Data mining helps companies to gather information from a number of sources and put them all together so that they can be used resourcefully. Extracting data from various sources is not easy and takes a lot of effort. This is why, a number of companies outsource data mining tasks to third-party vendors who have more temporal resources to engage in such repetitive tasks.
There are many commercial systems to boost data mining, but along with technology, data mining trends are changing very quickly too.Current trends are dominated by complex algorithms that detect market trends and patterns, which in turn help businesses to engage in a variety of business processes. These data insights also help companies to identify variations and predict events before they happen.
There are several implications when it comes to data mining but in this article we shall take a look at some important trends that will affect this process in 2018.
A lot of data mining will depend on multimedia files such as images, video, text, audio, etc. All this data will be transformed into numerical data so that it can be processed. Most businesses have begun to use multimedia data mining to identify associations and to check for similarities. As people continue to use mobile devices, the wealth of information in the form of images, auto, and video will only increase. Each day, YouTube users watch roughly 500 million hours of video, and 92% of mobile video viewers also share the same with others.
This SlideShare presentation briefly describes what multimedia data mining is, and how you can engage in it yourself.
Mobile usage is expected to explode in the coming months, especially in emerging markets such as India, Africa, and Latin America. The Hindu newspaper reported that there are roughly 478 million mobile internet users in India alone. The more people use mobile devices, the more important the data that is generated from mobile devices shall be. However, it will prove to be difficult for companies and vendors to mine data from mobile devices as GDPR rules and other regulations may penalize data mining based on mobile activity and data.
Read this article to understand data mining in the context of mobile devices.
A lot of data these days are stored in different locations. While companies may choose to store various information at different locations, consumers too use mobile devices from a variety of locations. In both the cases, location and geographical data matter quite a lot, and can be very useful for those who seek data insights. GPS location-based data is the single-most important vector in 2018 and beyond. Extracting data from sources based on location may prove to be difficult but many companies specialize in this arena.
Read this article to understand spatial data mining for location based services, which was published in the Indian Journal of Science and Technology.
Many companies have also begun to seek data related to cyclical usage, and behavior based on time. For instance, e-commerce businesses are keen to understand when people prefer to purchase during a day or when they use social media the most. Such temporal data is crucial to developing marketing campaigns and sales communication.
Temporal data mining is going to be very important in 2018 as this is closely linked to mobile usage too.Read this detailed paper to understand the nuances of temporal data mining, which is crucial in the automatic exploration of data.
2018 is already dominated by artificial intelligence and IoT devices, and the remaining few months are likely going to be the same as well. Both AI and IoT generate huge amounts of data, and the opportunities for data mining in these areas are huge. Both e-commerce and large enterprises will use AI and IoT to gather and process data, while these emerging technologies will also remain resources for data mining themselves. 47% of digitally mature companies have a defined AI strategy, while another 26% feel AI is the biggest marketing trend.
Read this insightful article that pits data mining against AI and machine learning.
There already exists large amounts of rich data, and insights derived from this data. In fact, there is an entire industry devoted to processing data and helping companies with rich insights. Data mining will also derive information from insights already derived from existing big data. This meta data will help data mining scientists to derive insights from previous insight. Statistical tools and predictive analysis will help in data mining based on meta data from various resources.
A German university recently published an article related visual data mining and how that is related to meta data.
Data mining as a profession will be affected by the recent GDPR rollout. GDPR explicitly states that one needs to have consent before someone's data is processed or used. This explicit consent maybe difficult to obtain and may force most data scientists to look for more ethical methods of data mining. However, most websites have already begun to seek permission from users for their data, and thus, data mining is not likely get affected by GDPR in the long term.
As of now, only 44% of companies are GDPR-ready, and if you haven't done it already, it is time to do so.
Read this article regarding data mining and GDPR, recently published by a legal agency.
With millions of people using mobile devices, and with millions of devices expected to be fit with sensors, the potential of data is simply too huge to even imagine. Data mining is the crown of data science, and is closely linked to the evolution of big data. Insights from data mining is regularly used by business analysts and marketers, and 2018 is not going to be any different. However, data mining techniques will continue to derive from multimedia sources, mobile devices, location-based data, and seasonal trends.
The advent of artificial intelligence and IoT will further help data mining enthusiasts to gather and process more data. However, what will underscore data mining trends is the importance given to metadata, and the ability of data mining professionals to comply with privacy regulations such as European Union's GDPR. Data mining is a complex subject and 2018 will be dominated by emerging technologies, privacy regulations, and how companies will strike a balance between the two.
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