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1. ENTERPRISE and
DEPARTMENTAL
BUSINESS INTELLIGENCE

2. ENTERPRISE BUSINESS
INTELLIGENCE
• What is enterprise business intelligence?
• Business intelligence encompasses all the processes and
methods of collecting, storing, and analyzing data from
business operations to provide a comprehensive view of a
business. The most basic enterprise business intelligence
definition is the deployment of BI throughout a large
corporation. Larger, more complex companies create more data
and require more extensive and sophisticated business
intelligence platforms. Enterprise BI helps these organizations
increase productivity and efficiency.

3. • What are the Elements of Enterprise Business Intelligence
 Data cleaning – The process involves discovering duplicate content, handling missing values,
normalizing data formats, administering inconsistencies and validating data for its precision. Data
cleaning improves the readability and integrity of data, making it ready for analysis.
 Reporting and exploration – The process focuses on deriving insights from data. It involves the
creation of structured reports, charts and visualizations comprising key metrics from data
analysis. Meanwhile, the exploration process requires digging deeper into data with ad-hoc
querying, data discovery functions and exploring data from multiple angles to uncover hidden
information, leading to new opportunities or detecting existing anomalies.
 Dashboards – Dashboards are the visual representation of real-time or near-real-time business
metrics and KPIs consolidated in an easily understandable format for users. They serve as a key
to interpreting complex data, identifying patterns, enhancing transparency and improving
decision-making.
 Predictive analytics – AI/ML and statistical algorithms help analyze historical data, extract
patterns and identify correlations to predict future outcomes. It enables businesses to move
beyond the capabilities of descriptive and diagnostic analytics and embrace a proactive approach
to stay ahead of the market.

4. • Benefits of an Enterprise Business Intelligence Platform
 Quick decision-making – Enterprise BI helps leaders quickly figure out what’s going on in their organization. It
collates all the enterprise-wide data, such as sales data, customer data, market trends and much more, and
presents it as stories using compelling visualizations. Due to this, businesses can easily grasp the insights and make
informed decisions.
 Gain a competitive edge – Enterprise BI turns complex data into an understandable format that enables users
across different departments to spot trends, identify market trends, understand customer behavior and uncover
hidden opportunities. It helps predict future outcomes and empowers every business user to make data-driven
decisions, boosting efficiency and leading companies to stay ahead of their competitors.
 Improved customer satisfaction – With a 360-degree view of their customers, businesses can identify customers’
shopping patterns, cater to their feedback and complaints, and address them as soon as possible, improving service
quality. The insights can help businesses personalize offers and interactions, predict their needs, plan marketing
campaigns and build loyal relationships with them.
 Increased revenue – Using Enterprise BI, businesses can leverage historical as well as real-time data to gather
insights on how to optimize operations, enhance customer experiences and predict their needs. They can also
leverage data-driven insights to identify sales patterns, target high-value prospects, improve lead generation and
increase customer retention while reducing costs and minimizing risks.
 Boosts productivity – Productivity for businesses refers to streamlining operations and empowering teams with
intelligent insights. Enterprise BI consolidates enterprise-wide data and automates report generation, reducing the
time spent on manual data collection and analysis. It provides a holistic view of data and empowers users across
teams to access it to gain insights, reducing inconsistencies.

5. Industry Examples of Enterprise Business Intelligence Platform
 Financial planning & analysis – Enterprise BI enhances financial intelligence by enabling business users to explore
data independently, perform ad hoc analysis and generate insights without depending on IT. It handles
multidimensional, hierarchical and complex data, saving time and effort for FP&A teams. FP&A teams can drill down
to a granular level of detail and generate reports instantly and effortlessly.
 Retail analysis – With enterprise BI, business users can analyze sales, marketing and customer service data across
multiple channels and get detailed analyses on demand prediction. By leveraging these insights, users can
customize product recommendations based on various factors such as sales, demand, weather and festivals.
 Risk analysis – Enterprise BI analyzes historical data and current trends to identify anomalies and potential risks
while anticipating their impact and empowering businesses to take preventative steps. Moreover, enterprise BI also
helps in adhering to regulatory standards to safeguard businesses from potential threats.
 Customer behavior analysis – Enterprise BI provides a holistic view of customer experiences and insights that can
help understand the buying patterns of millions of customers. By leveraging insights from historical data, businesses
can make exciting offers to relevant loyal customers to improve upsell and cross-sell, enhance outreach strategies,
and enhance experiences.
 Supply chain analysis – Businesses can closely monitor product inventory, warehouses, store performances and
supplier responses by leveraging insights gained from enterprise BI. Businesses can monitor supplier activities
across various parameters and use these insights to maintain vendor networks and customize supply chains.

