Business intelligence consist the strategies and technologies used by enterprises for the data analysis of business information. These technologies provide historical, current, and predictive views of business operations. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics. Business intelligence technologies can handle large amounts of structured and sometimes unstructured data to help identify, develop, and otherwise create new strategic business opportunities. They aim to allow for the easy interpretation of these big data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability. Business Intelligence works mostly performed by BI softwares; Business intelligence software is a type of application software designed to retrieve, analyze, transform and report data for business intelligence. The applications generally read data that has been previously stored, often though not necessarily in a data warehouse or data mart.
What You Should Know About Business Intelligence Software
Implementing analytics software has been a major initiative for
companies undergoing digital transformation, and the main subsection of
analytics tools deployed in companies are business intelligence
tools. These tools help to provide visibility into a company’s data.
By being able to visualize and understand business data, employees can
make more informed decisions and impact the company in a positive way.
With the amount of data accessible to businesses today, it is a near
necessity that they implement some type of software to better
understand and act on that data. Here some key Benefits of Business Intelligence Software:
- Easily visualize and understand company data
- Connect all company data sources into a single platform to make cross-department connections
- Encourage data-driven decision making for business optimization
- Discover new insights that can enhance the bottom line
Why Use Business Intelligence Software?
In today’s big data world, every company is sitting on an enormous
amount of data. Inside lies insights that can make or break company
processes and performance. The question should not be why use business
intelligence software, but why not use business intelligence software?
There are seemingly infinite insights a business can pull from their
data, but here are three important reasons to use business intelligence
software.
- Data-Driven Decision-Making: A key component to
digital transformation is to become a data-driven organization. By using
data to drive every decision the business makes, the company can
optimize and achieve its fullest potential. This concept should be
instilled within every employee in the company, not just a few
leadership members who make high-level decisions. Instead, companies
should be leveraging analytics and business intelligence tools to
understand all aspects of the business, including hiring forecasts,
which marketing campaign should be used to target certain demographics,
which sales prospects to target first, supply chain optimization, and
many others. Each of these business aspects and the decisions made
around them should first be vetted by using data and business
intelligence software. Every manager and leader should be asking what
data was used to determine each decision.
- Measure and Understand Company Performance: Another
main reason that businesses adopt business intelligence tools is for
tracking and measurement of company goals. Data visualization tools are
frequently used to track company key performance indicators in real
time. Business intelligence platforms and self-service business
intelligence software can be used to then determine why the business is
either exceeding or falling short of those important company metrics. By
developing a keen understanding of why the business is performing the
way it is, adjustment and pivots can be made quickly and easily. So if a
team is falling short of a goal, they can make up for it and get back
on track. It is one thing to simply know where your sales numbers are or
how your web traffic is performing, but it is another to dig into the
reasons behind it and adapt based on what is successful and what is not.
- Discover New Actionable Insights: BI tools combine
data from a variety of sources, including accounting and enterprise
resource planning (ERP) software, CRMs, marketing automation tools, and
others. Data analysts can use this integrated data to find correlations
between different departments and the actions they are taking to
discover previously hidden insights. It’s possible that certain sales
tactics are impacting the numbers for one specific product differently
than they are for another. Analysts can discover this by comparing the
list of closed accounts from their company CRM with products shipped in
their ERP system. Because teams are generally siloed and using disparate
software, these insights have traditionally been much more difficult to
discover. However, by using business intelligence software properly,
companies are at an advantage they never had in the past.
Who Uses Business Intelligence Software?
In a data-driven organization, business intelligence (BI) tools
should be adopted by a variety of departments for a wide range of
purposes. BI software is most frequently used by data analysts and data
scientists, but self-service BI tools, which are much easier for the
average end user to adopt, can be used by sales, marketing, and
operations teams. In reality, nearly every employee should be using
analytics solutions at some point to truly become a data-driven company.
While there are point solutions that provide analytics for very
specific departmental purposes, such as marketing analytics software, sales analytics software, and HR analytics software among others, BI tools can offer the same functionality on a much broader level and allow for cross-departmental insights.
