Business intelligence (BI): What it means, why it matters, and best practices

What is business intelligence?

Business intelligence (BI) is the combination of applications, processes, and infrastructure that, as Gartner explains 1, “enables access to and analysis of information to improve and optimize decisions and performance”. From expense management to supply chain visibility, sales pipeline management and beyond, modern BI tools are focused on extending the value of data across departments, roles, and increasingly, the ecosystem of partnerships that enable organizations to effectively operate and compete in today’s fast-paced business climate.

The history and evolution of BI

The emergence of business intelligence can be traced to the decision support systems of the 1960s, evolving in three major waves of innovation over the decades. The challenge is always the same: How can businesses analyze data to make discoveries that lead to competitive edge? Each generation has come a little closer to that promise but it’s the third generation of BI we are now entering that holds the greatest potential to spread the value of BI to every business user and unlock all the value in data:

The history and evolution of business intelligence: 1. centralized data queries, 2. decentralized user-driven BI, and 3. democratized data access and analysis.

1st Generation BI – Centralized:

In the early days of BI, if a person wanted to learn something from data, they had to submit a question to a data analyst with the skills to create a query or use a complex technology stack that analyzed multi-dimensional data sets (OLAP data cubes 2). Often weeks later, they’d get a report that could be out-of-date or raised further questions. This inefficient “Ask > Wait > Answer” cycle limited BI’s value, while reaching only 25% of business users with static information.

2nd Generation BI – Decentralized:

The next wave of BI, pioneered by Qlik, introduced user-driven BI. This replaced the complex technical stack with more agile methods to prepare and load data, and intuitive ways to visualize and explore that data. Business analysts could create analytics apps for key processes, delivering interactive BI dashboards to everyday users. Eventually even more lightweight data visualization tools came to market, and while BI could now reach between 25-50% of employees, most of these visualization tools lacked governance. Because these tools focus on content authoring, low data literacy rates limited user adoption and led to the use of untrustworthy data sources.

3rd Generation BI – Democratized:

BI is entering its next phase, driven by new approaches to how we manage data, deploy analytics and improve data literacy. Trusted data is accessible to all users through governed data catalogs. Augmented intelligence (AI) accelerates discoveries and increases data literacy by suggesting insights, automating processes, and providing conversational, natural language interaction. And embedded analytics brings BI to the applications and processes that people and machines (IoT analytics) interact with daily. These innovations are enabling organizations to reach the 50-75% of employees not yet using BI, offering a huge potential increase in value from data.

Key Capabilities of Modern Business Intelligence Tools

The intense pace of change is prompting organizations of all types to reinvent how they do business. As demand for data driven insights rapidly increases, businesses that can execute a pervasive, modern approach to BI are best positioned to lead in their industry. Here are the key capabilities to look for when evaluating modern BI tools.

Data integration and management

The most successful business intelligence initiatives combine a smart analytics strategy with an effective data strategy. Raw data only gains value when it can be transformed into highly accessible, analytics-ready information.

This often begins by moving source data (ERP, CRM, etc.) into a central repository like a data lake or data warehouse. Data connectors in the analytics system load data from these repositories as well as specific applications and files so it can be prepared for use. This can be slow and tedious, requiring data experts which can create bottlenecks at scale. However, innovative data replication and data migration technologies can automate the integration process. In addition, Governed data catalogs that profile and document every data source let business users easily access, create, and share data sets on their own, combining any data they need to analyze.

Data replication and data migration automates moving source data into a data warehouse.

“By 2020, businesses that give users access to a curated catalog of internal and external data will gain twice as much value from analytics investments.”3

Modern Business Intelligence and Analytics Technologies

At the core of the best modern business intelligence software is a next-generation data analytics engine that enables users to explore data freely while performing ultra-fast analytics calculations that remove the limits of query-based technologies which many BI tools rely on. Other key BI technologies that enable a modern approach to analytics include:

Data visualization

The ability to explore and interact with data makes it easier for users to explore, discover patterns, and gain insights from data. Smart visualizations make data even more actionable, revealing the shape of the data, highlighting outliers and trends, and putting data in the ideal context to answer any question.

Search and interactive selections

The best BI platforms let users freely explore data using text search and interactive selections to filter within charts, tables and other elements. This is most effective with technologies that map every data association, keeping all elements in the current context as a user interacts while revealing related and unrelated values to guide analysis.

