With projected revenues of around US $203 billion by 2020, big data and business analytics are here to stay.  

The human race currently produces over 2.5 quintillion data bytes each day. Almost all devices currently manufactured come equipped with the ability to connect to the internet. Mobile internet connectivity is expanding rapidly all over the world. The already mind-boggling amount of data produced only continues to rise steadily upward.

Companies and businesses across the globe understand the power of harnessing data to increase revenue regardless of size, scale, or industry. Sufficient access to relevant data is just the first step a company can take. At Zuar, we want to help you remain competitive in the digital age with our data analytics and insight. To start, here’s our guide to the ins and outs of business intelligence.

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Business Intelligence Defined

Corporate analysts discussing business intelligence

Business Intelligence is the technology-driven process of acquiring data, data warehousing, business analytics, data visualization, and the attached infrastructure, tools, methodologies, and applications. The end result of business intelligence is to provide management with actionable insights.

The insights gained through analysis can be leveraged by organizations to make data-driven decisions, and in turn, increase profitability and decrease liabilities.

Richard Millar Devens created the concept in his publication, Cyclopædia of Commercial and Business Anecdotes. Published in 1865, it describes a banker who profited by utilizing information about the environment and his competitors.

It was Howard Dresner, however, who proposed using the term ‘business intelligence’ as an umbrella term to describe "concepts and methods to improve business decision making by using fact-based support systems."

Get started with Zuar's business intelligence platform to improve your decision making processes.

To find out more, check out our ongoing series about implementing Embedded Analytics.

The Importance of Business Intelligence

The main reason that business intelligence is vital for companies is that it can help them make better, data-driven decisions by looking at historical and present data within their business context. Analysts leverage business intelligence to allow organizations to run more efficiently and smoothly by providing benchmarks for performance. The right data, used effectively, can help businesses with everyday operations, hiring efforts, compliance, and more.

Business intelligence helps companies make these decisions by providing them with ways to:

  • Identify how to increase profits
  • Compare data to competitors
  • Optimize operations
  • Identify market trends
  • Analyze customer behavior
  • Track and measure performance
  • Discover problems in processes

Business Intelligence Strategy

Previously, business intelligence applications were typically managed by IT professionals. However, business intelligence tools have evolved to be user-friendly and more intuitive, allowing users across disciplines to utilize them. These days, business intelligence is split into two types: traditional and modern. Traditional business intelligence is where IT professionals make use of in-house data to create reports. Modern business intelligence is where people within the company interact with intuitive and agile systems to analyze data quickly.

For some reporting, like financial and regulatory reports, traditional business intelligence methods still shine because 100% accuracy is essential, and the data sets that get used are predictable and standard. Modern business intelligence tools get used when an organization needs quick insights into a changing dynamic, like for marketing events, where speed is valued and a margin for error is acceptable.

While a business intelligence strategy is essential for organizations to make effective business decisions, many of them have a difficult time implementing these strategies due to tactical mistakes, poor data practices, etc. Zuar simplifies and streamlines business intelligence practices to give companies the tools they need to make data-driven decisions.

Example of Business Intelligence

Reporting is a primary aspect of business intelligence, and dashboards (hosted software applications that compile available data into graphs and charts to show the immediate state of a company) are one of the main business intelligence tools. Business intelligence doesn’t tell its users what to do or what can happen if they take certain actions, but it’s also not only about generating reports. It offers users a way to examine data and derive insights by streamlining, searching, and merging data, and querying the data to make efficient business decisions.

For example, an organization that wants to manage its supply chain more efficiently can use business intelligence capabilities to determine where variabilities exist in the shipping process and where delays are happening. They can also use business intelligence to find out which products or modes of transportation have the most issues throughout the process.

The use cases go even further than typical business performance, though. For example, the school system in Columbus, OH uses business intelligence solutions to examine data like attendance and performance to improve their student’s learning and graduation rates.

What is Data Staging?

Pair of glasses in front of data visualization.

