Ultimate Guide to Business Intelligence (BI) for Businesses

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business decisions in the past were
often based on a combination of Prior
experience accumulated knowledge and
intuition but management by gut feeling
has taken a back seat to data-driven
decision making business intelligence
tools combine data analysis data
visualization and Reporting capabilities
to uncover actionable insights and
deliver them to Executives managers and
other business users business
intelligence commonly known as bi helps
guide and organization's operational
decision making and strategic planning
bi applications generate insights on
business performance processes and
Trends so management teams can identify
problems and New Opportunities then take
actions to address them the result can
be more efficient and productive
business operations more effective
marketing competitive advantages over
industry Rivals and ultimately higher
revenue and profits bi software emerged
in the early 1990s and is widely used in
both large and small businesses more
recent developments include self-service
bi tools embedded bi deployments in
business applications and augmented
analytics features based on AI and
machine learning technology now instead
of relying on BI professionals to run
queries for them as in the early days of
bi business users increasingly can
analyze the data themselves
the bi process is being even further
democratized by the introduction of
generative AI large language models and
their chatbot interfaces into mainstream
bi tools but bi and data management
teams still face a variety of challenges
in deploying managing and supporting
Enterprise bi systems
we'll examine the basics of bi tools as
well as what businesses need to know
about using them including their
business benefits and those challenges
for a deeper dive explore our complete
collection on all things Enterprise bi
by clicking the link above or in the
description below
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bi tools evolved from earlier decision
support systems that were developed
starting in the 1960s
those systems were designed primarily to
funnel information to senior business
Executives in contrast modern bi
platforms have broader functions and
user bases that extend from c-suite
Executives to department heads middle
managers business analysts and Frontline
operational workers here are the
business intelligence functions
currently prevalent in the Enterprise
data analysis this is the linchpin of
data-driven decision-making processes
business users and bi analysts can run
queries to analyze data for business
insights that can be used to optimize
business processes marketing campaigns
corporate strategies and other
Enterprise elements querying and
Analysis also highlights business Trends
so Executives can explore ways to
capitalize on new Revenue opportunities
that otherwise might be missed business
monitoring and measurement bi systems
track key performance indicators and
other business metrics so Executives and
business managers can continuously
monitor the performance of individual
business units or the entire
organization
business problems can be identified and
addressed in a more proactive way than
they could in the past when performance
reports were less Timely
reporting and information delivery
perhaps obvious but important bi results
must be made available to business users
so they can well use the information
initially that was primarily done via
static reports often sent out in printed
form reports are still widely used but
bi dashboards have become increasingly
popular they offer a more Visual and
interactive interface with built-in data
visualizations and the ability to drill
down into the underlying data for more
analysis alerts can also be set to
automatically notify users of predefined
performance thresholds or problems and
predictive analysis conventional bi is a
form of descriptive analytics by
analyzing historical data or real-time
data streams it examines things that
have already happened or are happening
now
Predictive Analytics forecasts future
events it's a type of advanced analytics
usually done by data scientists but bi
tools can be used to run predictive
models and what-if Analysis queries on
the outcomes of different business
scenarios thus adding a predictive
element to the bi process
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consulting firm Gartner says the core
capabilities of bi platforms should
include things like security governance
cloud-enabled analytics data source
connectivity data preparation automated
insights data visualization reporting
and data storytelling
self-service querying visualization and
Reporting are supported in all bi tools
now in addition the augmented analytics
features built into bi platforms include
natural language querying support and AI
driven technologies that help users find
and understand data prepare it for
analysis and create visualizations for
specific bi uses businesses can also
deploy other types of tools such as data
mining software real-time analytics
systems and online analytical processing
engines
but there's more to business
intelligence environments than the bi
tools themselves a typical bi
architecture also incorporates internal
source systems and external data sources
data repositories such as data
warehouses and data Marts plus now maybe
a data lake or data lake house and a
variety of data processing and data
management tools
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one technology analyst describe bi and
