5 Trends of data analytics in 2019 to look out for

Data analytics is growing rapidly and this year is proving to be no exception. Analytics platforms offer tremendous value and many companies are eager to take advantage of this technology. So, what does 2019 hold for the future of data analytics? We explore the five trends that will see a shift in data, machine learning and how companies are using them.

The shift from single to multi-platform cloud platforms.

We are going to see a shift from single cloud platforms to using multiple cloud platforms. As companies realise the benefits of cloud over legacy systems, we are going to see more and more companies shift their data. Thus, companies will not store cloud-only data but also mission-critical data. The benefits of cloud are compelling: On-demand capacity, low-cost storage and a useful array of tools, make cloud the preferred storage method. Hence, we are going to see hybrid cloud systems, with the option to calibrate and distribute between different systems. The option will be vital, as more companies use the cloud as the main storage method.

Focus on getting a single view of data

Data continues to grow in volume and capacity, capturing a myriad of variables. For example, cars contain 50 sensors that capture terabytes of data in seconds. A large volume of data is useful but only if humans can understand it. Therefore, one of the biggest trends we will see in 2019, is the ability to converge different data formats and variables into a single view. In the past, converging data has been very difficult to do. However, 2019 has seen two interesting developments that will make data convergence feasible.

The first is the standardisation of data formats, with different cloud vendors standardising data models. Secondly, we are seeing the emergence of data catalogues, where firms can buy data, making it easier to merge it into a single view.

The rise of Behavourial Data analytics

2019 will see more companies use Behavioural Analytics. What is Behavioural Analytics? An advanced data algorithm that allows users to study consumer behaviour and predict how they might act in the future. Studying consumer behaviour is nothing new in marketing, however, with behavioural analytics, marketers can take into account a host of factors, like macroeconomics.

Furthermore, behavioural analytics allows companies to get a far more accurate idea of how consumers will react to future events, planned or otherwise. The level of uncertainty is unheard of and will be a huge boon for corporations.

Edge computing becomes more important

When using traditional data analytics models, companies have to deal with a host of problems like latency, bandwidth capacity and connectivity. However, edge computing can take all these problems away by analysing data close to its source. Edge computing refers to computer machines far away from the central computer system and close to the origin of data. As IoT proliferates, the technology will generate billions of data points putting central computer infrastructure under severe strain.

Edge computing will play a vital role because it can collect and analyse data in real time. Thus, instead of receiving raw data, computer infrastructure will receive processed information and reducing strain on infrastructure, bandwidth capacity and network latency. We will see edge computing spread into different industries ranging from autonomous vehicles to fleet management.

More regulatory schemes

In May 2018, the European General Data Protection Regulation (GDPR) was passed. The act restricted the amount of personal data that can be collected. With this development, it is a given that we can, and should, expect more regulatory schemes planned or implemented in 2019. Data security will also be a huge issue because cyberattack will be far more sophisticated, costing companies millions, if not billions, in losses. Thus, firms will invest in robust security systems.

Key takeaways

As companies realise the potential of data analytics, we will see more firms invest in data analytics platforms. We are going to see new technologies that support data analysis, technologies like hybrid cloud platforms, edge computing, behavioural analytics, and focus on giving data a single view. Third-parties like the government and companies will invest in tighter regulatory frameworks and data protection schemes. Overall, 2019 we will see an expansion of technologies that support data analytics.

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