Augmented Analytics

AI and machine learning are quickly becoming an essential facet of BI, quickly processing massive volumes of data to suggest relevant insights and automate processes while letting users interact conversationally. This augments human intelligence and increases data literacy so more users can get value from business intelligence.

Open APIs and extensibility

Organizations face an ever-growing array of specific business intelligence needs and uses cases. An open platform that supports the ability to create custom applications and extensions, integrate with other technologies, and embed analytics in existing business applications processes is essential to maximize the value BI.

Collaboration and sharing

Modern BI tools offer users the ability to easily create and share data sets, analytics, and insights across an organization. The most effective BI ecosystems offer a governed, centralized hub to facilitate this collaborative process and equip users with robust interactive data storytelling capabilities to circulate their discoveries.

Governance, security and flexible deployment

Today, demand for business intelligence comes from the C-suite to the edge of every organization. Reaching this scale requires governed control, trusted security and the ability to deploy and scale analytics with any combination of infrastructure from on-premise to the most modern cloud environments.

BI Applications Across the Enterprise

From self-service BI and dashboards to mobile BI and conversational analytics, the most effective modern business intelligence software supports a wide range of business needs and users, allowing every employee to access the insights they need, regardless of technical skill. Here are the main ways organizations use business intelligence tools to get more from their data.

“By 2021, conversational analytics and natural language processing will increase BI adoption from 35% of employees to more than 50%.”3

How do organizations use business intelligence?

Organizations in every industry are using business intelligence to empower their employees with insights that drive better decision-making and business performance. Here are some key BI strategies frequently used across major departments in an organization:

Finance teams optimize expense management, enhance forecasting, budgeting and planning, and better manage revenue, risk and compliance.

Sales teams discover market trends and sales opportunities, measure sales performance and forecast pipeline.

Supply chain management teams make better decisions in forecasting and planning, sourcing and supplier performance, and transportation.

HR teams increase operational efficiency by analyzing labor, benefit and recruitment data holistically across their organization.

IT teams optimize data governance, security and scalability while lowering costs by spotting underused systems and applications.

Marketing teams improve ROI through better customer segmentation, targeting and campaign analysis and predicting the performance of new business initiatives.

What are the major benefits of BI?

According to BARC’s BI Survey, the top benefits of business intelligence software are faster and more accurate planning, analysis and reporting, better business decisions and improved data quality. But how do these translate to real business value? With the right business intelligence platform and strategy, here are four major ways BI can deliver value and drive digital transformation within organizations:

  • 1. Reinvent business processes, optimizing business performance

  • 2. Understand customers to deepen loyalty and increase lifetime value

  • 3. Uncover unexpected new sources of revenue

  • 4. Better balance risk with reward across business operations

What are BI best practices?

Build Data Literacy with Training and Tools

Organizations with higher data literacy rates have greater enterprise value. But only 24 percent of all workers say they can read, work with, analyze and argue with data. Close the literacy gap by giving employees access to BI tools that are easy to learn and use, build confidence, increase adoption and empower every user.

Ensure Flexible Deployment and Scalable Architecture

Scale and deploy business analytics to every corner of the organization with the help of a multi-cloud architecture. This gives users the ability to access and share data insights between on-premise and cloud deployments while keeping governance and trust standards high.

Centralize BI Governance, Security and Management

Keep data and analytics secure through a model that lets administrators set rules based on users, actions and resources. Ensure that everyone is working with the same, accurate data by implementing governed, centralized libraries of data, analytics and measures.

Extend the Value of Your BI Investment

Companies using embedded analytics are 89 percent more likely to see higher operating profits of 10 percent or more. Ensure your BI platform gives employees access to data insights in their everyday applications.

Transform your business with a new generation of BI technology.

Business intelligence is most effective when you combine an agile data strategy with a modern analytics strategy. Only Qlik offers end-to-end, real-time data integration and analytics solutions.

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Qlik Sense BI platform offers a unique associative analytics engine, sophisticated AI, and scalable multi-cloud architecture.

Uncover bolder insights with world-class analytics.

Qlik Sense sets the benchmark for a new generation of data analytics. With its one-of-a-kind associative analytics engine, sophisticated AI, and scalable multi-cloud architecture, Qlik is built to empower people at all levels of your organization to make bigger discoveries and better decisions every day.

Learn more about business intelligence and analytics.

References

1. “Analytics and Business Intelligence (ABI)” Gartner Glossary, Gartner Inc., retrieved 20 Aug. 2019

2. “OLAP Cube.” Wikipedia, Wikimedia Foundation, 18 Sept. 2019

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