Data Handling and Business Intelligence - Current Trends and Strategic Impact

Data Handling and Business
Intelligence

Table of Contents
INTRODUCTION...........................................................................................................................2
MAIN BODY..................................................................................................................................2
Current trends in business intelligence........................................................................................2
REFERENCES................................................................................................................................6
1

INTRODUCTION
Business analytical refers to the technical infrastructure that stores, collect and analyse data.
This study is going to discuss some current and effective trends of business analytics such as
self-service BI, data visualizing and others (Maheswaran and Asirvatham, 2018). Further, it will
show impact of business analytics on improving performance, better business decision and
strategic development. It will also show some limitations of business analytics such as cost and
complexities while uses and implementation.
MAIN BODY
Current trends in business intelligence
Before discussing current trends and strategic impact of business intelligence utilization, it
is important to know about business intelligence. In regard to business intelligence, it can be said
that it is a technology driven process that helps businesses in analysing big data and providing
actionable valuable information to managers, workers and internal stakeholders by which they
can make informed business decisions (Omar, Minoufekr and Plapper, 2019). It helps employees
to become more intelligent and informed about businesses. there are some tools that are being
used by businesses the most for business intelligence such as: dashboards, reports, warehouse,
cloud data services and others.
Automation, collaborative insights, natural language processing are some current trends in
business intelligence. The main key of businesses of any sector is: increasing customers’
satisfaction rate and it can be increased when businesses have information about customers as
what they want, which are their preferences and others. This technology makes able to managers
and customers relationship manager in predicting and knowing about consumers’ behaviours.
Manager can gather data related to emotion detection, speech analytics and customers’ journey.
Some current trends include:
Automation: There are numbers of large companies that make use of artificial intelligence
in order to automate data. This automation eliminates manual data processes and this time can be
utilized in making decisions. An ability to rapidly analyse data and act on results define business
intelligence. Business processes is being speed up with data automation. (Maheshwari, Gautam
2

DATA HANDLING AND
BUSINESS INTELLIGENCE
1

INTRODUCTION
Business intelligence is a modern concept based on a technology driven tools which are helping
in analyzing data and delivering the information of actionable nature to the managers, executives
and workers in making business decisions in an informed manner. It allows for handling business
practices with higher level of intelligence (Grover and et.al., 2018). Through BI tools, reams of
information can be converted into bite – sized insights for making informed business decisions.
The huge data sets are analyzed through BI tools and accordingly findings are presented in the
form of reports and dashboards. The present report is based on such BI technique by specifically
regarding the current trends in data warehousing, business intelligence and data mining.
MAIN BODY
Both data warehouse and data mining are facilitated through the tools of BI. Data warehouse is
basically related to the storage and organisation of data to facilitate BI processes. It is designed
to support the activities of business intelligence, especially for analytics. It is intended to perform
analysis and queries by storing huge amount of historical data. Therefore in BI, it serves as the
backbone of storage of data.
BI is largely meant for monitoring and tracking data sets against the KPIs of the business or the
goal of the business (Popovič, Puklavec and Oliveira, 2019). However, the data mining practice
allows for analysis of data sets in order to detect the emerging trends and patterns as indicated by
the data and is meaningful for making effective business decisions. It is used for finding solution
to the issues associated with the business by exploring the available data sets by recognizing the
patterns in the raw data which results in useful insights of the business.
With regards to the requirement of the report, the following trends pertaining to the business
intelligence tools that are current evolving in the data driven environment has been reviewed.
Cloud Adoption and accelerated SaaS: Nowadays it has been seen that businesses are migrating
to a cloud based BI allowing them to host on public or private cloud or can be able to subscribe
to a Software as a Service solution. The main benefits that can be derived from implementing
cloud based BI are reduced stress due to accessibility of data from the cloud from any location
and on any device. There is an increased scalability and flexibility and allowing for simpler
management and administration. It is also providing security through data backup and disaster
assistance. Many corporations get benefitted of this version of BI in the time of COVID-19 in
facilitating the transition of working remotely
New BI is based on AI: AI technologies have even marked their presence in BI where modern
business intelligence solutions are empowering businesses with augmented analytics which is
helpful in detecting anomalies, analyzing unexpected events and dig deeper to take out highly
relevant and useful information. Also, it helps in humanize data and making it more accessible to
all (Richards and et.al., 2019).
Automation: As there is a scaling up of data analytics and there is a constant increase in data
volumes, automation would be necessary for the elimination of data processes that are manual,