Currently, Data Analytics is gaining worldwide attention because of its importance to the business. According to Jeff Bezos – CEO of Amazon – who built a powerful Amazon empire, one of the reasons for Amazon’s success is the way people use and analyze data to serve their work.
What is Data Analytics?
According Investopedia.com, Data analytics (or data analysis) is the science of analyzing raw data in order to make some meaningful conclusions about that information.
Data Analysis is the process of converting raw data into useful information for businesses
The job is to collect and organize a huge amount of data (Voice of customers, personas, market research, etc.) and then convert it into condensed and understandable information (insights). This information will then be used by various departments within the company to come up with accurate strategies or decisions to help grow the business.
Why is Data Analytics important for Business
Analyzing and working on raw data can measure related matters which are of company’s concern, which could make the work more transparent and clear. In addition, the data can tell people the status of the work and have effective methods to improve, which would not be based entirely on intuition or feelings.
For example, a brand/company has millions of customers and thousands of agencies across the country. By the end of the month or quarter, managers want to know how the business situation in the domestic markets proceed to make reasonable strategies.
They need to conduct market research and surveys with actual and specific data. Then, they need to gather information, organize and analyze to know the reaction of customers with current products in which area have the positive/negative behavior? Why? What needs to maintain? What needs improvement? What are the trends?
Understanding the needs and satisfying of customers are important factors for the business to become successful and growth.
Every industries all need Data Analytics
Based on a survey on datafloq.com, there are top 5 industries that should have Data Analytics continuously and periodically:
- Healthcare & Pharmaceutical
- Telecommunications Sector
- Internet Industry
- Energy Sector
- Automotive Industry
However, because of the advantages that Data Analytics bring, all business from SMB to large enterprises around the world are exploiting the power of data to enhance their services and revenues nowadays.
Types of Data Analytics
There are 4 types of Data analytics:
Descriptive analytics is the explanation of historical data to better understand the changes that have occurred in a business. Descriptive analytics describes the use of a range of historic data to draw comparisons.
Diagnostic analytics are looking on the processes and causes, instead of the result. It focused on why something happened rather than what has occurred.
In Predictive analytics, we need to then build a model to project what could happen in the future based on certain things happened.
Prescriptive analytics is considered an extension of predictive analytics. It requires complex algorithms in order to accomplish such machine-based decision-making.
If your business has strong analytics with data in this era, your company is on a lucrative path.
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