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Let’s play a quick game of “Would You Rather.” Would you manually pull 6,000 rows of data into a spreadsheet to guide your next business strategy or would the software do it for you?
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If you prefer the former, you may be a data scientist (or a masochist). If you’re anything like me, you tend to look at unstructured data and often see a structured report or a series of data visualizations. Either way – we both need business knowledge.
Can You Start A Bi Career Without A Business Intelligence Degree?
So what is business intelligence, and how can you use it to make business decisions easier? In this guide, I unpack why you should implement a business intelligence strategy and what it can do.
Business Intelligence (BI) refers to the processes and tools used to collect, manage and analyze data to determine how a business is doing and how it can improve from there.
Don’t worry—BI doesn’t mean your job as a business executive or data analyst is being taken over by robots. Organizing data into reports is only half the battle. Your job is to extract insights from that data and make sound, human decisions. BI simply automates the otherwise difficult process of data extraction and analysis, making your job much easier and more effective.
Think of business intelligence as your company’s data whisperer—it takes the loud cacophony of raw numbers and smooths them into a symphony of actionable insights. Just… slightly less charming. Let’s break it down—nothing magical but a really practical process:
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Typically, data science experts will interpret the results of business data analytics before BI makes the language less technical. Essentially, BI facilitates insights from data analytics to simplify business terminology.
Think of it as the difference between a study done on a technical health topic and an article published about the study. The study’s findings may sound like a foreign language, but the article describes its implications and provides recommendations for readers to take home.
Let’s assume that you are not happy about the possibility of manual data analysis and interpretation of results. Here are some reasons BI can make your system work better.
The uses of BI are practically limitless. The first step to implementing it is deciding what business goal you want to achieve. Do you want to compare the performance of your sales channels, use data from past marketing campaigns to inform your next one, or create a new HR dashboard with employee usage data?
Can Business Analysts Transition To Business Intelligence Consulting?
For many uses of BI, you can completely rely on internal data, but some problems require external data. For example, you may want to consider data published in a business journal when implementing BI.
Example: The same clothing company could collect additional data from customers based on their buying patterns to identify what styles they like and better market those styles to them.
Once all of your data sources are gathered, you’re ready to choose tools to transform, analyze, and learn from the data. The platform(s) you use for BI will depend on your goals, which is why it’s important to determine them in Step 1.
Example: A textile company can use a BI solution with powerful analytics capabilities to understand what customer data means about their interests and buying habits.
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Leave it to robots to identify patterns and make predictions from data. Most BI tools are designed to perform descriptive and predictive analytics, which can shed light on where your business stands. For example, your BI platform can look at employee turnover history and predict which departments need the most aggressive recruiting efforts and when.
Example: A clothing company’s BI software may recognize that customers are consistently returning a certain type of romper due to fit problems, suggesting that the company should reevaluate the product’s design.
We’ve established that (almost) everyone prefers a colorful chart, graph, or map to a large spreadsheet of data. Data visualizations are especially useful when sharing results with the entire team—they’re easy to digest and therefore better for motivating action toward goals.
Example: A clothing company might use a BI-generated chart to determine how much profit it could increase by better targeting customers with personalized marketing efforts.
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BI tools help show you where action can be taken, but they can’t take action for you. Develop short- and long-term strategies based on your findings to address your problem areas, whether they are internal inefficiencies, supply/demand issues, or lack of customer service.
Example: A clothing company may initially eliminate generally unpopular styles while gathering more customer data, then proceed to adjust its marketing strategy a few months down the line.
In addition to choosing a BI tool that meets your unique needs, make sure that whatever solution you choose includes the following features:
Once you’ve implemented business intelligence software, automate it so you can spend time delighting your customers instead of racking your brain over spreadsheets.
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Here are a few quick-fire questions, so you don’t have to search for 2,000-some words about whether you need a PhD in data science to use business intelligence effectively (you don’t):
The main goal of business intelligence is to turn data into actionable insights. By analyzing raw data, BI helps organizations make strategic decisions, identify opportunities for improvement, and gain a competitive edge.
You don’t need a PhD to get into BI — start with a few online courses that cover the basics, like data analysis and pattern recognition. Do some practice with popular BI tools and maybe a few YouTube tutorials, and you’ll be on your way. As you move forward, don’t overlook the power of a good BI community forum, where you can gain insight from people who have navigated this path for a long time.
To be clear: there are BI experts out there who have spent years honing their knowledge in this field. Their depth of understanding is something, but not impossible to achieve.
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Coding can be a plus when you want to go all mad scientist with your data, but it’s not mandatory. Plenty of BI tools these days are Star Wars-themed LEGO sets—they let you put together nifty data models without actually knowing the mechanics or science behind the Millennium Falcon. But dabbling in a little SQL or Python can definitely add some muscle to your BI game.
Luke Strauss Luke Sunny is a writer and content marketer from San Diego. Since earning her degree in International Management from Pepperdine University, she has channeled her passion for digital marketing and creative writing to create engaging content for organizations in a variety of verticals. When he’s not at his desk, you’ll find him at music festivals, spending time with friends and family. For any type of business, good competitive intelligence is critical to success. Business owners and marketers need to understand the competition, stay ahead of industry trends, and adapt quickly as the market shifts.
Conducting custom market research or purchasing standard market intelligence software can be potentially expensive. And cheaper options, such as “state of the industry” reports, can lose their value quickly as markets evolve. These factors often leave small to medium businesses at a disadvantage.
Fortunately, the development of competitive intelligence solutions in recent years has leveled the playing field. With affordable, powerful and usable tools now widely available, small businesses can turn the luxury of custom market research into a regular practice.
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In this post, we have compiled a list of the top 12 market intelligence tools for market research and online competitor analysis.
Before delving into details about specific competitors’ marketing strategies or product offerings, it makes sense to develop a general understanding of your overall market. Who are you competing with? Which direction is the market going? Who is getting the most attention from consumers? Questions like these can guide your strategy moving forward.
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