At the first glance, it seems a little odd to say that Data Analytics is having a huge impact on agriculture, but this fact is actually the reality today. While the invention of machines had transformed the agriculture after the 16th century, it’s the data which is going to change the picture of agriculture in the coming times.
Data analytics means to analyze the data so as to access the information within that data set. Examples of the type of data analysis that business and industry do today include getting information about their employees, the methodology they adopt for their production, their customer’s buying psychology and needs, and so on. The question is why are they pursuing data analytics; what is the benefit to them? They are making all this effort to make themselves more efficient and competitive by addressing their opportunities to improve effectively and on time. The objective, through data analysis is to reach a 100 percent accuracy level; accuracy in the quantum of investment, time and effort. The methodology or the software that is used...
Data Analytics is the advanced technique of dealing with a large amount of unstructured data also known as Big Data. Its importance was first understood when industries realized that the data they’re storing can be used to improve the business and customer service.
Social media is a big part of the millennial lifestyle. People of every age, culture, country are connected and engaged through different types of social media platforms, and now with the rising of sophisticated digital devices, using social media has become easier.
Everything is made up of data. Music that we listen to, the daily news and updates we find on television and media, the messages we send and receive, everything is made up of “DATA”.
Presently, data science is one of the most highly demanded career option that many people want to pursue. It involves using various scientific methods or algorithms to extract information from different structured and unstructured data. The people who perform all these activities are called data scientist.
Data science includes domains like machine learning, artificial intelligence, deep learning and many more. Data science is a huge field which covers a lot of domains under it. In this article I will discuss more about the three above mentioned topics.
Data science is a field which requires multiple types of skills and expertise. It requires in-depth knowledge of both technical and business acumen. This is why professionals from different fields can enter big data. There are different certification courses, diplomas, bachelor and master courses, and boot camps which one can attend to get trained in different aspects of data science.
A data scientist analyzes data to find meaningful patterns. More specifically, amassing large amounts of data, both structured and unstructured, creating models and algorithms to facilitate the storage of this data, figuring the correct data sets and variables and interpreting the data to discover opportunities and solutions.