performance against competitors.
Apart from all these techniques, there are certain tools that also aids organisation within
extracting precise information through which it will become easy for decision makers to
formulate strategies. This involves ad hoc analytics, online analytical processing, mobile, real-
time and operational business intelligence.
Knowledge and understanding business intelligence
At present scenario, the immediate reporting capabilities are being possessed by most of
the business applications tool like financial management software and customer relationship
management. As a form technology, business analytics and intelligence is more accessible that
provides organisation with wide range of benefits (Niño, Niño and Ortega, 2020). There are
different trends that prevail within the market in context of business intelligence. They are
specified beneath:
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Artificial intelligence: As per the reports of Gartner, machine learning and AI are liable
for conducting critical activities that are done via usage of human intelligence. In addition to this,
the capability is being leveraged to deal with real time data analysis along with dashboard
reporting.
Collaborative business intelligence: BI software is integrated with collaborative tools
that comprises of social media along with other enhanced technologies through which overall
work can be amplified (Pagliacci, Sani and Calvo, 2020). Through sharing of work the
collaborative decisions can be made which will further amplify overall development of the
organisation in an adequate manner.
Embedded BI: This concept is accountable for incorporation of some features within
business applications for enhancement along with extension of reporting functionalities.
Embedded analytics implies usage of reporting along with analytic capabilities within the
transactional applications of the business.
Cloud analytics: The BI application will be rendered within the cloud and it is identified
that through this technology the decisions can be made quickly. This is liable for analysing data
on demand. This will enable organisations within having scalability and enhanced agility through
which data analysis capacity can be amplified.
Data quality management: The quality of information is critical issue that is faced via
data analysts while delivering their responsibilities. By having quality information, it becomes
easy to have insight into data that is available. Organisation must consider different parameters,
they are: validity, completeness, consistency, accuracy, uniqueness and timelines.
Analysis
It has been identified that business intelligence refers to aggregation of data collection, its
storage along with knowledge management with analysis for evaluation along with
transformation of critical information (Rahahleh and Omoush, 2020). It is identified that for
doing so, organisations tend to make use of wide range of applications, strategies, technical
architectures, technologies and products for collecting, analysing, presenting along with
disseminating external and internal business information. The benefits that can be attained by
organisation by the usage of business intelligence are specified beneath:
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Accurate and fast reporting: Employees can opt for utilisation of customised reports or
templates for monitoring KPIs through the usage of wide range of data sources that comprises of
sales, financial and operations data. Such kind of reports is so interactive that users can make use
of different variables in order to access information in quick manner.
Competitive analysis: This aspect is liable for providing ability for management along
with manipulation of larger data so that competitive vantage can be attained affirmatively. In
addition to this, forecasting, budgeting and planning is powerful for staying ahead from their
competition and going beyond standard analysis by making use of BI software (Vilander, 2020).
Furthermore, sales can also be tracked so that marketing performance of competitors can be
analysed in appropriate manner.
Identification of market trends: This aspects aids within identification of new
opportunities as well as build strategy through the usage of supportive data. This will lead to
creation on direct influence on long term profitability as well as render wide scope to what is
occurring.
This is analysed that by making use of business intelligence that varies from extraction of
information, mining it and its utilisation enables organisation to have strong competitive edge.
This will lead businesses to attain desired standards of productivity along with profitability.
Practical application along with deployment
Business intelligence aids organisation within having actionable and meaningful
information that can be utilised for supporting efficacious tactical, strategic along with
operational insights. The reports are generated on the basis of real time statistics that are relevant
for business through which they can respond quickly (Zhou and et. al, 2020). The BI software
solution is liable for analysing data that is being fed or input by the data sources then this is
organised in different patterns as per the trend so that precise intelligence can be attained. The
applications of BI as well as their deployment are specified below:
Google: Data driven reviews of performance
The vigorous information culture within the organisation comprises of team named
people analytics, they are accountable for bringing information for bearing employment-related
questions. Through this they are able to have result oriented approach and their findings involve
rooted data analysis.
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Grow: Prompt visualisations
The firm work with Heap for unearthing the requirements of their user in context of free
software trails (15 BUSINESS INTELLIGENCE EXAMPLES & APPLICATIONS, 2019). This
was rough draft but provided Grow with relevant sense related with their offerings. The firm was
able to acknowledge that customers needed speed and easily create visualisations.
These are some applications of business intelligence that enabled organisation with
formulation of decisions by taking into account certain aspects. There are many more fields
where this concept is used for having an insight into their offerings.
Skills to professional practices
The business intelligence and front-end skills are more geared to present as well as
communicate data with others. Skills that are needed with reference to business intelligence are
mentioned below:
Data analysis: Most of the activities that are associated with BI involve analyst
associated capabilities and through the usage of data better decisions can be formulated. This
leads them to reach to accurate conclusion.
Problem solving: BI is not only about carrying out analysis and this is also related with
creation of strategies as well as solving real world problems associated with data. For an
instance, individual can have actionable insight from peculiar retail KPIs that requires
visualisation and can be easily presented during meeting.
Advanced vision along with attention toward details: The critical aspect that is
mandatory is detail orientation. For BI analyst, it is important that with small segment of
information, it might become necessary to convert this into an actionable insight (A Guide To
Starting A Career In Business Intelligence & The BI Skills You Need, 2019). This needs that
there has to be forward thinking vision along with minutely accessing each detail so that precise
decisions can be formulated.
These are some skills that must be possessed by business analyst in order to ensure that
they are able to extract the intelligence from the information they have. This will also lead them
to develop decisions and have a precise insight into different aspects of the business.
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References
Books and Journals
Jain, A., Tripathi, R.C. and Shree, D., 2020. Block-2 Data Handling.
Niño, H.A.C., Niño, J.P.C. and Ortega, R.M., 2020. Business intelligence governance framework
in a university: Universidad de la costa case study. International Journal of Information
Management, 50, pp.405-412.
Pagliacci, M.G., Sani, S. and Calvo, E., 2020. “Business intelligence” and “Big Data”: A
winning connection for management of enterprises. In Management and evolution of the
European Union member states in the Big Data era (pp. 64-72). Sciendo.
Rahahleh, A.H. and Omoush, M.M., 2020. The Role of Business Intelligence in Crises
Management: A Field Study on the Telecommunication Companies in
Jordan. International Business Research, 13(1), pp.221-232.
Vilander, R.M., 2020. Business Intelligence and Developing Management Reporting: Action
research in a case organization.
Zhou, C. and et. al, 2020. A data-driven business intelligence system for large-scale semi-
automated logistics facilities. International Journal of Production Research, pp.1-19.
Online
15 BUSINESS INTELLIGENCE EXAMPLES & APPLICATIONS. 2019. [Online]. Available
through: < https://builtin.com/big-data/business-intelligence-examples-applications>.
A Guide To Starting A Career In Business Intelligence & The BI Skills You Need. 2019. [Online].
Available through: <https://www.datapine.com/blog/bi-skills-for-business-intelligence-
career/>.
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