Business Intelligence, Data Handling, and Softcat Report Evaluation

This report provides a comprehensive overview of business intelligence and data handling, focusing on key concepts and their practical applications. It delves into the significance of business reporting, data warehousing, data mining, and predictive analytics software, illustrating their roles in transforming raw data into actionable insights for strategic decision-making. The report uses Softcat, an IT services company, as a case study to demonstrate how these concepts can be applied in a real-world business context. It examines the tools and techniques used for data collection, integration, analysis, and presentation, emphasizing their impact on operational, tactical, and strategic business decisions. The report also explores the benefits of data warehousing, data mining, and predictive analytics in enhancing business reporting and improving organizational efficiency. The references section includes academic resources to support the research.

Data Handling
And Business Intelligence

Table of Contents
Introduction......................................................................................................................................1
Business Intelligence...................................................................................................................1
Business reporting.......................................................................................................................1
Data warehousing........................................................................................................................2
Business intelligence...................................................................................................................2
Data mining.................................................................................................................................3
Predictive analytic software.........................................................................................................3
Conclusion.......................................................................................................................................4
References........................................................................................................................................5

Introduction
Business intelligence refers to set of technologies, architects and processes that are liable
for converting raw data within meaningful information that is liable for driving in profitable
business actions. It renders a direct influence on operational, tactical and strategic business
decisions of firm (Bughin, 2016). Business reporting is liable for carrying out public reporting of
financial and operating data by enterprises along with this it involves continuous provision of
information with respect to decision makers in a firm for supporting their work. This report is
based on Softcat who deals within IT industry and their service involves asset management,
collaboration, business intelligence & analytics, end-user computing & mobility, networking &
security and there are many others. This report is based on business reporting along with its
critical evaluation.
Business Intelligence
The applications, practices and technologies that are utilised for collecting, integrating,
analysing as well as presentation of operations are referred to as business intelligence. It is liable
for leveraging services along with software for transforming data within actionable insight which
is responsible for informing decisions of firm (Fiaz and et. al, 2016). This will enable
organisations like Softcat with tools for accessing and analysing data sets which will furnish
analytical findings within graphs, maps, dashboards, reports and summaries for providing their
users with enhanced intelligence in context of state of business. It is liable for merging business
analytics, data visualisation, mining, tools as well as infrastructure which will lead firms like
Softcat to render a comprehensive view of data which can lead to drive changes, elimination of
inefficiencies as well as adapting to supply changes. This will aid firms in business reporting in
an appropriate ways. For an example, when data is collected from distinct sources it will provide
different aspects related with particular perspective of the organisation. This will assist them to
develop decisions in accordance by processing and anticipating crucial assets which will be
provided by them (Martínez-Rojas, Marín and Vila, 2015). For this, Softcat can make use of
tools like SAP Business intelligence, MicroStrategy, Yellowfin BI and many others. This will aid
them in having insight by carrying out in-depth analysis.
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Business reporting
The process of improvisation of quality as well as transparency of information, which is
furnished by firms to their investors as well as key stakeholders for formulation of better
decisions, is referred to as business reporting. This acts as an important aspect while planning as
it involves rendering information as well as data to their specified audiences (Mohanty, Bhuyan
and Chenthati, 2015). An instance can be taken to acknowledge this aspect like Softcat render
different services so they have provide their customers as well as stakeholders with information
related with financial plans, customer service reviews (to employees so that their team can
enhance their services) and marketing research outcomes. The emphasis has been shifted to
models which acts as significant value drivers along with qualitative information related with
strategies, risks, opportunities and plans. There are different tools that can be utilised by Softcat
for reporting, they are: Zoho Analytics, HubSpot, SAP Crystal Reports, Dbxtra and many others.