Before you learn what data staging is, you have to know the definition of ETL. The ETL process, or extract, transform, and load process, is the process of copying data from multiple sources to a single destination source.

Data warehouses, or enterprise data warehouses, are makeshift central repositories that house data on its journey between source and its final destination. These systems, called data staging areas, are the core components of business intelligence.

Data warehouses receive data from disparate sources like operational systems and sales data. The data updates regularly and serves as a central system for every worker in the enterprise to tap into. The chain of business intelligence starts with acquiring relevant data, and data warehouses are the place to go.

They maintain data history and improve the quality of data by providing relevant descriptions, data integration, summarization, and data restructuring. Data mining is impossible without data warehouses; not only do they store and update information daily, but they maintain historical records spanning up to 10 years.

What is the Data Value Chain?

The data value chain is the series of steps within a big data system required to obtain actionable insight. It is a conceptual framework that covers the end-to-end journey of data analysis. They are decision support tools used to plan and control the chain of activities required to achieve the desired results.

Data Value Chain Diagram

The main high-level activities are data acquisition, data analysis, data curation, data storage, and data usage. This structured approach helps the decision-making process by breaking down the business intelligence process into smaller actionable tasks.

The advent of this framework system led to a collectivized approach to business intelligence.

Business Intelligence vs. Analytics

Female business analyst working from laptop

Business intelligence provides insights into the current state of an organization. For example, it can show you how many prospects are in your sales pipeline right now or how many users you’ve lost or gained this week. This is important to keep in mind when distinguishing business intelligence from business analytics.

Business intelligence is descriptive; it tells you what’s going on right now and what happened in the past to bring the organization to its current state. Business analytics is an umbrella term encompassing predictive data analysis techniques. They help you predict what will happen in the organization’s future and what the company can do to create better outcomes.

The difference between business intelligence’s descriptive powers and business analytic’s predictive powers goes a little bit deeper than just this timeframe. It also gets into the question of “who is business intelligence for?”. While business intelligence describes a business’s current state of affairs, and business analytics gives advice based on analyzing and interpreting data, there’s still one big goal that needs to be achieved. Business intelligence and analytics should be relatively easy for non-technical end users to utilize and understand and allow them to dive right into the data and make new reports. That’s why Zuar focuses on shortening the learning curve so that any organization can jump right into analyzing data, creating reports, and making better business decisions.

How Business Intelligence and Analytics Work Together

Business intelligence includes both data and business analytics, but those are only used as pieces of the whole process. Business intelligence helps users to draw a conclusion for data analysis. Data scientists look into data specifics and use predictive analytics and advanced statistics to find current and past patterns to forecast future ones. Data analytics helps answer why certain things happened and can be used to predict what will happen next. Business intelligence takes those algorithms and turns the results into something more actionable.

Business analytics is a part of the larger business intelligence strategy for organizations. It answers specific questions and provides analysis for planning and decision-making at a glance. However, businesses can still continue to use the analytics process to improve iterations and follow-ups continually. Business analytics is not a linear process; answering one question leads to more questions and iterations. The process is more like a cycle of data discovery, access, exploration, and information sharing. We call this the cycle of analytics -- a term that explains how businesses use these analytics to react to ever-changing questions and expectations.

Business intelligence tools originally took a top-down approach that was driven by IT organizations where most analytics questions were answered through the use of static reports. When that was the case, any follow-up questions would end up on the bottom of the reporting queue; the process would have to start from the beginning again. Those methods led to slow and frustrating reporting cycles, and it was difficult to leverage the data to make informed decisions. Now, we have more modern business intelligence tools that are interactive and approachable. IT departments are still a crucial part of managing this data, but more levels of users can create accurate reports on short notice. With the right business intelligence software, users can visualize data, create their own reports, and answer their own questions. Zuar's Mitto and Portal solutions are a great example of this.

Get started with business intelligence at Zuar, utilizing our data strategists’ capabilities and advanced insight tools to improve your bottom line. Request a free data strategy assessment.

Check out these tips and tricks for business intelligence optimization.