In the current world of digital analytics transformation, data is a critical resource. Organizations of all sizes, across different industries, have to know how to collect and process data to make the most of it. This includes the use of cloud technologies, the Internet, and especially sensors, devices, and IoT systems.
Ultimately, businesses now have access to high velocity, high-volume data from a variety of sources. Hence, all this information has to be analyzed, and that is where data analytics comes into the picture. Organizations that neglect to develop a comprehensive data strategy will most likely lose compatibility and fail behind the better-equipped ones.
What is Big Data and Data Analytics?
Big Data basically entails large volumes of structured or unstructured data that is processed with special automated tools to be used for statistics, analysis, predictions, and decision-making. Therefore, the term “big data” is also understood as technology for searching, analyzing, and using unstructured information in huge volumes.
The more we know about a specific object or phenomenon, the more accurately we comprehend its essence and can predict the future. By capturing and processing data from sensors, the Internet, and transactional operations, companies can fairly accurately predict the demand for products, and emergency services can prevent man-made disasters.
Overall, the true value of big data is measured by the level of ability to analyze and understand it. Artificial intelligence, machine learning, and modern database technologies enable us to visualize and analyze big data in near real time to gain valuable insights. Data analysis helps companies leverage the existing data to open new opportunities and develop new business models.
By capturing and processing data from sensors, the Internet, and transactional operations, companies can fairly accurately predict the demand for products, and emergency services can prevent man-made disasters.”This concept sprouts many processes and terms like data commercialisation, which are familiar with quick-adopting corporations.
5 Spheres Data Analytics has Changed
Agriculture and Farming
Big data analytics has huge potential for agriculture. For instance, there are special devices that collect various data from fields. Some need to be inserted into the ground to track the moisture level and soil content. Others are attached to vehicles to track their route, performance, and fuel consumption.
There are also weather stations to enable farmers weather forecast, services for obtaining satellite images of fields, and drones for mapping the field and assessing the current crop state. Different online tools collect data, process it, and analyze it to provide growers with valuable information in an accessible format.
There are developments for which it is not necessary to install devices on the field at all. Some platforms collect data from open sources such as government open databases or from satellites. Through them, the farmer receives information about the farm site, which can also be no less valuable than the information collected by devices directly from the fields.
In the medical field, big data can be used for diagnostics and treatment. And although most promising projects are still at the development or testing stage, there are already implemented ones.
It now becomes possible to study the effectiveness of treatment due to the processing of all available data on the treatment. Based on the analysis of all known case histories and diagnostics, the doctors will be able to use decision support systems, which will provide them with unprecedented access to the experience of thousands of colleagues across the country.
More so, the widespread use of various sensors of the human body activities measurement, connected to wearable gadgets, will reduce the need for laboratory tests and help prevent unexpected complications. And an automatic reminder of the need for independent therapeutic and prophylactic manipulations will increase the quality of the prescribed treatment.
By collecting and analyzing data about how we learn, education establishments can use the received information as valuable insights that can help them identify or create the most effective teaching strategies, highlighting the issues and transforming the delivery of education. Apart from this, data analysis can be used even for planning school bus routes or improving classroom cleanliness.
Besides, with the growing popularity of online education, big data can offer great insights into what and how people learn, leading to huge enhancements in personalized, adaptive learning.
When organizing transportation, it is not always easy to assess how quickly a vehicle will travel from point A to point B. The speed of delivery is influenced by the operational work of employees, traffic jams, the condition of the vehicle, and the location of gas stations. If you analyze the combination of these factors, obtaining data from open sources, you can effectively plan routes and manage the operation of warehouses.
Besides, big data in logistics allows for risk minimization. If a company takes into account the state of technology and monitors weather and road conditions, it can increase the safety of transportation.
Social media data analytics is one of the best examples of how big data is currently affecting our lives. Marketers can better understand customer behavior, enhance customer experience, target audience segments, and engagement by collecting information about users on social media sites. The two sides of big data on social media are micro-targeting and brand analytics in the digital marketing spectrum.
Collected, analyzed, and stored data can benefit both businesses and human lives. It can offer insights that lead to improvements in a variety of spheres. Even more so, there is no industry that big data can’t transform for the better.