Business reporting illustrates intelligence that is being attained by reporting about
specified aspects related with business. For formulation of business reporting it involves
different aspects through which this data is being developed (Trivedi and et. al, 2017). In this
case, concepts like data warehousing, business intelligence along with data mining will be used;
they are illustrated within other sections.
Data warehousing
The process associated with collection as well as management of data from different
sources for rendering meaningful insights into business is referred to as data warehousing.
Basically, it implies process associated with construction as well as usage of data warehouse. It
is constructed through integration of data from heterogeneous sources that are responsible
supporting ad hoc queries and analytical reporting which will assist within formulation of
decision making. Both data warehousing and business intelligence are utilised for describing
processes associated with storage of data of firm within internal or external database. (In this
context, Softcat can make use of cloud computing to ensure that on-demand availability of
resources of computer systems which comprises of computing power and data storage without
any kind of active management. For an instance the firm can avail space from cloud for storing
their information as well as make payments accordingly) (Bughin, 2016). Basically, with respect
to business reporting data warehousing is utilised as it comprises information from distinct
resources and by making use of business intelligence firms can have insight into their operations
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which will aid them within data visualization. Softcat can opt for Amazon Redshift, Teradata,
Informatica, Oracle 12c and many others.
Data mining
The process that is being utilised by firms for turning raw data within useful insight is
defined as data mining. This aims at finding out concealed, valid as well as potential patterns
within huge data sets (Fiaz and et. al, 2016). It is liable for identification of
previously/unsuspected unknown relationship among data. This acts as a multi-disciplinary skill
which utilise AI, machine learning, database technology and statistics. This will render Softcat
with an insight with respect to fraud detection, scientific discovery and marketing, etc. It will
lead to identification of correlation, anomalies and patterns among large data sets for predicting
outcomes. Softcat can make use of distinct techniques through which they can enhance
information related with revenues can be enhanced, improvised customer relationship, minimise
cost, reduction in risks and many more. Business reporting can be attained through this as it (data
mining) will assist them to extract the data through which intelligence can be attained. Through
this firm can have appropriate business reporting which will lead them to formulate effectual
decisions (Martínez-Rojas, Marín and Vila, 2015). For this, Softcat can make use of tools like
RapiMiner, Apache Mahout, Sisense and many others are available which can be used depending
upon their requirements.
Predictive analytic software
The wide range of techniques are provided from machine learning, predictive modelling and
data mining for analysing present as well as historical facts for making out predictions with
respect to future or other unknown instances is defined as predictive analytics software. It will
aid Softcat to formulate their reports and share with their stakeholders in an appropriate manner
by acknowledging their positioning within the market and what they can bring in through which
their services can be enhanced. Basically, information will be provided in context of past and by
making use of it decisions can be made for future (Mohanty, Bhuyan and Chenthati, 2015). This
also implies that technology like cloud computing has to be used so that details related with them
can be accessed when they are required. The technology driven process that is liable for
analysing data as well as presentation of actionable information which assist managers,
executives and other end users for making business decisions is referred to as business
intelligence (Trivedi and et. al, 2017). These tools will furnish intelligence in this context.
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Conclusion
From above it can be concluded that business reporting refers to a document that is liable for
analysing condition and make use of theories through which improvisations can be made. This
implies that business intelligence denotes technology driven processes for carrying out analysis
as well as present actionable information which will aid authorities to formulate decisions. Data
warehouse is being utilised for storage of information, it relevant content is extracted through
utilisation of data mining and intelligence will be attained through this. It enables them to
formulate plans and reports with respect to financial conditions along with other aspects to attain
the organisational goals.
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References
Books & Journals
Bughin, J., 2016. Big data, Big bang?. Journal of Big Data, 3(1), p.2.
Fiaz, A.S., and et. al, 2016. Data visualization: enhancing big data more adaptable and
valuable. International Journal of Applied Engineering Research, 11(4), pp.2801-2804.
Martínez-Rojas, M., Marín, N. and Vila, M.A., 2015. The role of information technologies to
address data handling in construction project management. Journal of Computing in Civil
Engineering, 30(4), p.04015064.
Mohanty, H., Bhuyan, P. and Chenthati, D. eds., 2015. Big data: A primer (Vol. 11). Springer.
Trivedi, S.K. and et. al, 2017. Handbook of research on advanced data mining techniques and
applications for business intelligence. IGI Global.
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