Most Business Managers use Data Analytics and Business Analytics terms interchangeably. However, there is subtle difference between these terms and subtleties are based on the end usage of the analysis. In this blog, we will try to understand these minor but important differences between Data Analytics and Business Analytics.
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What is Data Analytics?
Data Analytics uses Data mining techniques to generate insight. It may report on historical information or it may provide predictions about future events; the end goal of data analytics is to add value through insight and turn data into information. Common examples of Analytics include:
- Reporting the data summary
- Identification of Patterns in data
- Classification of observations using historical data
- Prediction of future events using historical data
- Segmentation of data
All Data Analytics applications are based on following basic tenets:
- They are based on data
- They use statistical and mathematical techniques to generate data summary and predictions
- They add value to the data and transform it into knowledge
In short, analytics techniques are used to understand why things are happening and predict what will happen.
What is Business Analytics?
Business Analytics leverages all forms of analytics to achieve business outcome. It’s a small difference but it is important. Business Analytics extend traditional Data Analytics by including:
- Business problem in specific domain (for e.g. marketing, finance, HR etc.)
- Actionable insight that can be implemented in specific domain
- Performance measurement to check the effectiveness of Actionable insight
Data Analytics can generate great deal of knowledge by applying various forms of analytics. Business Analytics however, makes a difference between relevant knowledge and irrelevant knowledge. This difference is based on business’ strategic objectives. For e.g. analyzing company sales data can generate wealth of information, but not all that information may be relevant if the business objective is to optimize the inventory turns.
The Difference
The main difference between the areas of data analytics and business analytics is the level of daily interaction with tech and data versus business and decision-making. As you may imagine, a data analyst is more focused on the former, whereas business analysts on the latter.
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If analytics is about finding interesting information from large amount of data, business analytics is about making sure that this information has contextual relevancy and delivers business value.
Analytics focuses on creation of insight and not necessarily on what should be done with the insight once it is created, business analytics recognises that creating insight is just a small step in larger scheme of things which involve implementation of actionable insights and value generation.
If only the insight is considered in isolation, it may lead to develop series of outcomes that may not be implemented in broader organisational context.
For e.g. series of analytics models may be developed, that are highly accurate, but impossible to integrate into the organisations’ operational system. Referring back to our inventory optimization example, if the optimization models are not compatible with organisations’ current inventory management systems, or other operational systems, the value of the insight may be high, realised value is negligible.
By approaching same problem from Business Analytics perspective, the same organisation may be willing to sacrifice the model accuracy for ease of execution, ensuring that economic value is delivered.
A model that is 80% accurate, but which is easy to implement creates far more value than an extremely accurate model that can’t be deployed.
This operational aspect forms key difference between data analytics and business analytics.
Summary
Data Analytics is concerned in generating an insights from the data, however Business Analytics gives contextual relevancy to the analysis. Business analytics is the use of data-drive insight to generate business value.
Analytics without business analytics creates no return – it simply answers the questions.