7. Capabilities Of Enterprise Business
Intelligence Platforms
• The breadth of BI technology can make choosing an enterprise
business intelligence platform a complicated endeavor. As your
organization seeks to collect and analyze bigger and more complex
data
• Collaboration
• Analytics
• Infrastructure
• Governance
• Visualization

8. • Collaboration
• With a larger organization, you need a corporate BI solution that
works seamlessly between users and departments. The
platform should also provide a straightforward way to publish,
distribute, and share insights—even with outside clients. And it
should be able to do all of this securely, without compromising
your data.
Analytics
• The best enterprise business intelligence platforms give you the
ability to ask and answer questions immediately for on-the-fly
decision making. They also help power insights with advanced
analytics and statistics. Not only do you get a strategic, top-view
look at the data, but you can also dig into the granular details.

9. • Infrastructure
• Choose a corporate BI platform that’s genuinely self-service
and doesn’t require the IT team to help with every inquiry. Look
for customizable dashboards, tools to organize resources,
revision history, and search functions, so it’s easy for everyone
to find the right data every time.
• Governance
• Governance is an essential capability for enterprise BI
platforms. A centralized data source can help maximize
reusability, reliability, and consistency, helping you to regulate
reporting and provide more accurate analyses. The platform
must also keep proprietary data and analytics secure while
providing the right access to authorized users.

10. • Visualization
• An interactive, easy-to-use visual interface is key to adoption
across departments and management levels. But make sure the
platform can create more than just pie charts and bar graphs. It
should also have the capabilities to provide the heat maps,
scatter plots, and other data visualization methods needed for
your organization.
Finally, your corporate BI platform should integrate seamlessly
into your existing data structure and give you the flexibility to
connect to all your data on-premises or in the cloud. You should
also be able to access your data from any device or operating
system, whether that’s desktop or mobile, Windows or Mac.

11. • Enterprise Business Intelligence (BI):
 Scope: Enterprise BI involves the use of BI tools and systems across the
entire organization. It aims to provide a comprehensive view of the
organization's data, allowing for strategic decision-making at the top
levels of management.
 Tools: Enterprise BI tools are typically robust and scalable, capable of
handling large volumes of data from various sources. Examples include
enterprise data warehouses, big data platforms, and advanced analytics
tools.
 Strategies: The strategies for enterprise BI focus on aligning BI initiatives
with organizational goals, ensuring data governance and quality, and
fostering a data-driven culture throughout the organization.

12. • Departmental Business Intelligence:
 Scope: Departmental BI is more focused and tailored to the specific needs
of individual departments or teams within the organization. It may involve
creating custom reports, dashboards, or data visualizations to address
department-specific challenges.
 Tools: Departmental BI tools can vary widely depending on the
department's needs. They may include self-service BI tools, specialized
analytics software, or even spreadsheets for smaller teams.
 Strategies: Departmental BI strategies often revolve around empowering
users with self-service BI capabilities, promoting data literacy within the
department, and integrating departmental BI initiatives with the broader
enterprise BI strategy.

18. • Strategic Business Intelligence (BI):
1. Focus: Focuses on long-term planning and decision-making.
2. Data Analysis: Involves analyzing historical and current data to identify trends and make predictions.
3. Tools: Uses advanced analytics, data mining, and data visualization tools.
4. Usage: Used by top-level executives to set long-term goals and strategies.
5. Examples: Market trends analysis, competitive intelligence, long-term forecasting.
• Tactical Business Intelligence (BI):
1. Focus: Focuses on short-term, day-to-day operations and decision-making.
2. Data Analysis: Involves analyzing real-time or recent data to monitor performance and make immediate adjustments.
3. Tools: Often uses operational reporting, ad-hoc queries, and dashboarding tools.
4. Usage: Used by middle managers and operational staff to monitor KPIs and make short-term decisions.
5. Examples: Sales performance tracking, inventory management, customer service metrics.