Nowadays, vast amounts of data are generated every day. New data solutions and the latest technologies are needed to ensure that companies continue to be supported by data instead of inhibited by it! We present our top data trends from which companies will benefit in the future, or can already benefit.
Data processing with artificial intelligence and machine learning
The counterpart to raw data, which is often unusable without further processing, is so-called “actionable data”. This is compressed and meaningful data that is intended to support entrepreneurs in their decisions.
But there can be a lot of time and effort between these two data states. Because in order to convert raw data into actionable data, certain data tools are required, otherwise it can happen that the desired data result is never achieved! We asked our data experts what areas of application there are for Artificial Intelligence (AI) and Machine Learning (ML) in the field of data and to what extent this contributes to the creation of “actionable data”. Here come our COCUS insights on current data trends:
Data Transaction, Collection & Security
However, the basis of all data-based decisions is the initial state of the data situation. After all, even the best-equipped analysis tool is useless if the data is inconsistent. Meanwhile, IT professionals like to use technologies like ML to increase the accuracy of data and improve data sharing.
One of the areas of application here is the Internet of Things (IoT), because more flexibility can be added to the IoT network, which links a wide variety of devices via the Internet, with the help of ML. At the same time, the exchange of information between devices is becoming more precise, increasing the level of accuracy of data in the IoT.
In addition to the data situation, the type of data storage also plays an important role in being able to establish target-oriented analysis tools. Looking back over the last few years, clouds are increasingly being used as a storage location due to the constantly growing volumes of data. This is another application area for ML and AI: the technologies are used to centralise data to positively contribute to data scalability as well as data security.
For companies, it is particularly useful to embed the technologies directly into security solutions for public clouds or hybrid data services. There, without further precautions, there is a lower level of security compared to private clouds. By using AI and ML, the security risk is mitigated, making the option of going with the more cost-efficient cloud much more attractive.
The heart of the data world and successfully applied data knowledge is clearly data analysis. The preparation of data is currently still done by data scientists in many companies. In the meantime, however, modern analytical tools can also offer high-quality solutions. In addition, unlike data scientists, the tools rely on the completion of analyses.
An example of a powerful analytics tool is the data analysis concept “Augmented Analytics” (AA), which can provide insights in real time. AI, ML and Natural Language Processing (NLP) are among the technologies used in AA. NLP is used in AA, for example, to identify patterns and trends. The analysis of large amounts of data is automated with AA and nowadays provides indispensable “actionable data”. In this way, AI and ML can directly contribute to the ability to make decisions and take action! Because just generating data is no longer enough to be successful these days. You have to be able to recognise data trends and use them correctly to build a competitive advantage!
Using data trends properly
Would you like to learn which areas of application of AI, ML and other data trends are particularly suitable in your company to drive data-driven decisions? Then get in touch with COCUS!