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Data analytics is the science of analyzing data in order to draw insights and make decisions.
While related, it is important to note that data analytics is different from data mining. Where data mining extracts information from large data sets, data analysis inspects, cleans, transforms and models the data to identify patterns and insights that influence business objectives.
| Step | Type | Description |
|---|---|---|
1. Analyze what happened |
Descriptive Analytics | Provides insights into the past performance of key business metrics
|
| 2. Analyze why it happened | Diagnostic Analytics | Supplements descriptive analytics by taking those findings and digging deeper to understand the root causes< |
| 3. Project what will happen | Predictive Analytics | Builds on the root causes of findings and past events in order to forecast what may happen in the future |
| 4. Determine what should happen | Prescriptive Analytics | Reviews all analysis findings to understand what happened, why it happened and whether it’s likely to happen again, but most importantly to prescribe what to do about it |
These types of data analysis techniques each uncover insights that many businesses need in order to be effective. However, when they are used in combination, they provide a big picture view of a business’ needs and areas of opportunity.
The insights gained by creating and testing theories using a business’s data can result in increased operational efficiency and improved business performance. For example, identifying trends in manufacturing downtime can assist with capacity planning. Similarly, proving what works best for consumer engagement can help improve customer satisfaction.
Here are a few more examples of areas of business that can be influenced by data analysis:
Why is Data Analytics Important?Data analytics is an important field in modern business. Now that organizations can track almost everything digitally, they have to find ways to deal with big data. Knowing how to extract value from data is a modern business challenge, making the data analysis field more attractive than ever.
Data analysts are needed to help businesses properly store and understand their data both consistently and efficiently. With skilled analysts working behind the scenes to understand their data, businesses can make better decisions and improve customer satisfaction.
1DeVry University is accredited by The Higher Learning Commission (HLC), www.hlcommission.org. The University's Keller Graduate School of Management is included in this accreditation.
2Not including breaks. Assumes year-round, full-time enrollment.
