Analysis vs Analytics
Introduction:
It is often observed in the tech community that the terms analysis and analytics were used interchangeably. Recent adoption of data science and predictive analytics by different sectors is creating buzz in the job markets with which more and more new job roles are emerging in data science around the globe. Ironically, even the job descriptions nowadays are misleading the aspirants by interchangeably using these two terms.
But, technically these two terms have different meanings and are used in distinct cases. In this short article, let us try to understand this jargon with simple examples.
What is Analysis?
Analysis is defined as the process of investigating why something has happened in the past.
Usually in businesses, If we want to understand the underlying business performance of a company, we’d be analyzing the variance of a financial item such as revenue, budget, sales etc.. And the way we do these assessments is by using data we have gathered about our performance so far.
The distinct thing about analysis is that we to interpret events that have already happened in the past. Essentially, when you are doing analysis, you look backward in order to understand how your company has performed against the expectations of your stakeholders.
Examples:
- Explaining how and why there was a low customer satisfaction for our recent product.
- Why are some of the sales reps performing low?
- Why has there been a decline in the active users on the platform last quarter etc
What is Analytics?
A typical analyst’s work involves converting the stakeholder’s expectations into meaningful numbers that consolidate with the long range plan and goals of the organization. In order to forecast or predict these numbers to put in place, we use analytics. Simply, analytics involves predicting the future values or performance of an organization by accessing the present situation of the firm.
Analytics is essentially the application of logical and computational reasoning to the component parts obtained during analysis. And, in doing this, you are looking for patterns and key trends in the data and exploring what you could do with them in the future.
To put that straight, analytics helps the top management or stakeholders of the company to access their future goals and develop strategies accordingly to meet them.
Examples:
- Predicting the stock price of a company
- Estimating the customer churn for the next month.
- Estimating the number of new customers on our OTT platform.
Conclusion:
To conclude, the terms analysis and analytics serve different purposes. Analysis explains about why or how something has happened in the past whereas Analytics deals with predicting how something is going to change or impact the organization. Although, both deal working with data and addressing the needs of the stakeholders, the type of data and tools used in both the processes vary.
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