Home »
Big Data
Difference between BIG DATA ANALYTICS and DATA MINING, future scopes of BIG DATA
In this article, we are going to learn about big data analytics and data mining, future scopes of big data.
Submitted by Uma Dasgupta, on August 08, 2018
There arises a confusion among most of the people between Big Data and Data mining. In this article, I will try to make you understand the difference between both and later on we will focus on the future scopes of Big data.
Big data and data mining are two completely different things. The only similarity between them or we can say that the only thing that relates to big data and data mining is the use of huge data sets that serve business or other purposes. But both Data mining and big data analysis are used for two different operations.
Big Data Analytics
This is a process mostly used by different companies to analyze larger data sets with the objective of discovering the information of their need. It is commonly done to know the market trends, the customer’s interests, their preferences, hidden patterns, and the uncovered correlations. This analytics usually lead to new business opportunities, improvement of operational efficiency, improves the marketing successful fulfillment of public demands (preferences of customers).
Most of the companies nowadays depend on big data analytics to suggest them/advice them in making different kinds of business strategies.
Big data analytics can also be used to analyze data that might not have been discovered yet by conventional business programs. This includes:
- Analyzation of response e-mails of a public survey.
- Analyzation of data from different sensors connected to the Internet of things.
- Social media data aggregation and activity reports.
Big data analysis a very fruitful option for establishments and giving a good rise to the business of companies. But the problem that lies in the implementation such as:
- Cost of hiring big data experts are quite high.
- It becomes a huge challenge to the management to handle such a big amount of data.
- Integration of Hadoop systems and data warehouse presents another great challenge.
Figure: Big Data Analytics
Data Mining
Data mining is also defined as knowledge discovery. It is observing the data from a different viewpoint and preparing a summary containing useful information. The resultant information of data mining is usually used to reduce operational expenses. The software programs that are used in data mining are among the programs that are used in data analysis.
Technically, we can say that data mining includes discovering patterns or relations in large areas of related databases.
Data mining is done to assist the extraction of previously unknown patterns of data, including abnormalities present in data records, cluster analyzation of files containing data.
Figure: Data Mining
Future Scopes of Big Data
If you are still confused about your field and still in search of options, here are some reasons that will surely drag your attention towards BIG DATA.
DEMAND:
There is rising demand for analytics professionals in the corporate world nowadays.
Figure: Job trends in BIG DATA
SALARY:
As a high demand data analysis, need of skilled professionals are also rising, this is making Big data pay big bucks for the right skill, and it is not only limited to India its flowing over countries like Australia, U.K etc.
PRIORITY:
It is among the top priorities of MNCs and other companies, ruling the whole market worldwide.
Figure: Priority of BIG DATA
JOB TITTLES:
- BIG DATA ANALYST
- BIG DATA ENGINEER
- BIG DATA ARCHITECT
- BIG DATA ANALYTICS BUSSINESS CONSULTANT
- BUSSINESS INTELIGENCE AND ANALYTIC CONSULTANT
Figure: Job analytics of BIG DATA
Conclusion:
Till now, I hope I am able to make you all understand the difference between BIG DATA ANALYSIS and DATA MINING, and futures scopes in BIG DATA. If you have any query or suggestion please do post it in the comment section, will surely focus on them. In my upcoming articles, we will be discussing more BIG DATA and upcoming trends of IT World, till then stay healthy and keep learning!