The Top 10 Business Analytics Terms You Should Know

These are the Top 10 Business Analytics Terms you should know. Why are they important? Because understanding these terms will influence the way you look at data and the information you glean from it. Relating these terms to your business will bring more value to your company.

What Are Business Analytics?

The technical definition (if you want to skip the jargon, head to the next paragraph): Business analytics are ingesting, consolidating, aggregating, and organizing business data, and analyzing said data to identify trends, patterns, and root causes to gain insights into business performance.

Too much technical babble? Here’s the rub:

Imagine a spice cabinet. Except all those mini glass jars filled with fragrant herbs and colorful spices are either labeled correctly, mislabeled, or not labeled at all! How do you distinguish what’s what? Salt could be sugar and cinnamon could be cumin. You could be baking a cinnamon roll but accidentally end up with spiced naan bread! Well, that’s where Data41 comes in. We can help you identify every herb/spice and label each of them properly. We can also tell you the spices you’ve been confusing for each other. On top of that, we can tell you which combinations of spices best complement each other and which to steer clear of. And what’s more is we can equip you with so many delicious recipes based on all the different permutations and combinations of spices in your cabinet. The possibilities are endless. We can organize your spice cabinet AND make you a stellar chef! So, let’s get cooking!

The 4 Types of Business Analytics

1. Descriptive Analytics: What happened? This explains the current state of the data.
   • You baked spiced naan bread instead of the cinnamon roll you intended.
2. Diagnostic Analytics: Why did it happen? This explains how the current state of the data came to be.
   • You used salt and cumin instead of cinnamon and sugar.
3. Predictive Analytics: What will likely occur in the future? This applies statistical analysis to predict future behaviors and outcomes.
   • You might mistake the spices again if you don’t properly label their jars.
4. Prescriptive Analytics: What is the optimal course of action? This is finding the best course of action for a given situation.
   • Label your jars and follow the recipes.

Other Important Business Analytics Terms

1. Big Data – This is a term that is used to describe large, hard-to-manage volumes of data that can be both structured and unstructured. Big Data inundates businesses on a day-to-day basis. But it’s not just the size, amount, and type if data that matters – it’s what the business does with the data that’s important. Big data can be mined, cleansed, and analyzed for lucrative insights. These insights can have major influence over business decisions.
   • Big Data is your disorganized spice cabinet.
2. Data Cleansing – This is the process of detecting and correcting corrupt, incomplete, inaccurate, duplicate, and otherwise erroneous records from a database. Data cleansing is also referred to as “data scrubbing,” or “data cleaning.”
   • Data Cleansing is the process of labeling and organizing your spice cabinet.
3. Database Management – This is the act of maintaining complex databases. This keeps your database up-to-date and sustains the integrity of your data cleansing.
   • Database Management is the upkeep of your spice cabinet. It keeps it clean, labeled, and fully stocked.
4. Data Visualization – This is the science of deriving meaning from data sets by using visual aids like pie charts, histograms, scatter plots, heat maps etc. Data visualization plays a major role in illustrating the story your data is telling.
   • Data Visualization is like a recipe book tailored to all the spices in your cabinet and ingredients in your fridge. It’s also a catalog of all the things you’ve cooked before, and all the new recipes you have yet to try.
5. Data Transformation – This involves mapping and applying custom business logic to cleansed data with the goal of organizing business information for storage and consumption.
   • Data Transformation is like meal prepping based on the spices and ingredients you have and the flavors you’re craving this week.
6. Time-Series Forecasting – This is the process of making predictions based on historical time-stamped data. It applies statistical modeling to a time-series and forecasts that into future time periods.
   • Time-Series Forecasting is like crafting a menu for guests you’ve cooked for before. You already know their preferences and dietary restrictions, and now you’re cooking meals based on this knowledge.

Conclusion:

Understanding these business analytics terms should give you the confidence and the awareness to extract the most out of your data. Your data is rich with constructive feedback and information that can transform your organization for the better. If knowledge is power, data is its renewable energy source. Data41 can set you up with advanced analytics software like IBM Cognos Analytics or IBM Planning Analytics to reap the benefits of your data.

Contact us for a free discovery consultation!

Related resources:

https://www.ibm.com/analytics/big-data-analytics

https://www.businessnewsdaily.com/8655-predictive-vs-prescriptive-analytics.html

https://www.simplilearn.com/what-is-database-management-article