- Data Analysts and Data Scientists: The main users
of BI tools are data teams consisting of data analysts and data
scientists. These employees are generally the power users of analytics
tools, creating complex queries inside BI platforms to gather a deeper
understanding of business critical data. These teams may also be tasked
with building self-service dashboards to distribute to other teams. In
smaller companies, these employees are most likely tasked with providing
all data requests and working closely with the sales, marketing, and
operations teams to help offer insights and optimize processes.
- Sales Teams: Sales teams can use both self-service
business intelligence tools and embedded business intelligence
solutions to find insights into prospective accounts, sales performance,
and pipeline forecasting, among many other use cases. Generally, the
sales team members that use analytics on a daily basis are sales
operations managers or sales data analysts. However, they are extremely
useful for both sales managers and representatives. Managers can help
keep tabs on the performance of each representative and maintain a clear
picture of the potential pipeline. Additionally, sales teams can use
data visualization software to track year-long goals and quotas to give
the entire company visibility into high-level sales numbers. Ultimately,
using BI tools in a sales team can help businesses optimize their sales
processes to ensure they are bringing in the most revenue possible.
- Marketing Teams: Marketing teams are constantly
running different campaigns, whether they are email, digital
advertising, or even billboard campaigns. BI tools are a great way for
teams to track the performance of those campaigns in one central
location. Data visualization solutions are a great way for marketing
teams to track campaigns in real time, and by measuring the performance
of each effort, teams can plan for future campaigns and forecast how
much revenue they can attribute to said efforts. BI platforms can allow
analysts to dig deeper into marketing efforts by segmenting customers
based on a range of demographics to really understand which campaigns
resonate with which segment of their customer base. This can help the
marketing team make a targeted effort moving forward. Similarly to sales
use cases, marketing teams can utilize BI software to help improve
their bottom line and provide transparency and visibility into their
overall performance.
- Finance Teams: Accounting teams generally stick to
the tools they are familiar with for budgeting and forecasting, but by
blending financial data with sales, marketing, and other operations
data, users can pull actionable insights that they were unable to see
before. They can find these insights by using BI platforms to get an
understanding about which factors impact the bottom line. Additionally,
they can determine the right and wrong places to spend money. For
example, if a specific advertising campaign was the cause for a revenue
spike, then that was money well spent. If a specific product is yielding
less profit than others based on the effort of the sales team, then
finance teams can inform their sales leaders and adjust accordingly. The
beauty of BI tools is that it does not just give insights into
financial records, like accounting or corporate performance management
software; instead it gives actionable insights into how all the other
business factors impact profit and loss.
- Operations and Supply Chain Teams: One potential
data source for BI solutions is a company’s enterprise resource planning
(ERP) system. These applications track everything from accounting to
supply chain and distribution. By inputting supply chain data into a BI
platform, supply chain managers can optimize a number of processes to
save time and resources. For example, businesses can optimize inventory
to ensure that they are not over- or underproducing. With location
intelligence software, companies can determine the best location for
their next warehouse. BI platforms can help optimize distribution routes
and ensure service-level agreements (SLAs) are hit on time.
Additionally, data visualization software can help warehouse workers
track their daily goals to ensure all operations are running smoothly.
All of these optimizations can help businesses stay on track and achieve
higher company-wide goals.
What Kinds of Business Intelligence Software you should use
There are a number of different types of business intelligence solutions that have overlapping functionality but ultimately cater to a
different user or provide unique services.
- Business Intelligence Platforms: The most common
type of tools are business intelligence platforms. BI platforms are
comprehensive analytics tools that are used by data analysts and
scientists. They often require a certain level of coding or data
preparation knowledge. These solutions connect to databases, data
warehouses, or big data distributions and offer analysts the ability to
tinker with data to discover insights. Some platforms offer advanced
analytics features, such as predictive analytics, big data analytics,
and the ability to ingest unstructured data. Additionally, BI platforms
may offer self-service functionality so that basic business users can
use the tool, but at the core they are to be used by data and IT teams.