analytics as a business's eyes and ears
no longer nice to have but rather must
have that's because bi can identify
business issues that need to be
addressed enable faster and more
informed decision making
increase operational efficiency and
productivity
improve marketing and sales programs and
Aid strategic planning by business
executives
looking at different Industries
manufacturers use bi software in
production planning material and Supply
procurement Supply Chain management and
monitoring of manufacturing operations
retailers use bi to plan marketing
campaigns and product promotions manage
inventory and replenish products Banks
use it to help assess Financial risks
when deciding to approve mortgage and
loan applications they and other
Financial Services firms also analyze
customer portfolios with bi tools to
help plan cross-selling efforts aimed at
getting customers to buy additional
products hospitals analyze patient
outcomes and readmission rates to
improve patient care while doctors use
bi software to analyze clinical data and
help diagnose medical conditions
insurers rely on BI to evaluate risks
when considering applications for
insurance policies and to analyze policy
pricing hotel chains use bi to track
room occupancy rates adjust pricing
based on booking demand and manage
customer loyalty programs Airlines
likewise track ticket sales and flight
occupancy and manage flight schedules
crew assignments and food and beverage
ordering and transportation companies
plan distribution schedules and routes
and monitor gas mileage and other
aspects of Fleet operations
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in businesses data-driven speed is good
so long as the information that's used
is reliable The Accelerated decision
making that bi enables could lead
companies astray if it's based on faulty
or incomplete data and inaccurate
analytics results
some data management challenges that
enterprises can encounter in bi
initiatives include integrating data
from different systems ensuring data
quality and breaking down data silos all
crucial to do items so bi data is clean
consistent and complete other major bi
challenges involve project management
issues such as training users meeting
their data and analytics requirements
managing self-service bi deployments so
they don't devolve into chaotic
environments and avoiding bad data
visualization and dashboard design
practices integrating generative AI into
bi processes is becoming another
challenge for bi teams user adoption
issues are another potential business
intelligence roadblock business users
might be reluctant to give up Excel
spreadsheets or other familiar tools and
switch to bi software and creating a
data-driven culture remains an ongoing
challenge in many companies
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the following steps can help your
organization create a viable business
intelligence program that takes data
analysis Beyond tactical uses to a more
strategic level
one get management approval for the bi
program
that includes funding from corporate
Executives to staff a bi team and
purchase the required software and
Hardware
to help get the program approved
document business requirements potential
bi use cases and expected benefits with
an eye toward Roi
two develop your bi strategy visualize
what BI success should look like and
come up with a plan to make it a reality
start with an audit of existing
analytics tools and a survey of business
Executives and workers about their use
of data then consider data privacy
protections governance support for
self-service bi users technology needs
what kpis to track and other issues
three set up and staff the bit business
intelligence teams and large Enterprises
typically include a range of bi roles
and responsibilities from a bi director
or program manager to positions like bi
architect developer and analyst
but some of those roles may have to be
combined into one position in smaller
companies with limited budgets and
resources
four design the bi architecture plan out
the hardware and software components of
your bi architecture and how data will
flow through it from the original Source
systems to a data warehouse or datamart
and then to bi tools also decide whether
to deploy the environment on premises or
in the cloud although most new spending
on BI platforms is for cloud deployments
5. select bi and data visualization
tools the software selection process for
bi tools should involve business users
and ensure that the chosen software
meets their business needs that could
mean purchasing multiple tools for
different bi applications or separate
business units in self-service bi
environments 6. plan and conduct end
user training training is a crucial step
to familiarize business users with bi
tools and processes and to make sure
they're aware of data governance privacy
and security policies
and finally seven deploy and test the bi
system
before going live with the bi
applications test the environment to
make sure things work as planned that
includes the bi tools themselves plus
all the data processing and management
components
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long gone are the days of the cigar
chomping executive making reactive
business decisions based almost solely
on outdated statistics wishful thinking
and a bit of hubris today's business
intelligence Tools Plus the people with
the know-how to select support and apply
them properly can potentially raise your
company's business IQ and performance to
a higher level
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