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What is data analysis?
Data analysis is part of data science technology. In a nutshell, data analysis is a technique that leads the data scientist to a conclusion of all the information he has analyzed. Data analysis is used to examine data sets. It is understood what the data is about and what information it provides. Data scientists carried out using various specialized software. Data analysis is used in the industry. The technique helps companies make more decisions based on information. Companies use a data-based approach.
Data analysis has proven to be very beneficial for companies. The technique helps companies increase revenue and improve efficiency, optimize marketing campaigns and customer service efforts, and gain competitive guidance on their competitors. In addition, the data can be historical information as well as new information. Both are used in the analysis.
DATA SCIENCE, BIG DATA, AND DATA ANALYSIS
Data science, big data, and data analysis: these three terms appear to be the same, but they are different. Big Data and data analysis are two techniques that are part of data science technology. Below is a detailed discussion of exactly what these technologies are and the skills needed to work on them.
What is data science?
Data science is a technology that includes everything related to data preparation, data analysis, and data cleaning. Data science technology processes structured and unstructured data. In addition, data science technology is a mixer of statistics, problem-solving, math, data capture, etc. Data scientists have the ability to visualize data in a new way. To conclude, data science technology is the combination of all these techniques that are used to extract useful information from large data sets.
APPLICATIONS OF DATA SCIENCE
Data science technology is widely used in the following areas:
internet search
Recommendation systems
Digital ads
WHAT ARE GREAT DATA?
Big data is a great data set. Big data is too big, so we cannot process this data with traditional data processing methods. In addition, this large data is very inefficient to store in the memory we have. Today, big data is used in business to make more informed decisions and obtain information about useful information.
In addition, large data is not defined exactly by saying that it is a large amount of data. Big data is that information that has more volume, at high speed and with a great variety. More volume means that the size of the data must be large; a high speed means that the speed of data generation must be high and a variety of data means that the data must be of different types so that more information can be extracted from them.
CONCLUSION
As noted above, not all of these technologies are the same, but their purpose is to extract useful information from the data sets. In addition to analysis, there are many areas in data science technology. Students can choose them based on their area of interest and can participate in a course on them.
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Address: 360DigiTMG - Data Science, IR 4.0, AI, Machine Learning Training in Malaysia
Level 16, 1 Sentral, Jalan Stesen Sentral 5, KL Sentral, KL Sentral 50470 Kuala Lumpur, Malaysia
Contact : 011-3799 1378
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