As firms grow, data handling has been an issue of concern. Data engineers have been working round the clock to solve many challenges that ever growing data poses. In fact, data continuously becomes dynamic, as these firms attempt to deliver detailed and better results. According to ActiveWizards data engineers, they need to understand the evolution of data and the importance of every step. This will help them identify where they stand and what they need to embrace. Since not many; therefore, may understand the difference between data mining and big data, this article will clarify them.
Data mining and its applications
Although detailed, this can be termed as a simple way of getting data, and analyzing it from various set dimensions into a sensible and understandable manner. The databases are large; thus, the data must be analyzed in a simple way to help users make decisions in sales and cost implications. Data mining doesn’t stop at the extraction point, it also involves management, which also covers updating of such information if need be.
For many years, chain stores like supermarkets have used this methodology to scan through their database for shopping trends, markets shares, and other useful information.
Big data and its applications
Most people fear the concept of big data and wonder if they could afford to understand it. So, what is this concept? It is a relatively new way of handling data that is too complex for the traditional methods to handle without challenges. In fact, they cannot relate, analyze, or even edit it. Therefore, new and smart ways are integrated with the data, so that variables can move with it wherever they are exported or imported.
For instance, a bank handling millions of clients can use this idea to handle client information from all branches it has. Therefore, the analytical tools to be used must be able to relate various sets of queries like clients with undue loans from branch A or B.
What is the difference between data mining and big data?
While both concepts may be considered to handle big data, they have a couple of differences. Data mining is an old way that is becoming outdated very fast due to the complexity of data over time. Organizations are now embracing big data concepts. The big data is too complex to be handled with simple tools like Microsoft access, which a couple of years ago, could be used in data mining.
On one hand, the old concept can only relate data with precise relationships using either common automation or manual filtering while the new smart way applies to complex data with various variables. Therefore, it needs to use customized software that is able to dig deep into the database, bind each data with different variables, which will be used to draw analysis, query, and interpret.
Conclusions
While both concepts can still be seen to be used, it is clear that most people must turn to big data for better analysis of their data. A reputable firm will help setup the software you need to succeed in delivering better services to your clients.
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