What is a Business Intelligence Analyst?
If you’re reading this, you’re likely aware that data is currency in marketing. Data is how you know your marketing worked, how you know it didn’t work, and how you know what to change in the future.
Wait up a sec… we should add that data is just the start of all of that. Data in and of itself isn’t worth that much, unless it can be coerced into something meaningful. To show you what we mean, let us introduce the DIKW hierarchy.
You see what we mentioned in the intro is true, but only using the popular conception of “data.” Technically, data in and of itself doesn’t tell us much until it’s processed. What do we mean by processed? Well that depends on how much (and how quality) the processing is. To illustrate this point, here are examples of what constitutes each step of the DIKW heirarchy:
- Data includes logs, measures, addresses, phone numbers, names, number of clicks, and so forth, but without any interrelationships mapped. Data in and of itself does not answer any meaningful questions, but is rather the material out of which answers can be constructed. To fully illustrate this point, data is just a collection of symbols. On it’s own it might as well be written in a language foreign to you. What many people commonly refer to as data is actually information.
- Information is what many people mistakenly refer to as data. Information is data with a context, or that has been organized into a structure. A list of subscribers to a service and their ages is data. Wrangling the data to provide percentages in certain age groups is information. Following the example, once you know that 90% of your subscribers have kids and are in their 40’s, you can start to answer questions like “who, what, when, where.” Creating information through the processing and refining of data is a crucial portion of a business intelligence analyst’s role.
- Knowledge is more abstract than information, but easy to identity when we see it. Knowledge applies personal experience and mental rules (whether knowingly or unknowingly) to information. Put simply, knowledge answers “how” to implement or integrate understandings from information. Knowledge is often exhibited when information is provided to high-level decision makers or those experienced in their field. Knowledge is knowing what to do with your information.
- Wisdom can be seen as related to knowledge over time. In a business setting, wisdom extrapolates from knowledge and faces the future. Application of a businesses’ values, providing vision into the future based on knowledge, and having the leadership to provide this vision are what wisdom is all about. While elusive, wisdom is seen through “visionary” acts informed by information and knowledge.
- Technologies
- Applications
- And practices
Training of Business Intelligence Analysts
Business intelligence analysts may come from a variety of academic backgrounds or be self taught. With this said, most major employers require at least a bachelor’s degree for business intelligence roles. While any quantitatively-focused major will do including hard sciences, math, computer science, or engineering, many “softer” degrees coupled with training in informational analysis tools and business processes will also do. As a great deal of data gathered in business settings has to do with the presentation and honing or services or products, marketing is a common degree for business intelligence analysts. Many bachelor’s level degrees in marketing work on data literacy and learning about the types of information that are useful in marketing settings. Master’s degrees in either marketing, data analytics, or business administration further hone marketing-specific tools and data management processes. For those interested in business intelligence, yet who have degrees in other fields, graduate certificates in marketing may also provide a time and cost effective way to hone skills in the field.Tools of Business Intelligence Analysis
We’ve mentioned a few of the routes to learning tools needed for business intelligence analysis, but what exactly are these tools? Depending on your precise role in your team, business intelligence analysis can range between fully data science-centered roles (more technical) all the way to report creation (less technical). Categories of tools used in this process include the following:- Spreadsheets
- Online Analytical Processing
- Reporting and querying tools
- Digital dashboards
- Website Analytics Services
- Data Mining Technologies
- Business Activity Monitoring Tools
- Data Warehousing Practices and Tools
- And Data Cleansing Techniques and Tools
- Microsoft Office or Google Sheets
- IBM Cognos or Micro Strategy
- BIRT Report or Jasper Reports, SQL
- Tableau or Domo
- Google Analytics among others
- Scripting languages or pre-built tools
- TaskCentre or KnowledgeSync
- Ab Initio Software or Amazon Redshift
- OpenRefine among others