- Self-Service Business Intelligence Software: For
companies interested in promoting a data-driven culture, self-service
business intelligence software is critical. Self-service business
intelligence tools do not require coding knowledge, so business end
users can take advantage of them. These solutions often provide
drag-and-drop functionality for building dashboards, prebuilt templates
for querying data, and maybe even natural language querying for data
discovery. Similarly to BI platforms, these tools are used to build
interactive dashboards for discovering actionable insights. This allows
users like sales representatives, human resource managers, marketers,
and other non-data team members to make data-driven decisions. This
saves time for the user, administrator, and data team.
- Embedded Business Intelligence Software: Some
software may offer the ability to embed analytics functionality inside
of other business applications. Often, these are the same vendors that
offer BI platforms and self-service business intelligence software. They
sell their proprietary business intelligence solutions by allowing
developers to embed the technology inside other applications. Businesses
may choose an embedded business intelligence product to promote user
adoption. By placing the analytics inside regularly used software,
companies can help to ensure employees are taking advantage of available
data. These solutions provide self-service functionality so that
average business end users can take advantage of data for improved
decision making.
- Data Visualization Software: If a business is
interested in simply tracking key performance indicators (KPIs) and
other important metrics, they may opt to use a data visualization
software. These products allow users to build dashboards to track
company goals and metrics in real time. However, they do not allow users
to drill down into the data to discover deeper insights. By
understanding where a business or team sits with certain company goals
and KPIs, they can make efforts in specific areas to achieve said goals.
These solutions allow for multiple KPI dashboards, so each team can set
up visualizations for their own goals. These tools can consume data
from a variety of sources, just like all other business intelligence
tools, such as databases and business applications.
- Location Intelligence Software: Often called
spatial intelligence, location intelligence software is a subset of
business analytics that provides insights based on map and spatial data.
These tools help users determine relationships between the physical
location of objects. In the same way a user can find patterns in
financial or sales data with a BI platform, data analysts can use
location intelligence tools to determine the ideal spot to open their
next restaurant or place their next warehouse. These tools are often
used separately from a business intelligence tool or even integrate with
existing analytics tools.
- Big Data Analytics Software: Big data analytics software
have similar functionality to business intelligence platforms. However,
they can consume large, unstructured data sets from big data clusters.
These products require a good deal of technical knowledge to query the
data from the file systems the data is stored within. These products
connect to Hadoop or proprietary Hadoop distributions. They still offer
analysts the ability to visualize and drill into data to pull out
actionable insights.
- Text Analysis Software: Text analysis software
allows users to visualize data from unstructured text data sets. These
tools often use natural language processing to pull out sentiment
analysis, syntax parsing, part-of-speech tagging, and entity
classification. These tools are often used by data teams and analysts.
They can be used to gain insights from emails and phone transcripts,
social media posts, or just general documents.
- Predictive Analytics Software: Data scientists and machine learning developers may require predictive analytics software.
These solutions allow users to perform data mining on historical data
to determine future outcomes. With predictive analytics tools, analysts
can build models and algorithms that use patterns and trends from past
data to plan for future possibilities. These solutions are critical when
forecasting, identifying potential risks, or finding unseen
opportunities within the business.
- Data Warehouse Software: Most companies have a
large number of disparate data sources, so to best integrate all the
data, they implement a data warehouse. Data warehouses can house data
from multiple databases and business applications, which allows business
intelligence tools to pull all company data from a single repository.
This organization is critical to the quality of the data that is
ingested by analytics software.
- Data Preparation Software: Another key solution
necessary for easy data analysis is a data preparation tool. These
solutions allow users to discover, combine, clean, and enrich data for
simple analysis. Data preparation tools are often used by IT or data
analysts tasked with using business intelligence tools. Some business
intelligence platforms offer data preparation features, but businesses
with a wide range of data sources often opt for a dedicated preparation
tool.
